2017年
（一）
Report topic: Cloud-Based Privacy-Preserving Parking Navigation
Reporter: Xiaodong Lin, Associate Professor, University of Ontario Institute of
Time: Friday, October 21st, 9:45 -10:45 a.m.
Location: Room 313, computer building
Abstract: Finding a vacant parking space in a congested area is always time consuming and frustrating for drivers. It is common for drivers to keep circling within a parking lot for a parking space. Study shows that in crowded area, such vehicles cause an average 30% of the traffic on the road. Real-time parking information can avoid vehicles being cruising on the roads. However, when the drivers are acquiring parking information, their privacy is inevitable to be disclosed. For example, some navigation applications, offered by Google and Apple, collect drivers' locations and destinations, which may reveal sensitive information about the drivers' personal lives.
In this talk, a Cloud-based Privacy-preserving pARking Navigation system (CPARN) through vehicular communications is presented to minimize drivers’ hassle and preserve drivers' privacy. In this system, a cloud server guides drivers to vacant parking spaces close to their desired destinations without exposing the privacy of drivers, including drivers’ identities, preferences and routes. Specifically, CPARN allows drivers to query vacant parking spaces in an anonymous manner to a cloud server that maintains the parking information, and retrieve the protected navigation responses from the roadside units (RSUs) when the vehicles are passing through. CPARN has the advantage that it is unnecessary for a vehicle to keep connected with the queried roadside unit to ensure the retrievability of the navigation result, such that the navigation retrieving probability can be significantly improved. Further, an efficient encrypted data search approach based on Bloom Filter is presented to reduce response delay during the retrievability of navigation responses from RSUs, as well as save storage space at RSUs. In the end of this talk, we will show some directions in vehicular ad hoc networks that still deserve further investigations and efforts.
Personal profile: Xiaodong Lin received the PhD degree in Information Engineering from Beijing University of Posts and
His research interests include wireless communications and network security, computer forensics, software security, and applied cryptography. Dr. Lin serves as an Associate Editor for many international journals. He has served or is serving as a guest editor for many special issues of IEEE, Elsevier and Springer journals and as a symposium chair or track chair for IEEE/ACM conferences. He also served on many program committees. He currently serves as Chair of Communications and Information Security Technical Committee (CISTC) – IEEE Communications Society. He is a senior member of the IEEE.
(二)
Reporter：Prof. C.-C. Jay Kuo (
Report topic1: Big Visual Data Analytics and Deep Learning
Time: Monday, October 24th, 15:00-16:15 p.m.
Location: Lecture hall of
Abstract：In the first part of this talk, I will introduce two very large image databases that are available to academic researchers. The first one is the ImageNet, which consists of 1.4 million object images. It is widely used for performance benchmarking of object classification and detection techniques. The second one is the Places database, which consists of 2.4 million scene images. It is used for performance evaluation of scene understanding algorithms. The availability of these large-scale databases enable the rapid development of the Convolutional Neural Network (CNN) and deep learning technology in recent years. The deep learning technology offers superior performance in many computer vision and image processing applications. In the second part of this talk, I will share our experience and shed light on its superior performance. In particular, I will present a filter theory to the understanding of CNN and the design of more effective CNN.
Report topic2: How to Mentor Young Researchers: Sharing of My Experience at USC
Time: Monday, October 24th, 16:15-17:30 p.m.
Location: Lecture hall of
Abstract:I have often encountered questions such as “How to mentor young researchers?” “How do you run a large research lab at USC?” It is actually not easy to give simple answers to these questions. Growth of young researchers depends on several factors:motivation, ambition, problem selection, research environment, guidance and feedback, writing and presentation. Furthermore, most young researchers such as MS/PhD students and post-docs pay little attention to the management issue such as time, objective, resources and teamwork management. If a graduate student can be more sensitive to his/her resource management, it is likely that he/she will graduate in a timely manner. The management skills become even more important, when a person starts to work after graduation. I received little training in management myself in the PhD program. However, during my career, I have gradually learned management skills to meet several challenges. I feel that this knowledge will be very beneficial to MS/PhD students, if they are sensitive to the need in an early stage. In this talk, I will share my own research experience at MIT and USC and my experience of running a large research lab at USC. Quite a few principles should be beneficial to students as well as faculty.
Personal profile：Dr. C.-C. Jay Kuo received his Ph.D. degree from the Massachusetts Institute of Technology in 1987. He is now with the University of Southern California (USC) as Director of the Media Communications Laboratory and Dean’s Professor in Electrical Engineering-Systems. His research interests are in the areas of digital media processing, compression, communication and networking technologies. Dr. Kuo was the Editor-in-Chief for the IEEE Trans. on Information Forensics and Security in 2012-2014. He was the Editor-in-Chief for the Journal of Visual Communication and Image Representation in 1997-2011, and served as Editor for 10 other international journals. Dr. Kuo has guided 136 students to their Ph.D. degrees and supervised 26 postdoctoral research fellows. He is a co-author of about 250 journal papers, 900 conference papers and 14 books. Dr. Kuo is a Fellow of AAAS, IEEE and SPIE.
Dr. Kuo received the 1992 National Science Foundation Young Investigator (NYI) Award, the 1993 National Science Foundation Presidential Faculty Fellow (PFF) Award, the 1994 USC Northrop Junior Faculty Research Award, the 2007 Okawa Foundation Research Award, the 2010 Electronic Imaging Scientist of the Year Award, the 2010-11 Fulbright-Nokia Distinguished Chair in Information and Communications Technologies, the 2011 Pan Wen-Yuan Outstanding Research Award, the 2014 USC Northrop Grumman Excellence in Teaching Award, the 2016 USC Associates Award for Excellence in Teaching, the 2016 IEEE Computer Society Taylor L. Booth Education Award, the 2016 IEEE Circuits and Systems Society John Choma Education Award, the 2016 IS&T Raymond C. Bowman Award and the 2017 IEEE Leon K. Kirchmayer Graduate Teaching Award.
（三）
Report topic: Location, Location, Distance---An Expedition between Geometry and Networks
Reporter: Jianping Pan, Professor,
Time: Tuesday, December 20th, 10:00-11:00 a.m.
Location: Room 313, computer building, Jiulonghu campus
Abstract: Many performance metrics in wireless networks are ultimately nonlinear functions of the distances between transmitters, receivers and interferers. For a given network coverage and a distribution of random users within the network, how to characterize the distances among these users in the same or neighbor cells or clusters becomes a challenge and a prerequisite to accurate system modeling and analysis. This talk presents some recent updates in Geometrical Probability for random distances associated with triangles and rhombuses (e.g., cell sectors with highly directional antennas), hexagons (e.g., cellular systems and ad hoc networks) and trapezoids (e.g., cell edge users) with or without a reference point, as well as arbitrary polygons, shows their wide applications in wireless communication networks, device-to-device (D2D) communications and other research areas, and compares them with some existing, state-of-the-art approximation approaches.
Personal profile: Dr Jianping Pan is currently a professor of computer science at the University of Victoria, Victoria,
（四）
Report topic: Cross-Domain Cyber-Physical Systems for Intelligent Transportation in Smart Cities
Reporter: Dr. Tian He，University of
Time: Wednesday, January 4th, 10 a.m.
Location: conference room 313, 3rdfloor, computer building, Jiulonghu campus
Abstract: For the first time ever, we have more people living in urban areas than rural areas. Based on this inevitable urbanization, my research aims to address sustainability challenges related to urban mobility (e.g., energy consumption and traffic congestion) by data-driven applications with a Cyber-Physical-Systems approach (CPS, also known as a broader term for Internet of Things), which is a new information paradigm integrating communication, computation and control in real time. Under the context of a smart cities initiative proposed by the White House, in this talk, I will focus on CPS related to large-scale cross-domain urban systems, e.g., taxi, bus, subway, cellphone and smart payment systems. I will first show how cross-domain data from these systems can be collaboratively utilized to capture urban mobility in real time by a new technique called multi-view bounding, which addresses overfitting issues of existing mobility models driven by single-domain data. Then I will show how the captured real-time mobility can be used to design a practical service, i.e., mobility-driven ridesharing, to provide positive feedback to urban systems themselves, e.g., reducing energy consumption and traffic congestion. Finally, I will present real-world impact of my research and some future work about CPS for smart cities.
Personal profile: Dr. Tian He is currently a full professor in the Department of Computer Science and Engineering at the University of Minnesota-Twin City. He received the Ph.D. degree from the University of Virginia, Virginia. Dr. He is the author and co-author of over 200 papers in premier network journals and conferences with over 19,000 citations (H-Index 57). Dr. He is the recipient of the NSF CAREER Award (2009), McKnight Land-Grant Chaired Professorship (2011), George W. Taylor Distinguished Research Award (2015), China NSF Outstanding Overseas Young Researcher I and II (2012 and 2016), and five best paper awards in international conferences. Dr. He have served a few general/program chair positions in international conferences and on many program committees, and also have served as an editorial board member for six international journals including ACM Transactions on Sensor Networks and IEEE Transactions on Computers. His research includes wireless sensor networks, cyber-physical systems, intelligent transportation systems, real-time embedded systems and distributed systems, supported by National Science Foundation, IBM, Microsoft and other agencies.
（五）
Report topic: Towards learning analytics based on cognitive modeling
Reporter: Dr Guandong Xu (
Time：Monday, January 16th, 10:00 a.m.，
Location: conference room, 4thfloor, computer building，
Abstract：The wide use of computer aided educational settings boosts the research in educational data mining and learning analytics. In this talk we are going to report our recent studies on deep learning analytics based on cognitive modelling. We propose a fuzzy cognitive diagnosis model to mine the specific skill proficiency of the examinees based on their performance of objective and subjective problem. We design a Bayesian network based method to detect “slip & guess” from examinees’ responses with the obtained skill proficiency. We study the gaming-the-system behaviour in intelligent tutoring systems and develop a framework that models student learning by combining the knowledge and gaming factor based on multiple-attempt responses.
Personal profile：Dr Guandong Xu is an Associate Professor (Reader) at the School of Software and the Advanced Analytics Institute, University of Technology Sydney. His research interests cover Data Mining, Web Analytics, Text Mining, Recommender Systems, Social Network Analysis and Social Media Mining. His research has gained grant funding from Australian and Chinese governments, e.g., ARC and NSFC grants, and projects from industries. In last ten years, he has had over 100+ publications including TOIS, TNNLS, TIFS, TSC, Inf Sci, IJCAI, AAAI, WWW, ICDE, ICDM, and CIKM. He is the Assistant EiC of WWW Journal. He received Australian BigInsight Data Analytics Award in December 2016 due to his significant impact on Best Customer Value.
（六）
Time: Tuesday, February 28th, 10:00-12:00 a.m.，
Location: conference room 413, 4thfloor, computer building, Jiulonghu campus, SEU
Report topic（一）: Introduction to School of Computer Science and Engineering, Nanyang Technological University
Reporter: Dr Kwoh Chee Keong (NTU)
Report topic（二）: Cyber-security, the Journey from Formal Methods, Program Analysis to Data Analytics
Reporter: Dr Yang Liu (NTU)
Abstract: Cyber-security is a complex system research, which requires the knowledge and understanding cross all layers of the computer architecture. In this work, I would like to share our attempts to solve security problems using various techniques. Starting from formal methods, we have applied formal modeling and reasoning to security designs and implementations on the topics related to security protocols, virtualization systems and Android apps. These efforts lead to our recent research project Securify A Compositional Approach of Building Security Verified System, which aims at building secure and verifiable systems ground-up. Security verification and building attack-free systems are very challenging tasks in view of the size and the complexity of the systems. To solve the scalability problem, we start to explore various program analysis to enhance the state-of-the-art malware and vulnerability detection, which generates encouraging results in Javascript/Android malware and binary vulnerabilities hunting. Along the way, we have collected size malware/vulnerabilities samples, which are currently used to improving security analysis, understand the security trend, attack attribution/correlation and eventually provide high-level intelligence.
Short Bio: Dr Liu Yang graduated in 2005 with a Bachelor of Computing (Honours) in the National University of Singapore (NUS). In 2010, he obtained his PhD and started his post doctoral work in NUS, MIT and SUTD. In 2011, Dr Liu is awarded the Temasek Research Fellowship at NUS to be the Principal Investigator in the area of Cyber Security. In 2012 fall, he joined
Dr. Liu specializes in software verification, security and software engineering. His research has bridged the gap between the theory and practical usage of formal methods and program analysis to evaluate the design and implementation of software for high assurance and security. His work led to the development of a state-of-the-art model checker, Process Analysis Toolkit (PAT). By now, he has more than 150 publications in top tier conferences and journals and is leading a research team of 30 researchers.
（七）
Report topic: Solar + Storage + IoT = $30 Trillion
Reporter: Srinivasan Keshav,
Time: Thursday, May 11th, 10:00-11:00a.m.
Location: Room 313, computer building, Jiulonghu campus
Abstract：Recent technological advances in the areas of solar photovoltaics, Lithium-Ion-based energy storage, light emitting diodes, and the Internet of Things will substantially change the energy, electrical grid, building, and transportation sectors. Some experts estimate that these will result in economic activity of about $30 Trillion over the next two decades. In this talk, I will touch upon the recent advances in these technical areas and speculate on their economic impacts. I will also present some recent results from my research group that attempt to address these changes.
Personal profile: Professor S. Keshav received a B.Tech in Computer Science and Engineering from IIT Delhi in 1986 and a Ph.D. in Computer Science from the
（八）
Report topic: Computational biology, mechanotransduction and autoimmune diseases
Reporter: Dr. Christine Nardini, CNR IAC Mauro Picone research institute in
Time: Thursday, May 18th,10:00 -11:00 a.m.
Location: conference room 213, 2ndfloor, computer building，
Abstract: With the technological revolution brought in by high-throughput biology, exact sciences have fiercely entered the realm of live sciences, with approaches supporting applications ranging from molecular biology to medicine, with the recent and particular focus on evidence-based medicine.
Over the time of this talk I will present the tools we developed with bases rooted in engineering and exact sciences (network construction, reconstruction and simulations) to approach a specific theme in medicine: degenerative diseases, a class of systemic, often autoimmune and chronic maladies, with no cure, consequent high societal costs and spreading at very fast pace worldwide.
In particular, with the design of a clinical pilot study in animals(Nardini et al. 2016) and a pilot clinical study in humans (ClinicalTrials.gov ID: NCT01619176) we explored the systemic effects of mechanical stimulations delivered in the subcutaneous tissue, thanks to the collection of heterogeneous omic data (mRNA-, 16S-rRNA-, miRNA-seq), at different histological (blood, gut-intestinal microbiome, synovial tissue, subcutaneous tissue) and temporal point (before therapy, early genes activation, after therapy).
This lead to the realization that the molecular events triggered locally have a systemic resonance, a very well understandable fact in the frame of non-linear equation and chaos theory, whose translation in medicine is however far from trivial, leading to potential extremely innovative applications in medicine, here discussed with the model disease of rheumatoid arthritis.
Personal profile: Dr.Christine Nardini ( CN ) is currently affiliated to the CNR IAC Mauro Picone in
（九）
Report topic: Fog Computing in Cyber-physical Systems and Security
Reporter: Dr. WenZhan Song，University of Georgia，School of Electrical and Computer Engineering
Time: Thursday, May 25th, 10:30 - 11:30 a.m.
Location: conference room 213，2ndfloor，computer building, Jiulonghu campus, SEU
Abstract: In this talk, we will discuss research challenges and opportunities of Fog Computing in Cyber-physical Systems and Security and present several case studies. We will first present an innovative Real-time In-situ Seismic Imaging (RISI) system design with fog computing. It is a smart sensor network that senses and computes the 3D subsurface imaging in real-time and continuously. Instead of data collection then post processing, the mesh network performs the distributed data processing and tomographic inversion computing under the severe bandwidth and resource constraints, and generates an evolving 3D subsurface image as more data arrives. A RISI system is essentially a “Subsurface Camera” that is a groundbreaking technology and has never been attempted before. We will then discuss smart grid informatics and security research and opportunities. With the integration of advanced computing and communication technologies, Smart Grid holds the promise as the next-generation energy critical infrastructure - efficient, resilient and sustainable. To achieve that end, significant research challenges and opportunities need to be addressed. Our research spans several important topics such as security attacks and countermeasures, topology/fault identification and restoration, demand response and real-time pricing, and microgrid testbed and cooperative controls.
Personal profile: Dr. WenZhan Song is the Georgia Power Mickey A. Brown Professor of Engineering in the
（十）
Report topic: Sound, Music and Wearable Computing for Rehabilitation and Learning: a Multidisciplinary Approach
Reporter: Ye Wang ,
Time: Friday,May 26th, 10:00 - 11:00a.m.
Location: conference room 413, 4thfloor, computer building, Jiulonghu campus, SEU
Abstract: The use of music as an aid for improving body and mind has received enormous attention over the last 20 years from a wide range of disciplines, including neuroscience, physical therapy, exercise science, and psychological medicine. We have attempted to transform insights gained from the scientific study of music, learning, and medicine into real-life applications that can be delivered widely, effectively, and accurately. We have been using music to enhance learning as well as to augment evidence-based medicine. In this talk, I will describe tools to facilitate the delivery of established music-enhanced therapies, harnessing the synergy of sound and music computing (SMC), wearable computing, and cloud computing technologies to promote learning and to facilitate disease prevention, diagnosis, and treatment in both developed countries and resource-poor developing countries. These tools are being developed as part of ongoing research projects that combine wearable sensors, smartphone apps, and cloud-based therapy delivery systems to facilitate music-enhanced learning and music-enhanced physical therapy. Tracing the seven-year journey of exploration from a student project to a dedicated research theme, I will share what we have learnt from the exciting yet challenging journey of multidisciplinary research. Finally, I will introduce our PhD program as well as two relevant conferences in the region to the audience (https://ismir2017.smcnus.org/; http://www.colips.org/conferences/icot2017/).
Personal profile: Ye Wang is an Associate Professor in the Computer Science Department at the National University of Singapore (NUS) and NUS
（十一）
Report topic: Towards the Internet of Medical Things
Time: June 5th, 2017, 14:30-15:30p.m.
Location: conference room 313, 3rdfloor, computer building, Jiulonghu campus, SEU
Abstract: The Internet of medical things promises to change the way we manage our health, shifting from reactive treatment to proactive wellness monitoring and early intervention. Fortunately, technologies in areas such as sensing, communications, data mining, privacy protection, and user interfaces, have recently made great advances. It is thus time to harvest these technologies to realize the vision of managing our own health, preferably at our own home.
In this talk, we introduce several recent studies in this general direction. First, we present HB-Phone, which is a bed-mounted sensor and can monitor a person’s heartbeats during sleep, by detecting the vibrations caused by heartbeats that are propagated through mattress. Second, we present Motion-Scale, which are mounted at bed legs and can detect body and limb motions on bed. These two sensors can continuously monitor a person’s vital signs and motions even when they are asleep. Finally, we present head-banger, a user authentication system for head-mounted smart devices, which can help protect user data privacy.
Personal profile: Yanyong Zhang is currently a Professor in the Electrical and Computer Engineering Department at
（十二）
Report topic: Data Science: Recent Developments and Future Trends
Reporter: Dr. Li Chen，University of the
Time: Wednesday, June 7th, 10:00a.m.
Location: conference room, 4thfloor, computer building, Jiulonghu campus,
Abstract: Data contains science. How data is handled today is much different than the classical mathematical approach of using models to fit the data. Nowadays, people are supposed to find rules and properties within the data set and sometimes among different types of data sets.
Data science is about the study of: (1) The science of data, (2) Knowledge extraction from massive data sets (BigData) mainly using machine learning, (3) Data and data set relations, (4) BigData processing including tools such as Hadoop and Spark on cloud computing, and (5) Visualization of massive data and human–computer interaction.
In this talk, we will explain data science and its relationship to BigData, cloud computing, and data mining. We also discuss current research problems in data science and provide possible relations to the data science industry. Emphasizing the bridge between computer science and math, we will explain why data science would serve as a tremendous engine to the development of the new computing and math theories.
In this talk, we will first quick introduce some basic concepts, and then focus on data mining and machine learning methods such as kNN, k-Means, SVM, PCA, neural networks, and other popular methods. We will selectively discuss the principles of these methods in certain depth. We also introduce timely problems for study including: smart search, the dimension reduction problem, video tracking, and topological data processing.
For future research problems, we would like to discuss computing and algorithm design based on various MapReduce-based models. For applications, we provide a simple case study in image segmentation using MapReduce with detailed algorithm analysis. We will give some hands-on examples in Spark using ML library and possibly provide a short introduction to TensorFlow.
Personal profile: Dr. Li Chen is currently an Associate Professor of computer science at the University of the
Chen is an ACM Distinguished Speaker. Chen has given professional talks on various topics in many universities and colleges including the
Chen's research interests are broad in computer science and applied mathematics and include applied algorithm design, digital and discrete geometry, image processing, and applications to data science. Chen has published more than 65 researcher papers in journals and conference proceedings including Discrete Mathematics; Theoretical Computer Science; IEEE Systems, Man, and Cybernetics; Information Science; the Chinese Science Bulletin; and the Chinese Journal of Computers.Chen has published a total of five books including the recently published “Digital and discrete geometry” (Springer, 2014), “Digital functions and data reconstruction (Springer, 2012), and “Mathematical problems in data science (with Su and Jiang, Springer, 2016).
Chen has received several awards including the SEAS Teaching Award(UDC, 2017), SEAS Outstanding Research Award (UDC, 2015), and the Award Research Fund of Chinese Academy of Science for Young Scientists (1987). In 2014, Chen chaired the Satellite Conference on Data Science of International Congress of Mathematicians (ICM14). He also holds a
（十三）
Report topic: MagNet: a Two-Pronged Defense against Adversarial Examples
reporter: Hao Chen, professor,
Time: June 13th, 14:00 p.m.
Location: conference room 313, 3rdfloor, computer building, Jiulonghu campus, SEU
Abstract: Deep learning has shown promising results on hard perceptual problems in recent years. However, deep learning systems are found to be vulnerable to small adversarial perturbations that are nearly imperceptible to human. Such specially crafted perturbations cause deep learning systems to output incorrect decisions, with potentially disastrous consequences. These vulnerabilities hinder the deployment of deep learning systems where safety or security is important. Attempts to secure deep learning systems either target specific attacks or have been shown to be ineffective. We propose Magnet, a framework for defending neural network classifiers against adversarial examples. MagNet does not modify the protected classifier or know the process for generating adversarial examples. MagNet includes one or more separate detector networks and a reformer network. Different from previous work, MagNet learns to differentiate between normal and adversarial examples by approximating the manifold of normal examples. Since it does not rely on any process for generating adversarial examples, it has substantial generalization power. We discuss the intrinsic difficulty in defending against whitebox attack and propose a mechanism to defend against graybox attack. We show empirically that MagNet is effective against most advanced state-of-the-art attacks in blackbox and graybox scenarios while keeping false positive rate on normal examples very low. This is a joint work with Dongyu Meng.
Personal profile: Hao Chen is a professor at the Department of Computer Science at the
（十四）
Report topic1: Bilingual Dictionary Induction for Low-Resourced Languages
Reporter:Yohei Murakami（Kyoto university）
Time: Friday, June 23th, 9:00-9:30a.m.
Location: conference room, 4thfloor, computer building, Jiulonghu campus
Personal profile: Yohei Murakami is an associate professor of Unit of Design, Center for the Promotion of Interdisciplinary Education and Research,
Report topic2: Research of Services Computing with the Language Grid
Reporter: Donghui Lin（Kyoto university）
Time: Friday, June 23th, 9:30-10:00 a.m.
Location: conference room, 4thfloor, computer building, Jiulonghu campus,
Personal profile: Donghui Lin holds a Ph.D. in Informatics from Department of Social Informatics of Kyoto University, Japan, and a M.E. degree from Department of Computer Science and Engineering of Shanghai Jiao Tong University, China. He was a researcher of National Institute of Information and Communications Technology (NICT),
Report topic3: Interdisciplinary Education for Design Innovation
Reporter: Toru Ishida（Kyoto university）
Time: Friday, June 23th, 10:00-10:30a.m.
Location: conference room, 4thfloor, computer building, Jiulonghu campus,
Personal profile: Toru Ishida has been a professor of
（十五）
Report topic: Sketching Big Network Data
Reporter: Dr. Shigang Chen, IEEE Fellow,
Time: August 8th, 2017, 10:00 a.m.
Location: conference room 213, computer building, Jiulonghu campus, SEU
Abstract: The Internet has moved into the era of big network data. It presents both opportunities and technical challenges for traffic measurement functions, which have important applications in intrusion detection, resource management, billing and capacity planning, as well as big data analytics. Due to the practical need of processing network data in high volume and at high speed, past research has strived to reduce the memory and processing overhead when measuring a large number of flows. One important thread of research in this area is based on sketches. Each sketch requires multiple bits and many sketches are needed for each flow, which results in significant space overhead. In this talk, we present a new branch of virtual sketches research that summarizes big network data into extraordinarily small size. The new methods compress big data into a space of less than 1 bit per flow. Yet they allow extraction of per-flow statistics from such a small summary with good accuracy. We also show how this virtual-sketch research can be extended along space/time/function/application dimensions.
Personal profile: Dr. Shigang Chen (sgchen@cise.ufl.edu) is a professor with Department of Computer and Information Science and Engineering at
（十六）
Report topic: Detecting Perspectives in Political Debates
Reporter: Dr. Yulan He,
Time: Monday, August 7th, 2：00-3：00p.m.
Location: conference room, 2ndfloor, computer building，
Abstract: In this talk, I will present our recent work in exploring how to detect people’s perspectives that occupy a certain proposition. We propose a Bayesian modeling approach where topics (or propositions) and their associated perspectives (or viewpoints) are modeled as latent variables. Words associated with topics or perspectives follow different generative routes. Based on the extracted perspectives, we can extract the top associated sentences from text to generate a succinct summary which allows a quick glimpse of the main viewpoints in a document. The model is evaluated on debates from the House of Commons of the UK Parliament, revealing perspectives from the debates without the use of labelled data and obtaining better results than previous related solutions under a variety of evaluations.
Personal profile: Yulan He is a Reader and Director of the Systems Analytics Research Institute at
（十七）
Report topic: Network Inference in Online Social Networks
Time: Wednesday, August 30th, 10:00-11:00a.m.
Location: room 213, computer building, Jiulonghu campus, SEU
Abstract: Online social networks represent a fundamental medium for the spreading and diffusion of various information where the actions of certain users increase the susceptibility of other users to the same; this results in the successive spread of information from a small set of initial users to a much larger set. Examples include the spread of malicious rumors and Internet hoax. It is important to root out the source and have timely quarantine in order to enhance the network cyber security. This talk will focus on the mathematical theories and algorithms of network inference in online social networks to rooting out malicious rumor sources by leveraging ideas in combinatorics, probability theory and graph theory. We conclude the talk with insights on putting the theory into practice in online social network software development.
Personal profile: Dr. Chee Wei Tan is an Associate Professor at the City University of Hong Kong. He received his M.A. and Ph.D. degree from
（十八）
Report topic: The Rise of Augmented Intelligence in Edge Networks
Time: Tuesday, August 29th,2017, 9:45-10:45a.m.
Location: Room 313, computer building, Jiulonghu campus, SEU
Abstract: Edge networks have been historically serving as the ordinary data pipe as part of the Internet, but recently are expected to play increasingly critical roles for benefiting mobile/IoT applications in terms of lower the response time and energy consumption due to its proximity to the end devices. In this talk, we present two systems which coin this vision and demonstrate the potentials and benefits of the augmented intelligence when deployed at the network edge. The first system is called PassiveVLC, which is based on the idea of modulating the light retroreflection with a commercial LCD shutter to realize a passive optical transmitter and thus visible light backscatter communication. PassiveVLC system enables a battery-free tag device to perform passive communication with the illuminating LEDs over the same light carrier, is flexible with tag orientation, robust to ambient lighting conditions, and can achieve up to 1 kbps uplink speed. The second system, SoftStage, is a client-edge cooperative middleware that effectively leverages and manages in-network caching and services to perform reactive content staging to improve vehicular content delivery 1.5~10x without any assumption about the client mobility pattern.
Personal profile: Dr. Chenren Xu received his Ph.D. from
2016年
计算机网络和信息集成教育部重点实验室学术报告（谢智刚教授，香港理工大学）
发布日期：2016-4-12 发布者：刘肖凡浏览次数：406
报告题目：How does Facebook grow? Do user populations of Twitter, LinkedIn, and other products and services grow in the same way? — A Universal Growth Equation from a Network Perspective
报告人：谢智刚教授，香港理工大学
时间：4月14日周四下午4点
地点：九龙湖校区图书馆五楼数学系第一报告厅
报告摘要：
The growth of the user population of a newly launched product or service is often considered as being controlled by multiple factors like deployment of appropriate business strategy, quality of the product, market readiness, and luck! Recent research in network science has provided convenient access to the construction of models that can describe collective human behaviour. Here, we develop a model, based on construction of a networked community and two fundamental behaviour of decision making, that can universally describe the growth of the user population of any newly launched product or service. This model leads to a universal growth equation that describes dynamically the size of the user population in terms of the prospective market size and the extents of peer influence and personal choice. We analyse 22 sets of real-world historical growth data of a variety of products and services, and show that they all follow the universal growth equation. The numerical procedure for finding the model parameters allows the market size, and the relative effectiveness of customer service and promotional efforts to be estimated from the available historical growth data. This model can be extended to a variety of practical growth applications. At the end of the talk we will present how the growth of a professor's publication over time can be modelled.
个人简介：
Michael Tse graduated with BEng(Hons) and PhD degrees from
计算机网络和信息集成教育部重点实验室学术报告（裴玉博士，香港理工大学）
发布日期：2016-5-27 发布者：刘肖凡浏览次数：811
应李必信教授的邀请，香港理工大学裴玉博士（助理教授）将在我院做学术报告。
时间：2016年5月31日上午10：30
地点：东南大学九龙湖校区计算机楼四楼会议室（413）
报告题目：Automatic Fixing of Programs with Contracts
摘要：Debugging---the activity of finding and correcting errors in programs---is so everyday in every programmer's job that any improvement at automating even parts of it has the potential for a significant impact on productivity and software quality. While automation remains formidably difficult in general, the last few years have seen the first successful attempts at automatically generating fixes to errors in some situations.
In this talk, I will present techniques and a supporting tool, collectively referred to as AutoFix, that programmers can use to automatically fix errors in object-oriented programs with contracts (a.k.a. assertions). AutoFix takes a group of passing and failing test cases as input, with the failing ones revealing the fault to fix; it then analyzes the execution of the input tests, generates candidate fixes to the fault, validates the candidate fixes against a regression test suite, and ranks the valid fixes by preference before reporting them to the user. In the experiments conducted to evaluate AutoFix, it generated fixes that are genuine corrections of quality comparable to those competent programmers would write to 25% of the subject faults. AutoFix is integrated into the EiffelStudio IDE and functions like a recommendation system that is capable of automatically finding bugs and suggesting fixes in the form of source-code patches.
个人简介：Dr.
同时，裴玉博士还代表香港理工大学计算系做博士后、博士生、硕士生招生宣传，欢迎感兴趣的博士生、硕士生、本科生参会交流。
计算机网络和信息集成教育部重点实验室学术报告（Prof. Xiaoming Fu，德国哥廷根大学）
发布日期：2016-6-16 发布者：刘肖凡浏览次数：443
时间：6月17日周五上午10:00
地点：计算机楼313
题目：Architecture, applications and experimentation for green information-centric networking
摘要：Information Centric Networking (ICN) is a new paradigm where the network provides users with named content, instead of communication channels between hosts. There are still a couple of open issues on ICN including naming, routing, resource control, security, privacy and a migration path from the current Internet. Also missing for efficient information dissemination is seamless support of content-based publish/subscribe. Further, and importantly, current proposals do not sufficiently address energy efficiency. This talk presents the work conducted within the EU-Japan FP7 GreenICN project which aimed to bridge this gap, addressing how the ICN network and devices can operate in a highly scalable and energy-efficient way, with disaster notification and video delivery as key applications. I will also briefly introduce our upcoming efforts on EU-Japan H2020 ICN2020 project, where we study on how ICN could be used for innovative applications such as multimedia, social networking and Internet of Things.
个人简介：Xiaoming Fu received his Ph.D. in Computer Science from
计算机网络和信息集成教育部重点实验室学术报告（Ye Wang博士，新加坡国立大学）
发布日期：2016-6-20 发布者：刘肖凡浏览次数：306
时间：2016年6月24日上午10:00
地点：九龙湖校区计算机楼413
题目：Neuroscience-informed sound, music, and wearable computing for rehabilitation and learning
报告人：Ye Wang, National University of Singapore
摘要：The use of music as an aid in improving body and mind has received enormous attention over the last 20 years from a wide range of disciplines, including neuroscience, physical therapy, exercise science, and psychological medicine. We have attempted to transform insights gained from the scientific study of music, learning, and medicine into real-life applications that can be delivered widely, effectively, and accurately. We have been using music to enhance learning as well as to augment evidence-based medicine. In this talk, I will describe tools to facilitate the delivery of established music-enhanced therapies, harnessing the synergy of sound and music computing (SMC), mobile computing, and cloud computing technologies to promote learning and to facilitate disease prevention, diagnosis, and treatment in both developed countries and resource-poor developing countries. These tools are being developed as part of ongoing research projects that combine wearable sensors, smartphone apps, and cloud-based therapy delivery systems to facilitate music-enhanced learning and music-enhanced physical therapy. I will also discuss the joys and pains working in such a multidisciplinary environment.
报告人简介：Ye Wang is an Associate Professor in the Computer Science Department at the National University of Singapore (NUS) and NUS Graduate School for Integrative Sciences and Engineering (NGS). He established and directed the sound and music computing (SMC) Lab (www.smcnus.org). Before joining NUS he was a member of the technical staff at
计算机网络和信息集成教育部重点实验室学术报告（George Baryannis博士，Huddersfield大学）
发布日期：2016-6-21 发布者：刘肖凡浏览次数：328
时间：2016年6月22日上午10:00
地点：东南大学九龙湖校区计算机楼2楼会议室
题目： Rule-based Real-Time Activity Recognition in a Smart Home Environment
报告人：Dr George Baryannis, Postdoctoral Researcher, University of Huddersfield
摘要：Emerging complex smart environments are characterized by the presence of a number of interconnected sensors and devices, forming the so-called Internet of Things. In such environments various activities by human, digital or robotic actors take place. Research on Activity Recognition (AR) has typically followed two complementary directions: data-driven approaches, exploiting machine learning techniques, and knowledge-driven approaches, leveraging logical modelling and reasoning. This talk focuses on the latter category, presenting a rule-based approach for both offline and real-time recognition of so-called Activities of Daily Living (ADL), relying on events produced by a non-intrusive multi-modal sensor infrastructure deployed in a residential environment, as part of the SPHERE project. Novel aspects of the approach include: the ability to recognise arbitrary scenarios of complex activities using bottom-up multi-level reasoning, starting from sensor events at the lowest level; an effective heuristics-based method for distinguishing between actual and ghost images in video data; and a highly accurate indoor localisation approach that fuses different sources of location information. The proposed approach is implemented as a rule-based system using the Jess rule engine and is evaluated using data collected in a smart home environment of the SPHERE project. Experimental results show high levels of accuracy and performance, proving the effectiveness of the approach in real world setups.
报告人简介：Dr. George Baryannis received his Dipl.Eng. in Electronic and Computer Engineering from the Technical
计算机网络和信息集成教育部重点实验室学术报告（Prof. Haibin Zhu, Nipissing University, Canada）
发布日期：2016-6-27 发布者：刘肖凡浏览次数：448
时间：6月29日周三上午10:00
地点：计算机楼313会议室
题目：Role-Based Collaboration and the E-CARGO Model: A Decade Review: 2006-2016
摘要：Role-Based Collaboration (RBC) has emerged into a discovery methodology from a computational methodology with continuous research effort in the past decade. RBC uses roles as the primary underlying mechanism to facilitate collaboration activities. It consists of a set of concepts, principles, models, and algorithms. RBC imposes challenges and benefits not discovered in traditional methodologies and systems. Related research has brought and will bring in exciting improvements to the development, evaluation, management, and execution of computer-based systems including service, cloud, production, and administration systems.
In this talk, we examine the requirement of research on collaboration systems and technologies, briefly discuss RBC and its model Environments - Classes, Agents, Roles, Groups, and Objects (E-CARGO); review the related research achievements on RBC in the past decade; discuss those problems that have not yet been solved satisfactorily; present the fundamental methods to discover related problems with RBC and E-CARGO; and analyze the connections between other fields and RBC.
个人简介：Dr. Haibin Zhu is a Full Professor and the coordinator of the Computer Science Program, Founding Director of Collaborative Systems Laboratory,
He is the receipt of the chancellor’s award for excellence in research (2011) and two research achievement awards from Nipissing University (2006-2007, 2012-2013), the IBM Eclipse Innovation Grant Awards(2004, 2005), the Best Paper Award from the 11th ISPE Int’l Conf. on Concurrent Engineering (ISPE/CE2004), the Educator’s Fellowship of OOPSLA’03, a 2nd class National Award for Education Achievement(1997), and three 1st Class Ministerial Research Achievement Awards from China (1997, 1994, and 1991).
His research interests include Collaboration Theory, Technologies, Systems, and Applications (Role-Based Collaboration and Adaptive Collaboration), Human-Machine Systems, CSCW (Computer-Supported Cooperative Work), Multi-Agent Systems, Software Engineering, and Distributed Intelligent Systems.
计算机网络和信息集成教育部重点实验室学术报告（Prof. Yao Liu, U South Florida）
发布日期：2016-6-29 发布者：刘肖凡浏览次数：529
时间: 7月1日周五上午10:00
地点: 计算机楼313会议室
报告题目: Wireless Physical Layer Security
报告人: Prof.
报告摘要: In wireless networks, location distinction aims to detect location changes or facilitate authentication of wireless users. To achieve location distinction, recent research has been focused on investigating the spatial uncorrelation property of wireless channels. Specifically, the differences of wireless channel characteristics are used to distinguish locations or identify location changes. However, my students and I discover a new attack against all existing location distinction approaches that are built on the spatial uncorrelation property of wireless channels. In such an attack, the adversary can easily hide her location changes or impersonate movements by injecting fake wireless channel characteristics into a target receiver. To defend against this attack, we propose a detection technique that utilizes an auxiliary receiver or antenna to identify these fake channel characteristics. In this talk, I will introduce the unrevealed attacks and discuss the defense methods.
个人简介: Dr. Yao Liu is an Assistant Professor in the Department of Computer Science and Engineering,
计算机网络和信息集成教育部重点实验室学术报告（林志强博士，UT Dallas）
发布日期：2016-7-20 发布者：刘肖凡浏览次数：457
报告题目：No CAPTCHA? No Tracking? Automatic Brute Forcing of
报告人：林志强博士，UT Dallas
报告时间：7月21日下午14:30
报告地点：九龙湖校区计算机楼三楼会议室313
报告摘要： Most mobile apps today require access to remote services, and many of them also require users to be authenticated in order to use their services. While most apps do use cryptographic mechanisms such as encryption (e.g., HTTPS), hashing (e.g., MD5, SHA1), and signing (e.g., HMAC) to ensure the confidentiality and integrity of the network messages including in password authentication, they do not use other mechanisms such as CAPTCHA to stop adversaries keeping guessing password (part of the reason because CAPTCHA hurts the mobile user's experience), nor counting how many failed password attempts for a given user within a short period of time.
Therefore, many mobile services are vulnerable to password brute forcing attack. A straightforward approach to brute force a password might just use a robot (e.g., a GUI fuzzer) to keep mutating the password field in the GUI interface of an app, and then observe whether a successful/failure login interface pops up. However, such an approach is neither scalable nor generic (e.g., different apps can have different successful/failure login interface). Therefore, in this talk, Dr. Lin will talk about a generic and scalable approach to brute-force mobile user's mobile service password (by using automatic protocol reverse engineering and program analysis techniques such as slicing and API replay).
More specifically, he will talk about AutoForge, a system that can automatically forge valid request messages from the client side to test whether the server side of an app has ensured the password security of user accounts with sufficient checks. To enable the security testing, a fundamental challenge lies in how to forge a valid cryptographically consistent message (e.g., with a mutated password but valid MD5 or HMAC) such that it can still be consumed by the server. This challenge has been addressed with a set of automatic protocol reverse engineering and program analysis techniques. AutoForge has been tested with 76 mobile services (each of which has over 1,000,000 installs). Surprisingly, the experimental results show that 65 (86%) of the mobile app servers including CNN, Expedia, iHeartRadio, and Walmart are vulnerable to password brute-forcing attacks.
个人简介：Dr. Zhiqiang Lin is an Assistant Professor of Computer Science at The University of Texas at
计算机网络和信息集成教育部重点实验室学术报告（张令明博士，University of Texas at Dallas）
发布日期：2016-8-5 发布者：刘肖凡浏览次数：407
报告题目：Predictive Mutation Testing
报告时间：2016年8月9日上午10:00-11:00
报告地点：东南大学计算机楼四楼会议室
报告摘要：Mutation testing is a powerful methodology for evaluating test suite quality. In mutation testing, a large number of mutants are generated and executed against the test suite to check the ratio of killed mutants. Therefore, mutation testing is widely believed to be a computationally expensive technique. To alleviate the efficiency concern of mutation testing, this talk introduces predictive mutation testing (PMT), the first approach to predicting mutation testing results without mutant execution. In particular, the proposed approach constructs a classification model based on a series of features related to mutants and tests, and uses the classification model to predict whether a mutant is killed or survived without executing it. PMT has been evaluated on 163 real-world projects under two application scenarios (i.e., cross-version and cross-project). The experimental results demonstrate that PMT improves the efficiency of mutation testing by up to 151.4X while only incurring a small accuracy loss on mutant execution result prediction, indicating a good tradeoff between efficiency and effectiveness of mutation testing.
个人简介：Dr. Lingming Zhang（张令明） is an assistant professor in the Computer Science Department at the University of Texas at Dallas. He obtained his Ph.D. degree from the Department of Electrical and Computer Engineering in the
2015年
计算机网络和信息集成教育部重点实验室学术报告（加拿大维多利亚大学潘建平博士）
发布日期：2015-4-17 发布者：刘肖凡浏览次数：440
报告题目：A Personal Experience of Academia and Industry Research
时间：4月20日周一下午14：00
地点：九龙湖计算机楼3楼会议室
报告摘要：With diverse education background in different disciplines and countries, and work experience in both academia and industry research labs in different countries, I hope I can share some of my own experience, as well as what I observed and learned from others, with young faculty members and grad students, for a smoother and more successful navigation of visit, study, and work at the University of Victoria and hopefully elsewhere too, on questions that I am still looking for answers as well (e.g., how to start, continue and further research pipelines, how to write, publish and present research outcomes, how to interact with students and collaborators,how to attract government and industry funding, etc). I also like to hear from the audience on their research activities and experience and learn from them too, so if anyone has any questions and wish to be addressed in an anonymous way during the talk, please drop me an email in advance.
报告人简介：Dr Jianping Pan iscurrently a professor of computer science at the University of Victoria, Victoria, British Columbia, Canada. He received his Bachelor's and PhD degrees in computer science from Southeast University, Nanjing, Jiangsu, China, and he did his postdoctoral research at the University of Waterloo, Waterloo, Ontario, Canada. He also worked at Fujitsu Labs and NTT Labs. His area of specialization is computer networks and distributed systems, and his current research interests include protocols for advanced networking, performance analysis of networked systems, and applied network security. He received the IEICE Best Paper Award in 2009, the Telecommunications Advancement Foundation's Telesys Award in 2010, the WCSP 2011 Best Paper Award, the IEEE Globecom 2011 Best Paper Award, the JSPS Invitation Fellowship in 2012, and the IEEE ICC 2013 Best Paper Award, and has been serving on the technical program committees of major computer communications and networking conferences including IEEE INFOCOM, ICC, Globecom, WCNC and CCNC. He is the Ad Hoc and Senor Networking Symposium Co-Chair of IEEE Globecom 2012 and an Associate Editor of IEEE Transactions on Vehicular Technology. He is a senior member of the ACM and a senior member of the IEEE.
计算机网络和信息集成教育部重点实验室学术报告（付新文教授，UMASSLowell）
发布日期：2015-6-23 发布者：刘肖凡浏览次数：443
应罗军舟教授的邀请，UMASS Lowell的付新文教授将访问我院并作学术报告。
题目: How to Classify Crimes and Investigations and A New Crime
演讲人：付新文副教授（University of Massachusetts Lowell）
时间：6月25日（周四）上午10:00
地点：东南大学九龙湖校区计算机楼313房间
摘要:
The Internet has become the primary battlefield of the cyber war and the prevalent environment of cybercrimes. We want to understand cybercrime in order to predict them, prevent them, detect them and respond to them. It is also critical to understand state-of-art cyber crime investigation to educate a quality cyber operation workforce. In this talk, we introduce our models to this end. We model cybercrimes as a combination of three basic crime strategies and cybercrime investigations as computerized techniques and traditional forensic technique. We also build a web based cybercrime and investigation database for easy search of cases of interest. To demonstrate the threats from cybercrimes, we also introduce a new type of cybercrime, the n-gram language model based attacks that are able to recognize text inputs such as emails on touch-enabled devices, and raise mobile security and privacy awareness.
讲者简介:
Dr. Xinwen Fu is an associate professor in the Department of Computer Science,
计算机网络和信息集成教育部重点实验室学术报告（李向阳教授，伊利诺理工）
发布日期：2015-7-6 发布者：刘肖凡浏览次数：733
应罗军舟教授邀请，美国伊利诺理工大学的李向阳教授（IEEE Fellow）将访问学院并做报告。报告信息具体如下：
题目：High Precision Real-Time Tracking with RFID Tags Using COTS Devices
报告人：李向阳，美国伊利诺理工大学（Illinois Institute of Technology）
时间：7月7日周二下午14:30
地点：东南大学九龙湖校区计算机楼 313
摘要：
In many applications, we have to identify an object and then locate the object to within centimeter- or millimeter-level accuracy. Legacy systems that can provide such accuracy are either expensive or suffer from performance degradation resulting from various impacts, e.g., occlusion for computer vision based approaches. In this talk, we present several RFID-based systems for locating objects. One category is device-based where RFID tag is attached to the object-to-be-localized, and the other category is device-free method where no RFID tag is attached the object at all. We will focus on the device-based method while briefly introduce our device-free methods.
The first part of the talk is about Tagoram, object localization and tracking using COTS RFID tags and readers. Tracking mobile RFID tags in real time has been a daunting task, especially challenging for achieving millimeter-level accuracy. Our system achieves these goals by leveraging the phase value of the backscattered signal, provided by the COTS RFID readers, to estimate the location of the object. In Tagoram, we exploit the tag’s mobility to build a virtual antenna array by using readings from a few physical antennas over a time window. Our system is robust to device diversity and multipath impact. We have implemented the Tagoram system using COTS RFID tags and readers. The system has been tested extensively in the lab environment and used for more than a year in real airline applications. For lab environment, we can track the mobile tags in real time with accuracy to a median of 5mm along the moving direction. In our year-long large-scale trial studies in real luggage sortation systems of two airports, our results show that Tagoram can achieve accuracy to a median of 63.5mm in these real deployments. We also will show other related applications using our techniques.
The second part is brief review of our device-free results.
The results are collaborated with research groups at
个人简介：
Dr. Xiang-Yang Li is a professor at Computer Science Department of IIT, an IEEE fellow (2015), an ACM Distinguished Scientist (2014), and an EMC Visiting Chair Professor at
His research interests include wireless networks, mobile computing, privacy and security, cyber physical systems, social networking, and algorithms. He has published more than 120 papers in top-tier journals, and 200 papers in well-known international conferences. His Google-scholar citation is more than 10,000, and H-index is >50. Dr. Li and his students won four best paper awards (IEEE IPCCC 2014, ACM MobiCom 2014, COCOON 2001, IEEE HICSS 2001), one best demo award(ACM MobiCom 2012) and was selected as best paper candidates twice (ACM MobiCom 2008, ACM MobiCom 2005).
Dr. Li has served or is serving as an editor of several journals, including IEEE Transaction on Parallel and Distributed Systems, IEEE Transaction on Mobile Computing. He served at various capacities (conference chair, TPC chair, or local arrangement chair) in a number of conferences, including TPC chair of ACM MobiHoc 2014. His research has been supported by NSF, NSFC, and RGC HongKong. He has graduated eleven PhD students since 2004. For more information about Prof. XiangYang Li, please check his webpage www.cs.iit.edu/~xli and www.cs.iit.edu/~winet.
计算机网络和信息集成教育部重点实验室学术报告（沈俊副教授，伍伦贡大学）
发布日期：2015-7-7 发布者：刘肖凡浏览次数：837
应罗军舟教授邀请，澳大利亚伍伦贡大学沈俊副教授将来访我院并做报告。具体信息如下。
题目：ACO in Data-Intensive Services System
讲者：沈俊副教授，澳大利亚伍伦贡大学
时间：7月10日下午2：30
地点：九龙湖校区三楼会议室
摘要：The rapid proliferation of enormous sources of digital data has led to greater dependence on data-intensive services. Each service may actually request or create a large amount of data sets. To compose these services will be more challenging. Issues such as autonomy, scalability, adaptability, and robustness, become difficult to resolve. In order to automate the process of reaching an agreement among service composers, service providers, and data providers, an ant-inspired negotiation mechanism is considered in this paper. We exploit a group of agents automatically negotiating to establish agreeable service contracts. Two stage negotiation procedures are used in our data-intensive service provision model, which will provide effective and efficient service selection for service composers. We also present a multi-phase, multi-party negotiation protocol, where the ant colony system is applied to select services with the best or near-optimal utility outputs. In order to adapt the ant colony system to handle the dynamic scenarios during negotiations, we also discuss several strategies for modifying the pheromone information in the first place. The experimental results show that our negotiation-based approach can facilitate the data-intensive service provision with better outcome.
个人简介：Dr Jun Shen was awarded PhD in 2001 at Southeast University, China. He held positions at Swinburne University of Technology in
计算机网络和信息集成教育部重点实验室学术报告（唐少杰博士，UT Dallas）
发布日期：2015-7-14 发布者：刘肖凡浏览次数：1107
应肖卿俊博士的邀请，University of Texas at Dallas的唐少杰博士将访问我院并作报告。具体信息如下
时间地点：7月17日星期五上午10点，九龙湖计算机楼三楼会议室
讲者：唐少杰博士，University of Texas at Dallas
题目：Modeling Data Dissemination in Online Social Networks: A Geographical Perspective on Bounding Network Traffic Load
摘要：In this work, we model the data dissemination in online social networks (OSNs) and study the scaling laws of traffic load. We propose a three-layered system model to formulate data dissemination sessions for social applications in OSNs. The layered model consists of the physical network layer, social relationship layer, and application session layer. By analyzing mutual relevance among these three layers, we investigate the geographical distribution feature of dissemination sessions in OSNs. Based on this, we derive the traffic load of OSNs under a realistic assumption that every source sustains a data generating rate of constant order. To the best of our knowledge, this is the first work to address the issue of traffic load scaling for OSNs by modeling the social data dissemination from a layered perspective.
个人简介：Dr. Shaojie Tang is currently an assistant professor of Naveen Jindal School of Management at
计算机网络和信息集成教育部重点实验室学术报告（Sotirios Batsakis副教授，Huddersfield大学）
发布日期：2015-7-15 发布者：刘肖凡浏览次数：1028
应漆桂林教授的邀请，英国Huddersfield大学的Sotirios Batsakis副教授正在我院访问，将于7月15日下午面向全院师生做公开报告。具体信息如下：
报告时间和地点：7月15日下午2点30分，九龙湖校区计算机楼4楼会议室。
题目：
Large-Scale Reasoning with Semantic Data
摘要：
Motivated by the recent unparalleled explosion of available data coming from the Web, sensor readings, databases, ontologies reasoning over Semantic Web Data, using MapReduce is an important topic. Such datasets could benefit from the introduction of rule sets encoding commonly accepted rules or facts, application- or domain-specific rules, commonsense knowledge, including spatiotemporal reasoning rules, etc. This raises the question of whether, how, and to what extent knowledge representation methods are capable of handling huge amounts of data for these applications. Results indicate that our methods have good scalability properties and are able to handle a benchmark data-set of 1 billion triples.
个人简介：
Dr. Sotirios Batsakis is Senior Lecturer at the
计算机网络和信息集成教育部重点实验室学术报告（Toru Ishida教授等，日本京都大学）
发布日期：2015-7-23 发布者：刘肖凡浏览次数：1191
应高志强教授的邀请，日本京都大学Toru Ishida教授一行四人将访问东南大学，并给出以下报告，欢迎各位老师参加。
时间地点：7月24日星期五下午2：30，四牌楼校区中心楼105会议室
讲者：Toru Ishida教授、Lin Donghui助教授、Otani研究员，Kyoto University
题目1：Create a New Circle of Science, Engineering and Design: Introduction to Kyoto University Design School
摘要1：The global society is seeking solutions for complex problems regarding global warming, disasters, energy, food, and population. In 2013, we started five year PhD course, Collaborative Graduate Program in Design (so called
conducted: field-based learning (FBL) and problem-based learning (PBL), leadership training courses named overseas internships (individually) and field internships (in a group), as well as various academia-industry education activities in order to develop talent with a broad view and creativity.
简历1：Toru Ishida has been a professor of Kyoto University since 1993. His academic background includes visiting scientist/professor positions at Columbia University, Technische Universitaet Muenchen, Université Pierre et Marie Curie, University of Maryland, Shanghai Jiao Tong University, Tsinghua University, Xinjiang University and Hong Kong Baptist University. He is a fellow of IEEE, a vice president of IEICE, and a member of the Science Council of Japan. He is a co-founder of the Department of Social Informatics,
题目2：Open Language Grid: Towards a Worldwide Language Service Infrastructure
摘要2：To develop a multilingual environment that can handle various situations in various communities, existing language resources should be easily shared and customized. We proposed and developed the Language Grid as service-oriented collective intelligence; it allows users to freely create language services from existing language resources and combine those language services to develop new services to meet their own requirements. This talk explains current status, future direction of the Language Grid, and its typical applications. First, we explain the design concept, service architecture and research achievements of the Language Grid. Then, we introduce the efforts towards a worldwide language service infrastructure for language resource sharing through global collaboration. Finally, we describe how the Language Grid is used as a platform for real field activities by using several examples.
简历2：Donghui Lin has been an assistant professor of Kyoto University since 2012. He received his Ph.D. degree in informatics from
计算机网络和信息集成教育部重点实验室学术报告（李颉教授，日本筑波大学）
发布日期：2015-7-25 发布者：刘肖凡浏览次数：1553
报告题目：Distributed Networking and Data Collection for Wireless Sensor Networks
报告人：日本筑波大学李颉教授
时间：2015-7-28 10:00-11:00
地点：计算机楼313会议室
Abstract:
In this talk, we will provide an overview on the research and applications of wireless sensor networks. Then we will focus on the continuous data collection problem in wireless sensor networks with a mobile base station by using distributed coding. The coding and decoding schemes for the data collection in wireless sensor networks will be introduced. The efficiency of the proposed schemes will be shown through comprehensive theoretical analysis and the performance evaluation.
Short Bio:
Jie Li is a Professor in Faculty of Engineering, Information and Systems,
计算机网络和信息集成教育部重点实验室学术报告（Yuanlin Zhang博士，德克萨斯理工大学）
发布日期：2015-8-17 发布者：刘肖凡浏览次数：1466
应张志政老师的邀请，美国德克萨斯理工大学的Yuanlin Zhang 博士将访问我院并作学术报告，报告信息如下。
题目：Vicious Circle Principle and Logic Programs with Aggregates
时间：2015-8-18 10:00-11:00
地点：计算机楼4楼会议室
报告人：美国德克萨斯理工大学 Yuanlin Zhang
摘要： In this talk, I’ll present a knowledge representation language Alog which extends ASP with aggregates. The goal is to have a language based on simple syntax and clear intuitive and mathematical semantics. We give some properties of Alog and a comparison with other approaches.
个人简介：
Yuanlin Zhang is an Associate Professor of Computer Science at
计算机网络和信息集成教育部重点实验室学术报告（张成奇教授，悉尼科技大学）
发布日期：2015-9-9 发布者：刘肖凡浏览次数：1420
应耿新教授的邀请，悉尼科技大学张成奇教授将访问我院并作学术交流，具体安排如下：
时间：9月10日上午10:30
地点：计算机楼3楼会议室
报告题目：Graph Processing and Mining in the Era of Big Data
摘要：
With the emergence and rapid proliferation of applications that deal with big graphs, such as web graphs (Google, Yahoo), social networks (Facebook, Twitter), e-commerce networks (Amazon, Ebay), and road networks, graph processing and mining has become increasingly prevalent and important in recent years. However, in the era of big data, the explosion and profusion of available graph data in a wide range of application domains rise up new challenges and opportunities in graph processing and mining.
Graph processing and mining is one of the research strengths in the centre for Quantum Computation and Intelligent Systems (QCIS) at the
个人简介：
Chengqi Zhang has been appointed as a Research Professor of Information Technology at The University of Technology, Sydney (UTS) since December 2001. He has been the Director of the UTS Research Centre for Quantum Computation & Intelligent Systems (QCIS) since April 2008. Chengqi Zhang obtained his PhD degree from the
Prof. Zhang’s key areas of research are Distributed Artificial Intelligence, Data Mining and its applications. He has published more than 200 refereed research papers, including a number of papers in the first-class international journals, such as Artificial Intelligence, IEEE and ACM Transactions. He has delivered 14 keynote/invited speeches at international conferences over the last eight years. He has attracted 12 ARC grants of $4.7M. He has supervised 30+ PhD students in completion. He received NSW State Science and Engineering Award in Engineer and ICT category in 2011 and also UTS Chancellor research excellence award in Research Leadership category in 2011.
Prof. Zhang is a Fellow of the Australian Computer Society (ACS) and a Senior Member of the IEEE Computer Society (IEEE). He had been serving ARC as an ARC College of Expert from 2012 to 2014. He has been the Chair of the Australian Computer Science National Committee on Artificial Intelligence from 2005 till now. He was General Co-Chair of PAKDD 2014, WI/IAT 2018, and ICDM 2010. He is the General Co-Chair of KDD 2015 and he is also Local Arrangements Chair of IJCAI 2017.
计算机网络和信息集成教育部重点实验室学术报告（沈俊副教授，澳大利亚伍伦贡大学）
发布日期：2015-11-4 发布者：刘肖凡浏览次数：465
澳大利亚伍伦贡大学沈俊副教授将于11月6日访问我院并作报告，具体信息如下：
报告题目：Supervised Learning Based on Monte Carlo Methods and its Applications in Biology
报告人：澳大利亚伍伦贡大学沈俊副教授
时间：2015-11-6 10:00-11:00
地点：东南大学九龙湖校区计算机楼313会议室
摘要：Neural network (NN) applications had a stagnant development since the 1970s. But its development and application in the related areas such as machine learning, pattern recognition, artificial intelligence and even the robotics, have obtained a wide recognition and stimulated further innovation. NN has been categorized in two types of networks, which are shallow neural network and deep neural network. They all have been extensively developed, deployed and compared. With the latest improved unsupervised learning algorithm and its parallel implementation on GPU in the recent years, the deep neural network seems to be much more rational because its multi layers' neural working mechanism is more analogous to human brain. In this talk, we will start from the traditional methods, and then deploy a supervised learning machine in a shallow neural network model using
个人简介：Dr Jun Shen was awarded PhD in 2001 at Southeast University, China. He held positions at Swinburne University of Technology in
计算机网络和信息集成教育部重点实验室学术报告（吴逵教授，加拿大维多利亚大学）
发布日期：2015-11-9 发布者：刘肖凡浏览次数：345
加拿大维多利亚大学吴逵教授将于本周访问我院并作学术报告，具体信息如下。
报告题目：Copula Analysis and Inference in Computer Networks
报告人：加拿大维多利亚大学（University of Victoria）吴逵教授 (Prof. Kui Wu)
时间：2015-11-10 14:00-15:00
地点：东南大学九龙湖校区计算机楼313会议室
摘要： A copula is a function that links univariate marginals to their multivariate distribution. In practice, it is normally easy to find the univariate marginals, but it is hard to obtain the multivariate distribution. With a copula, one can capture the joint distribution of random variables once their marginal distributions are obtained. Copulas, while well known in the domain of quantitative finance and have been used widely in portfolio and risk management, are still nascent in network and communication research. Compared to other dependence measures, such as the correlation function, copula has its special advantages in network traffic modelling. For instance, the invariant property of copulas indicates that a copula of two random variables remains the same if both random variables are transformed with strictly increasing functions. This property implies that the dependence structure of two traffic flows, in the measure of copula, remains unchanged, even if the packet sizes of the two flows are scaled up differently.
This talk will introduce copula analysis with a hope of triggering more research interest of applying copula analysis in the domain of computer networks, particularly in network applications involving nonlinear dependence modelling.
计算机网络和信息集成教育部重点实验室学术报告（Wei Yu教授，Towson University）
发布日期：2015-12-10 发布者：刘肖凡浏览次数：253
报告题目：Efficient and Resilient Energy-Based Cyber-Physical System
报告人：Prof. Wei Yu,
时间：2015-12-11 10:00-11:00
地点：东南大学九龙湖校区计算机楼313会议室
摘要： The smart grid, as a typical energy-based cyber-physical system, uses modern computing, communication and control technologies to make the power grid more efficient, and resilient. Nonetheless, the smart grid may operate in an environment with numerous uncertainties. In this talk, I will introduce frameworks to enable the design of efficient systems, explore failure and security risks in the system, and the development of mitigation schemes against failures and threats. This research provides a scientific foundation for designing an efficient and resilient energy-based cyber-physical system.
个人简介：Dr. Wei Yu is currently an Associate Professor in the Department of Computer and Information Sciences at
个人简介：Prof. Kui Wu received the B.S. degree in Computer Science in 1990 and the Master's degree in Computer Engineering in 1993, both from
计算机网络和信息集成教育部重点实验室学术报告（Weifa Liang教授，澳大利亚国立大学）
发布日期：2015-12-11 发布者：刘肖凡浏览次数：274
报告题目：Capacitated Cloudlet Placements in Wireless Metropolitan Area Networks
报告人：Prof. Weifa Liang,
报告时间：2015年12月14日 14:30-15:30
地点：东南大学九龙湖校区计算机楼313会议室
摘要：In this paper we study the cloudlet placement problem in a large-scale Wireless Metropolitan Area Network (WMAN) that consists of many wireless Access Points (APs). Although most existing studies in mobile cloud computing mainly focus on energy savings of mobile devices by offloading computing-intensive jobs from them to remote clouds, the access delay between mobile users and the clouds usually is large and sometimes unbearable. Cloudlet as a new technology is capable to bridge this gap, and has been demonstrated to enhance the performance of mobile devices significantly while meeting the crisp response time requirements of mobile users. In this paper we consider placing multiple cloudlets with different computing capacities at some strategic local locations in a WMAN to reduce the average cloudlet access delay of mobile users at different APs. We first formulate this problem as a novel capacitated cloudlet placement problem that places $K$ cloudlets to some locations in the WMAN with the objective to minimize the average cloudlet access delay between the mobile users and the cloudlets serving their requests. We then propose a fast yet efficient heuristic. For a special case of the problem where all cloudlets have the identical computing capacity, we devise a novel approximation algorithm with a guaranteed approximation ratio. In addition, We also consider allocating user requests to cloudlets by devising an efficient online algorithm for such an assignment. We finally evaluate the performance of the proposed algorithms through experimental simulations. The simulation results demonstrate that the proposed algorithms are promising and scalable.
个人简介：Prof. Weifa Liang received the PhD degree from the
计算机网络和信息集成教育部重点实验室学术报告（庄艳艳博士，University of British Columbia）
发布日期：2015-12-18 发布者：刘肖凡浏览次数：315
报告时间：2015年12月23日（周三）下午14：30
地点：九龙湖校区计算机楼311会议室
报告人：庄艳艳博士，University of British Columbia
报告题目：NetCheck: Network Diagnoses from Blackbox Traces
报告摘要：This talk introduces NetCheck, a tool designed to diagnose network problems in large and complex applications. NetCheck relies on blackbox tracing mechanisms, such as strace, to automatically collect sequences of network system call invocations generated by the application hosts. NetCheck performs its diagnosis by (1) totally ordering the distributed set of input traces, and by (2) utilizing a network model to identify points in the totally ordered execution where the traces deviated from expected network semantics.
Our evaluation demonstrates that NetCheck is able to diagnose failures in popular and complex applications without relying on any application- or network-specific information. For instance, NetCheck correctly identified the existence of NAT devices, simultaneous network disconnection/ reconnection, and platform portability issues. In a more targeted evaluation, NetCheck correctly detects over 95% of the network problems we found from bug trackers of projects like Python, Apache, and Ruby. When applied to traces of faults reproduced in a live network, NetCheck identified the primary cause of the fault in 90% of the cases. Additionally, NetCheck is efficient and can process a GB-long trace in about 2 minutes.
报告人简介：Yanyan Zhuang is currently a Postdoctoral Fellow in the Department of Computer Science at University of British Columbia (UBC). She will join the Department of Computer Science and Engineering at New York University (NYU) as a non-tenured research professor in 2016. She has published papers at NSDI, INFOCOM, ACSAC, and IEEE Transactions such as JSAC and TVT. She has been a program committee member of conferences such as Tridentcom, PacRim, and SAS. In 2014, she was awarded an NSERC (Natural Sciences and Engineering Research Council of Canada) postdoctoral fellowship. Her research focuses on developing mobile sensing platforms, and program diagnoses for developers to troubleshoot application failures. In the past three years, she has received a number of grants and awards from the Canadian and US government agencies for over $1.6M USD.
计算机网络和信息集成教育部重点实验室学术报告（Yi MU教授，University of Wollongong）
发布日期：2015-12-21 发布者：刘肖凡浏览次数：257
报告题目：Public Key Encryption with Keyword Search against Insider Attack
报告人：Prof. Yi Mu,
时间：2015年12月23日10:00-11:00
地点：东南大学九龙湖校区计算机楼313会议室
摘要： The ciphertext retrieval is of paramount importance for data confidentiality and utilization. Thanks to bilinear-pairing-based cryptography, searching in an encrypted data has become a reality. The most common application of searchable encryption is cloud storage systems, where an honest-but-curious server manages the storage system and is able to find correct text from an encryption without decrypting it. Although the security against outsiders can be achieved, the most challenging task is to resist the so-called insider attack from the untrusted cloud storage server, who can actively guess the encrypted text with high probability. In this talk, the security models of searchable encryption such as secure channel free and insider attack will be discussed. A novel framework to resist inside attacks will be introduced. In addition, a discussion will be presented to show how to reduce the computational cost of searchable encryption with pre-computation.
个人简介：Professor Yi Mu received his PhD from the Australian National University in 1994. He is currently a full professor and Director of Centre for Computer and Information Security Research at University of Wollongong, Australia. He was the Head of School of Computer Science and Software Engineering at
计算机网络和信息集成教育部重点实验室学术报告（贾文静博士，悉尼理工大学）
发布日期：2015-12-21 发布者：刘肖凡浏览次数：328
题目：Scene Text Detection/Recognition: Recent Advances and Our Solutions
报告人：贾文静 (悉尼理工大学)
时间地点：12月23日（周三）下午15:00，计算机楼201会议室
报告摘要：Text information appearing in a scene carries vital information for interpreting the contents, and identifying objects and surrounding environment in images. Although conventional document analysis techniques have bee quite successful, identifying general text in images remains a very challenging research problem. The recent prestigious conferences on computer vision, pattern recognition, and machine learning have seen an increased interest on this topic from the computer vision research community. In this talk, I will show you the challenges and the recent advances in research on scene text recognition and our solutions and attempts.
报告人简介：Dr. Wenjing Jia is currently a Lecturer at the
计算机网络和信息集成教育部重点实验室学术报告（童飞博士，加拿大维多利亚大学）
发布日期：2015-12-21 发布者：刘肖凡浏览次数：366
题目：One Handshake Can Achieve More for Practical Data Collection in Sensor Networks
报告人：童飞 (加拿大维多利亚大学)
时间地点：12月25日（周五）上午10:00
地点：东南大学九龙湖校区计算机楼301会议室
报告摘要：To alleviate long sleep latency due to duty-cycled radio operations, existing collection protocols for wireless sensor networks adopted pipelined scheduling techniques, which stagger the sleep-wakeup schedules of nodes along forwarding paths, requiring accurate time synchronization as underlying support. They either ignored the synchronization issue or just assumed that a local synchronization scheme over non-duty-cycled radios could meet the requirement, however, which may lead to a significant synchronization issue in practice. In this work, we propose a practical Pipelined Data Collection (PDC) protocol for duty-cycled sensor networks. PDC adopts an inter-layer incorporation of network and MAC layers. It only relies on an RTS/CTS-like handshake with a set of proposed algorithms, not only for data transmission as commonly utilized, but also for pipelined scheduling and schedule synchronization, data-gathering tree establishment, and network topology control and maintenance, all of which are naturally and seamlessly incorporated together and able to support each other. Due to the pipelined-forwarding feature, PDC is very suitable for linear sensor networks (LSNs), which have recently attracted increasing attention resulting from the vast requirements on the monitoring and surveillance of a structure or area with a linear topology. We model PDC for an LSN, where all nodes can generate data as in reality. Based on the model, we analyze the network performance in terms of the system throughput, active time ratio per cycle of each node, and packet delivery latency. Through the extensive OPNET-based simulations, we validate the model and reveal the dependency of the network performance on various system parameters. PDC has also been implemented in the Contiki OS (a pioneering open-source OS for the Internet of Things). The testbed evaluations based on two hardware platforms (Z1 and MicaZ) and the compared results with a de facto standard for data collection based on the fully emulated Z1 in Cooja (a simulator provided by the Contiki OS) have demonstrated its practicality and efficacy.
报告人简介：Fei Tong received his B.S. degree in Computer Science and Technology from South-Central University for Nationalities, Wuhan, China, in 2009, and his M.S. degree in Computer Engineering from Chonbuk National University, South Korea, in 2011. He is currently a PhD candidate supervised by Dr. Jianping Pan at the Department of Computer Science,
计算机网络和信息集成教育部重点实验室学术报告（陈凯博士，香港科技大学）
发布日期：2015-12-22 发布者：刘肖凡浏览次数：571
报告题目：PIAS: Practical Information-Agnostic Flow Scheduling for Commodity Data Centers
报告人：香港科技大学陈凯博士
时间：2015-12-28 10:00-11:00
地点：计算机楼313会议室
Abstract:
Many existing data center network (DCN) flow scheduling schemes minimize flow completion times (FCT) based on prior knowledge of flows and custom switch functions, making them superior in performance but hard to use in practice. By contrast, we seek to minimize FCT with no prior knowledge and existing commodity switch hardware.
In this work, we present PIAS, a DCN flow scheduling mechanism that aims to minimize FCT by mimicking Shortest Job First (SJF) on the premise that flow size is not known a priori. At its heart, PIAS leverages multiple priority queues available in existing commodity switches to implement a Multiple Level Feed- back Queue (MLFQ), in which a PIAS flow is gradually demoted from higher-priority queues to lower-priority queues based on the number of bytes it has sent. As a result, short flows are likely to be finished in the first few high-priority queues and thus be prioritized over long flows in general, which enables PIAS to emulate SJF without knowing flow sizes beforehand. We have implemented a PIAS prototype and evaluated PIAS through both testbed experiments and ns-2 simulations. We show that PIAS is readily deployable with commodity switches and backward compatible with legacy TCP/IP stacks. Our evaluation results show that PIAS significantly outperforms existing information-agnostic schemes. PIAS is available at http://sing.cse.ust.hk/projects/PIAS.
Short Bio:
Dr Kai Chen is an Assistant Professor with Department of Computer Science and Engineering, Hong Kong University of Science and Technology. He received his PhD in Computer Science from
计算机网络和信息集成教育部重点实验室学术报告（何亮博士，密歇根大学）
发布日期：2015-12-24 发布者：刘肖凡浏览次数：599
题目：SoH-Aware Reconfiguration to Enhance Deliverable Capacity of Large Battery Packs
报告人：何亮 (密歇根大学)
时间地点：12月28日（周一）上午10:00
地点：东南大学九龙湖校区计算机楼301会议室
报告摘要：
Unbalanced battery cells are known to significantly degrade the performance and reliability of a large-scale battery system. In this talk, I’ll introduce our investigation on exploiting emerging reconfigurable battery packs to mitigate the cell imbalance via the joint consideration of system reconfigurability and State-of-Health (SoH) of cells. Via empirical measurements and validation, we observe that a significantly larger amount of capacity can be delivered when cells with similar SoH levels are connected in series during discharging, which in turn extends the system operation time. Based on this observation, we propose two SoH-aware reconfiguration algorithms focusing on fully and partially reconfigurable battery packs, and prove their (near) optimality. We evaluate the proposed SoH-aware reconfiguration algorithms using both experiments and simulations. The algorithms are shown to deliver about 10–30% more capacity than SoH-oblivious configuration approaches.
个人信息：
Dr. Liang He is currently a research fellow at
2014年
7月4日学术报告通知（密苏里大学 沈孝钧教授）
发布日期：2014-7-3 发布者：宋美娜浏览次数：1341
报告题目：A Nearly Optimal Packet Scheduling Algorithm for Input Queued Switches with Deadline Guarantees
报告人：沈孝钧教授（密苏里大学）
时间地点：7月4日（本周五）下午2点半，九龙湖校区计算机楼313会议室
在本次报告中，沈老师将首先介绍在交换机的调度上的取得的最新研究成果。然后以此作为切入点，给老师们和同学们传授他多年来做科研的宝贵经验。包括，如何 寻找新的问题，确认研究动机；以什么样的研究方法来解决问题；以及，最重要的，如何将自己的研究成果有条理又逻辑的表达给读者。沈老师研究功力深厚、热情洋溢、喜爱后生，乐于分享，欢迎大家都来参加。
报告摘要：In order to guarantee quality of service, we consider how to schedule a set of packets buffered at input side of a switch such that maximum number of packets can be transmitted to their destined output ports before their deadlines. This problem has been proven NP-complete if three or more classes (distinct deadlines) are present in the set. Traditionally, the only way to deal with this problem is to use EDF (Earliest Deadline First) or similar methods. In 2007, we proposed the first non-EDF method that can produce a much higher throughput by repeatedly applying an optimal algorithm for two classes. Recently, a mush high throughput has been reached by a new algorithm which does not use the deadlines as the priorities. This new algorithm provides approximation ratio 2 and superb average performance as well. It would provide a practical solution to the historically difficult problem. A related paper will appear in IEEE Transactions on Computers.
报告人简介：
Dr. Xiaojun Shen (沈孝钧) received his bachelor degree in computer science in 1968 from
7月15日学术报告通知（沈俊博士 澳大利亚伍伦贡大学）
发布日期：2014-7-11 发布者：刘肖凡浏览次数：1140
报告题目：Multi-Phase Ant Colony System for Multi-Party Data-Intensive Service Provision
报告人：澳大利亚伍伦贡大学 沈俊博士
时间：2014-7-15 14:30-15:30
地点：计算机楼313会议室
报告摘要：The rapid proliferation of enormous sources of digital data has led to greater dependence on data-intensive services. Each service may actually request or create a large amount of data sets. To compose these services will be more challenging. Issues such as autonomy, scalability, adaptability, and robustness, become difficult to resolve. In order to automate the process of reaching an agreement among service composers, service providers, and data providers, an ant-inspired negotiation mechanism is considered in this paper. We exploit a group of agents automatically negotiating to establish agreeable service contracts. Two stage negotiation procedures are used in our data-intensive service provision model, which will provide effective and efficient service selection for service composers. We also present a multi-phase, multi-party negotiation protocol, where the ant colony system is applied to select services with the best or near-optimal utility outputs. In order to adapt the ant colony system to handle the dynamic scenarios during negotiations, we also discuss several strategies for modifying the pheromone information in the first place. The experimental results show that our negotiation-based approach can facilitate the data-intensive service provision with better outcome.
报告人简介：沈俊博士2001年在东南大学获得计算机工学博士学位，先后在澳大利亚多所高校从事科研教学工作，现在伍伦贡大学任 职，已经指导毕业博士4名，硕士3名。他在该校兼任ICT硕士学位协调人，信息系统和技术系学术委员会主席，学位委员会主任，他是IEEE高级会 员和ACM高级会员，担任《Journal of Web Services Research》《Services Oriented Computing and Applications》《International Journal of Cloud Computing》《International Journal of Embedded Sysem》编委，曾经四次担任IEEE国际会议程序委员会主席，曾被40多国际顶级杂志邀请审稿，先后担任60多国际会议程序委员会委员，其中已经连续 多年担任国际面向服务的计算大会(ICSOC)，IEEE服务计算大会(SCC)，云计算大会(CLOUDS)和大数据峰会(Big Data)的程序委员。他本人已经发表论文90多篇。
7月31日学术报告通知（施国琛教授 台湾中央大学）
发布日期：2014-7-29 发布者：刘肖凡浏览次数：1175
Motion Interpretation -
Virtual Music Instrument as Examples
7月31日（星期四）下午3点，九龙湖校区313会议室
Timothy K. Shih
<!--[if !vml]-->
<!--[endif]-->
Human-Computer-Interaction may allow people to communicate with machines in intuitive ways by exploring new usability of cameras and sensors. The MINE Lab (http://mine.csie.ncu.edu.tw/core/) uses a number of cameras, such as Kinect, Leap Motion and Creative Senz3D, to design a series of virtual music instruments. These instruments include Drum, Guitar, Bass Guitar, Piano, Xylophone, as well as a specially designed virtual instrument called the Spider King. Techniques include gesture tracking on human body and fingers. We follow three important principals. Frist, the performers should not carry anything in hand. Second, the performance must be understood and appreciated by general audiences. Third, music professionals may appreciate the designs. The MINE Virtual Band was introduced in May 2013. The concert performed in May 9th, 2013 and May 8th, 2014 receives very good comments from the audiences. This presentation includes basic techniques and concepts of using different sensors, as well as the designs of virtual instruments. In addition to the virtual band, our performance includes special effects on large screen, for real-time interaction with the audiences.
Biography of Timothy K. Shih
<!--[if !vml]-->
<!--[endif]-->Timothy K. Shih (http://www.csie.ncu.edu.tw/~tshih/) is a Professor at the National Central University, Taiwan. He was the Dean of the
9月5日学术报告通知（Jeff Pan教授 英国阿伯丁大学）
发布日期：2014-9-3 发布者：刘肖凡浏览次数：743
应漆桂林教授邀请，英国阿伯丁大学的Jeff Pan教授将于9月5日在我院举办学术报告会，欢迎感兴趣的老师和同学踊跃参加。
报告时间：2014年9月5日（周五）上午9:30-10:30
报告地点：计算机楼3楼会议室
报告题目：4 Vs in Semantic Reasoning: Variety, Velocity, Volumn and Veracity
报告摘要：The talk will begin with some example to illustrate why semantic web technologies are regarded as best practice for handling data integration. With semantic web tecnologies moving into main stream (some evidence will be provided in the talk), reasoning with semantic big data becomes a key task for bridging the gap betweeen data and query based exploitation. I will then give an overview of the start of the art on semantic reasoning, from the perspectives of variety, velocity, volumn and veracity. I will conclude the talk with some observations on related topics.
报告人简介：Jeff Z. Pan is a Reader (non-chair Professor) in the Department of Computing Science at
10月23日学术报告通知（Sylvie Doutre、Laurent Perrussel，法国图卢兹大学）
发布日期：2014-10-22 发布者：刘肖凡浏览次数：598
应漆桂林教授的邀请，法国图卢兹大学的Sylvie Doutre和Laurent Perrussel两位教授将在我院进行讲座，信息如下，欢迎各位参加。
报告时间：10月23日星期四，上午9点半到11点
报告地点：九龙湖计算机楼2楼会议室
报告1
报告人：Sylvie Doutre
报告人简介：Associate professor at the University of Toulouse, IRIT (France) since 2005. Research assistant at the University of Liverpool in 2004. PhD from the University of Toulouse in 2002. Main research topics: knowledge representation and reasoning, logic, argumentation (http://www.irit.fr/~Sylvie.Doutre).
报告题目：Constraints and changes in argumentation
报告摘要:This talk addresses the issue of enforcing a constraint in an argumentation system. The system consists in (1) an argumentation framework, the structure of which is made up of a set of arguments and of an attack relationship, (2) an acceptability semantics, and (3) acceptable sets of arguments, computed from (1) and (2). An agent may want another agent to consider a new attack, or to have a given argument in at least one extension, or even to relax the definition of the semantics. A constraint on any of the three components is thus defined, and it has to be enforced in the system. The enforcement may result in changes on components of the system. The talk surveys existing approaches for the dynamic enforcement of a constraint and its consequences, in the light of the three components, and reveals enforcement cases that remain to be investigated.
报告2
报告人：Laurent Perrussel
报告人简介：Associate professor at the University of Toulouse, IRIT (France) since 1998. His main research topics are (i) reasoning about action and change and (ii) social intelligence. His work currently focuses on belief change and strategic reasoning. (http://www.irit.fr/~Laurent.Perrussel).
报告题目：Trust-Based Belief Change
报告摘要：The aim of this talk is to exhibit a logic that supports reasoning about trust-based belief change. *Trust-based belief change* refers to belief change that depends on the degree of trust the receiver has in the source of information.
On the technical level, our approach consists in extending Liau's static modal logic of belief and trust in three different directions:
(i) a generalization of Liau's approach to graded trust,
(ii) its extension by modal operators of knowledge and by modal operators of graded belief,
(iii) by a family of dynamic operators in the style of dynamic epistemic logics (
The latter operators allow us to represent the consequences of a given trust-based belief change operation. We consider two kinds of trust-based belief change policy, namely an *additive* policy that gives priority to the last information source and a compensatory policy that balances opposite information received by different information sources.
11月7日学术报告通知（Lixin Gao教授，美国马萨诸塞大学阿默斯特分校）
发布日期：2014-11-4 发布者：刘肖凡浏览次数：660
应罗军舟教授的邀请，美国马萨诸塞大学阿默斯特分校的Lixin Gao教授将在我院进行讲座，信息如下，欢迎各位参加。
报告时间：11月7日星期五，上午9点到10点
报告地点：九龙湖计算机楼313会议室
报告人：Professor Lixin Gao
报告人简介：Lixin Gao is a professor of Electrical and Computer Engineering at the University of Massachusetts at Amherst. She received her Ph.D. degree in computer science from the
报告题目：Distributed Frameworks for Iterative Computations on Massive Datasets
报告摘要: The advances in sensing, storage, and networking technology have created huge collections of high-volume, high-dimensional data. Making sense of these data is critical for companies and organizations to make better business decisions, and even brings convenience to our daily life. Recent advances in data mining, machine learning, and applied statistics have led to a flurry of data analytic techniques that typically require an iterative refinement process. However, the massive amount of data involved and potentially numerous iterations required make performing data analytics in a timely manner challenging. In this talk, we present a series of distributed frameworks that enable fast iterative computations. By providing the support of iterative computations and asynchronous prioritized execution, we can ensure fast convergence of the iterative process.
|
11月19日学术报告通知（钱志云博士，加利福尼亚大学Riverside分校）
发布日期：2014-11-17 发布者：刘肖凡浏览次数：562
应曹玖新教授邀请，加利福尼亚大学Riverside分校钱志云博士将在我院做学术报告。
报告时间：11月19日（周三）下午2：00
报告地点：九龙湖校区计算机楼311
报告题目：Storage side channel attacks in modern OS and network stacks.
报告摘要：In this talk, I will introduce a class of practical storage side channel attacks against the Android OS and the TCP stacks. They lead to significant damage to user privacy, network security, application integrity. The attack in Android allows a background app to infer what the foreground app is doing without requiring any permission. Knowing the state of the foreground app, we are then able to hijack the foreground app and launch phishing attacks to steal sensitive information such as passwords and bank account info. The attack in TCP stacks allows an off-path attacker on the Internet to hijack TCP connections created between a legitimate client and server.
For instance, we are able to hijack the browser's connection to facebook and replace it with a phishing login page to steal credentials. Prompted by our work, corresponding vendors (e.g., Checkpoint, Linux kernel) have proposed mitigation solutions and applied patches.
报告人简介：Dr. Zhiyun Qian is an assistant professor at
11月28日院友徐永南博士访问我院
发布日期：2014-11-26 发布者：刘肖凡浏览次数：676
应罗军舟教授的邀请，我院院友徐永南博士将于周五访问九龙湖校区，并作学术报告。报告日程如下：
时间：11月28日14.30～15.30
地点：九龙湖校区计算机楼3楼会议室
报告题目：Big Data in the Internet: Fundamentals, Implementation and Impact
报告摘要：This talk discusses the concept and solution of Big Data from the Internet point of view. Based on Big Data solutions in real environment, this presentation reviews the data processing technologies, system requirement analysis, and architecture design. The talk will also address the impact of Big Data to new Internet technologies such as IoT, Cloud Computing and Software Defined Network, and the challenges and opportunities in their study, research and development.
报告人简介：Darren Xu is a Network Architect in the telecommunication division of Transaction Network Services. He earned his B.S. degree and M.S. degree in Computer Science from