Modeling Data Dissemination in Online Social Networks: A Geographical Perspective on Bounding Network Traffic Load

Modeling Data Dissemination in Online Social Networks: A Geographical Perspective on Bounding Network Traffic Load

时间： 地点：九龙湖计算机楼三楼会议室

报告简介：

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.

报告人简介：

Dr. Shaojie Tang is currently an assistant professor of Naveen Jindal School of Management at University of Texas at Dallas. He received his PhD in computer science from Illinois Institute of Technology in 2012, B.S degree in radio engineering from Southeast University in 2006. His research interest includes social networks, mobile commerce, game theory, e-business and optimization. He received the Best Paper Awards in ACM MobiHoc 2014 and IEEE MASS 2013. He also received the ACM SIGMobile service award in 2014. Tang served in various positions (as chairs and TPC members) at numerous conferences, including IEEE INFOCOM, IEEE ICDCS, ACM MobiHoc and IEEE ICNP. He is an editor for Elsevier Information Processing in the Agriculture and International Journal of Distributed Sensor Networks.

计算机网络和信息集成教育部重点实验室（东南大学）