Date(s) : 16/02/2018 iCal
14 h 00 min - 15 h 00 min
In this presentation, we adapt mathematical tools and models from Telecommunication Networks to Online Social networks. We will focus our presentation on two main issues in OSNs, algorithms for shaping timelines and the effects of a competition over popularity in OSNs.
This presentation is based on two papers:
– Timelines are publisher-driven caches: Analyzing and shaping timeline networks
Cache networks are one of the building blocks of information centric networks (ICNs). Most of the recent work on cache networks has focused on networks of request driven caches, which are populated based on users requests for content gen- erated by publishers. However, user generated content still poses the most pressing challenges. For such content timelines are the de facto sharing solution. In this paper, we establish a connection between timelines and publisher-driven caches. We propose simple models and metrics to analyze publisher-driven caches, allowing for variable-sized objects. Then, we design two efficient algorithms for timeline workload shaping, leveraging admission and price control in order, for instance, to aid service providers to attain prescribed service level agreements.
– Game theory approach for modeling competition over visibility on social networks
In Online Social Networks, such as Facebook, Linkedin, Twitter, Google+ and others, many members post messages to walls or to timelines of their friends. There is a permanent competition over content visibility since timelines have finite capacity. As new content arrives, older content gets pushed away from the timeline. A selfish source that wishes to be visible has to send from time to time new content thus pre-empting other content from the timeline. We assume that sending more content comes with some extra cost. We study the problem of selecting the rates of content creation as a non-cooperative game between several sources that share some common destination to which they send content. We identify conditions under which the problem can be reduced to the Kelly mechanism for which we compute explicitly the equilibrium. This is done in a very general probabilistic framework where time between arrivals of content is only required to be stationary ergodic.
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