2014/06/10 by Seyedakbar Mostafavi, Mostafavi, Seyedakbar, Mehdi Dehghan +1
Computer Science · Decision Sciences · Physics and Astronomy · #Caching and Content Delivery #FOS: Computer and information sciences #Game Theory and Applications #Networking and Internet Architecture (cs.NI) #Opinion Dynamics and Social Influence #Peer-to-Peer Network Technologies
paper · pdf · doi:10.48550/arxiv.1406.2479
openalex publication_date 2014/06/10 · openalex created_date 2022/02/24 · openalex updated_date 2026/07/28
In Peer-to-Peer (P2P) multichannel live streaming, helper peers with surplus\nbandwidth resources act as micro-servers to compensate the server deficiencies\nin balancing the resources between different channel overlays. With deployment\nof helper level between server and peers, optimizing the user/helper topology\nbecomes a challenging task since applying well-known reciprocity-based choking\nalgorithms is impossible due to the one-directional nature of video streaming\nfrom helpers to users. Because of selfish behavior of peers and lack of central\nauthority among them, selection of helpers requires coordination. In this\npaper, we design a distributed online helper selection mechanism which is\nadaptable to supply and demand pattern of various video channels. Our solution\nfor strategic peers' exploitation from the shared resources of helpers is to\nguarantee the convergence to correlated equilibria (CE) among the helper\nselection strategies. Online convergence to the set of CE is achieved through\nthe regret-tracking algorithm which tracks the equilibrium in the presence of\nstochastic dynamics of helpers' bandwidth. The resulting CE can help us select\nproper cooperation policies. Simulation results demonstrate that our algorithm\nachieves good convergence, load distribution on helpers and sustainable\nstreaming rates for peers.\n