Content and overlay-aware scheduling for peer-to-peer streaming in fluctuating networks
Journal of Network and Computer Applications
CCGRID '09 Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid
FairE9: fair file distribution over mesh-only peer-to-peer
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
p2pWeb: An open, decentralized infrastructure of Web servers for sharing ephemeral Web content
Computer Networks: The International Journal of Computer and Telecommunications Networking
Computer Networks: The International Journal of Computer and Telecommunications Networking
Trustworthy acquaintances in Peer-to-Peer (P2P) overlay networks
International Journal of Business Intelligence and Data Mining
International Journal of Grid and Utility Computing
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We propose a new genre of overlay network for disseminating information from popular but resource constrained sources. We call this communication primitive as Latency Gradated Overlay, where information consumers selforganize themselves according to their individual resource constraints and the latency they are willing to tolerate in receiving the information from the source. Such a communication primitive finds immediate use in applications like RSS feeds aggregation. We propose heuristic algorithms to construct LagOver based on preferably some partial knowledge of the network at users (no knowledge slows the construction process) but no global coordination. The algorithms are evaluated based on simulations and show good characteristics including convergence, satisfying peers' latency and bandwidth constraints even in presence of moderately high membership dynamics. There are two points worth noting. First, optimizing jointly for latency and capacity (i.e., placing nodes that have free capacity close to the source) as long as latency constraint of other nodes are not violated performs better than optimizing for latency only. The joint optimization strategy has faster convergence of the LagOver network, and can deal with adversarial workloads that optimization of only latency can not deal with. Secondly, somewhat counter-intuitively, in order to do the aforementioned joint optimization, it is sufficient to find random nodes based on only the latency constraint, since even if the capacity of individual nodes is saturated it does not matter since the LagOver network can potentially be reconfigured.