Gossip based peer sampling in social overlays
Performance of many P2P systems depends on the ability to construct a ran-
dom overlay network among the nodes. Current state-of-the-art techniques for constructing random overlays have an implicit requirement that any two nodes in the system should always be able to communicate and establish a link be- tween them. However, this is not the case in some of the environments where distributed systems are required to be deployed, e.g, Decentralized Online So- cial Networks, Wireless networks, or networks with limited connectivity because of NATs/firewalls, etc. In such restricted networks, every node is able to com- municate with only a predefined set of nodes and thus, the existing solutions for constructing random overlays are not applicable.In this thesis we propose a gossip based peer sampling service capable of running on top of such restricted networks and producing an on-the-fly random overlay. The service provides ev- ery participating node with a set of uniform random nodes from the network, as well as efficient routing paths for reaching those nodes via the restricted net- work. We perform extensive experiments on four real-world networks and show that the resulting overlays rapidly converge to random overlays. The results also exhibit that the constructed random overlays have self healing behaviour under churn and catastrophic failures.
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