Gossip-based Peer Sampling in Social Overlays

Performance of many P2P systems depends on the ability to construct a random 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 between them. However, this is not the case in some of the environments where distributed systems are required to be deployed, e.g, Decentralized Online Social Networks, Wireless networks, or networks with limited connectivity because of NATs/firewalls, etc. In such restricted networks, every node is able to communicate 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 every 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 network. 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.