On the Topology Maintenance of Dynamic P2P Overlays through Self-Healing Local Interactions

TL;DR

This paper proposes self-healing, local-interaction protocols for maintaining topology in dynamic P2P overlays, enhancing reliability through neighborhood knowledge and edge clustering measures, validated by simulation results.

Contribution

Introduces two novel local knowledge-based protocols for topology maintenance in P2P overlays, utilizing 2nd neighborhood info and Edge Clustering Coefficient for improved robustness.

Findings

Protocols are effective across various network types.

Simulation shows improved resilience under failures.

Edge Clustering Coefficient aids in identifying critical edges.

Abstract

This paper deals with the use of self-organizing protocols to improve the reliability of dynamic Peer-to-Peer (P2P) overlay networks. We present two approaches, that employ local knowledge of the 2nd neighborhood of nodes. The first scheme is a simple protocol requiring interactions among nodes and their direct neighbors. The second scheme extends this approach by resorting to the Edge Clustering Coefficient (ECC), a local measure that allows to identify those edges that connect different clusters in an overlay. A simulation assessment is presented, which evaluates these protocols over uniform networks, clustered networks and scale-free networks. Different failure modes are considered. Results demonstrate the viability of the proposal.