Spiral Walk on Triangular Meshes : Adaptive Replication in Data P2P Networks

TL;DR

This paper presents a decentralized, adaptive replication strategy for P2P networks using a spiral walk algorithm on triangular meshes, ensuring even distribution and efficient search with minimal overhead.

Contribution

It introduces a novel spiral walk algorithm for exhaustive neighborhood exploration and protocols for maintaining a triangular mesh topology in P2P networks.

Findings

Replication evenly populates the network mesh.

The approach adapts to node joins and leaves.

Search efficiency is improved with super peers.

Abstract

We introduce a decentralized replication strategy for peer-to-peer file exchange based on exhaustive exploration of the neighborhood of any node in the network. The replication scheme lets the replicas evenly populate the network mesh, while regulating the total number of replicas at the same time. This is achieved by self adaptation to entering or leaving of nodes. Exhaustive exploration is achieved by a spiral walk algorithm that generates a number of messages linearly proportional to the number of visited nodes. It requires a dedicated topology (a triangular mesh on a closed surface). We introduce protocols for node connection and departure that maintain the triangular mesh at low computational and bandwidth cost. Search efficiency is increased using a mechanism based on dynamically allocated super peers. We conclude with a discussion on experimental validation results.