Ad Hoc, self-supervising peer-to-peer search networks

TLDR

Peer‑to‑peer search networks are widely used for searching massive distributed digital repositories, but as they grow, peers can become overloaded by processing messages from other peers. The study examines how to reduce node load in P2P networks by enabling peers to self‑organize into a relatively efficient network and then self‑tune for greater efficiency. The authors introduce two local operations—connect() to form an ad‑hoc search or index link, and break() to remove a link that produces excessive load—and describe various implementations of these operations, examining the resulting network structures. Simulation results show that replacing fixed rules with dynamic local decision‑making yields self‑supervising networks that better adjust to conditions, outperform popular supernode topologies in efficiency, and exhibit improved fault tolerance and search latency.

Abstract

Peer-to-peer search networks are a popular and widely deployed means of searching massively distributed digital information repositories. Unfortunately, as such networks grow, peers may become overloaded processing messages from other peers. This article examines how to reduce the load on nodes in P2P networks by allowing them to self-organize into a relatively efficient network, and then self-tune to make the network even more efficient. Two local operations used by a peer are introduced: connect() , in which the peer forms an ad hoc search or index link to another peer, and break() , in which the peer breaks a link that is producing too much load. By replacing fixed rules with dynamic local decision-making, such “self-supervising” networks can better adjust to network conditions. Different ways to implement connect() and break() are described, and the network structures that form under different configurations are examined. Simulation results indicate that the ad hoc networks formed using the described techniques are more efficient than popular supernode topologies for several important scenarios. Results for the fault tolerance and search latency of such ad hoc networks are also presented.