Design and Analysis of a Bio-inspired Search Algorithm for Peer to Peer Networks

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in Buch/Sammelband/GutachtenBeigetragenBegutachtung


Decentralized peer to peer (p2p) networks like Gnutella are attractive for certain applications because they require no centralized directories and no precise control over network topology or data placement. The greatest advantage is the robustness provided by them. However, flooding-based query algorithms used by the networks produce enormous amounts of traffic and substantially slow down the system. Recently, flooding has been replaced by more efficient k-random walkers and different variants of such algorithms. In this paper, we report immune-inspired algorithms for searching peer to peer networks. The algorithms use the immune-inspired mechanism of affinity-governed proliferation to spread query message packets in the network. Through a series of experiments, we compare the proliferation mechanism with different variants of random walk algorithms. The detailed experimental results show message packets undergoing proliferation spread much faster in the network and consequently proliferation algorithms produce better search output in p2p networks than random walk algorithms. Moreover, theoretical results by calculating the packet spreading speeds are reported which provide an understanding of the improved performance of the proliferation based search algorithm.


TitelSelf-star Properties in Complex Information Systems
Herausgeber (Verlag)Springer, Berlin [u. a.]
ISBN (elektronisch)3540260099
ISBN (Print)978-354026009-7
PublikationsstatusVeröffentlicht - 2005


ReiheLecture Notes in Computer Science, Volume 3460

Externe IDs

Scopus 33748573496
ORCID /0000-0003-0137-5106/work/142244252