- author = "Michael Iles and Dwight Deugo",
- title = "A search for routing strategies in a peer-to-peer network using genetic programming",
- booktitle = "Proceedings 21st IEEE Symposium on Reliable Distributed Systems",
- year = "2002",
- pages = "341--346",
- month = "13-16 " # oct,
- keywords = "genetic algorithms, genetic programming, computer networks, discrete event simulation, learning (artificial intelligence), protocols, telecommunication network routing, Gnutella protocol, machine learning techniques, resource location optimization, routing strategies, simulated peer-to-peer network, traffic flow scenarios",
- ISSN = "1060-9857",
-
DOI = "
doi:10.1109/RELDIS.2002.1180207",
- abstract = "Results taken from a simulated peer-to-peer network are described, in which genetic programming is used to evolve routing strategies that optimise resource location in various traffic flow scenarios. In all cases the evolved strategies result in more numerous resource locations than a pure, non-adaptive peer-to-peer protocol such as the Gnutella protocol. The resulting evolved strategies are described, and empirical validation of the Gnutella protocol is given via both its creation through machine-learning techniques, and through the analysis of real-world constants used in the protocol.",
-
notes = "Inspec Accession Number: 7516795.
Carleton Univ., Ottawa, Ont., Canada",
