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Proceedings Paper

Multi-objective evolutionary algorithm for investigating the trade-off between pleiotropy and redundancy
Author(s): Zhiyang Ong; Hao-Wei Lo; Matthew Berryman; Derek Abbott
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Paper Abstract

The trade-off between pleiotropy and redundancy in telecommunications networks is analyzed in this paper. They are optimized to reduce installation costs and propagation delays. Pleiotropy of a server in a telecommunications network is defined as the number of clients and servers that it can service whilst redundancy is described as the number of servers servicing a client. Telecommunications networks containing many servers with large pleiotropy are cost-effective but vulnerable to network failures and attacks. Conversely, those networks containing many servers with high redundancy are reliable but costly. Several key issues regarding the choice of cost functions and techniques in evolutionary computation (such as the modeling of Darwinian evolution, and mutualism and commensalism) will be discussed, and a future research agenda is outlined. Experimental results indicate that the pleiotropy of servers in the optimum network does improve, whilst the redundancy of clients do not vary significantly, as expected, with evolving networks. This is due to the controlled evolution of networks that is modeled by the steady-state genetic algorithm; changes in telecommunications networks that occur drastically over a very short period of time are rare.

Paper Details

Date Published: 16 January 2006
PDF: 12 pages
Proc. SPIE 6039, Complex Systems, 60390Q (16 January 2006); doi: 10.1117/12.638406
Show Author Affiliations
Zhiyang Ong, Univ. of Adelaide (Australia)
Univ. of Southern California (United States)
Hao-Wei Lo, Univ. of Adelaide (Australia)
Matthew Berryman, Univ. of Adelaide (Australia)
Derek Abbott, Univ. of Adelaide (Australia)

Published in SPIE Proceedings Vol. 6039:
Complex Systems
Axel Bender, Editor(s)

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