Self-adaptive Gossip Policies for Distributed Population-based Algorithms

Details Self-adaptive Gossip Policies for Distributed Population-based Algorithms Self-adaptive Gossip Policies for Distributed Population-based Algorithms

2007-03-23

arxiv.org/abs/cs/0703117v1

Computer Science

Distributed, Parallel, and Cluster Computing

Submitted to Europar 2007

Scientific paper

Gossipping has demonstrate to be an efficient mechanism for spreading information among P2P networks. Within the context of P2P computing, we propose the so-called Evolvable Agent Model for distributed population-based algorithms which uses gossipping as communication policy, and represents every individual as a self-scheduled single thread. The model avoids obsolete nodes in the population by defining a self-adaptive refresh rate which depends on the latency and bandwidth of the network. Such a mechanism balances the migration rate to the congestion of the links pursuing global population coherence. We perform an experimental evaluation of this model on a real parallel system and observe how solution quality and algorithm speed scale with the number of processors with this seamless approach.

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