Authors: Laredo, J.L.J.¹; Castillo, P.A.¹; Mora, A.M.¹; Merelo, J.J.¹; Fernandes, C.²

Source: International Journal of High Performance Systems Architecture, Volume 1, Number 4, 29 March 2009 , pp. 260-268(9)

Publisher: Inderscience Publishers

Abstract:

In this paper we analyse the resilience of a peer-to-peer (P2P) evolutionary algorithm (EA) subject to the following dynamics: computing nodes acting as peers leave the system independently from each other causing a collective effect known as churn. Since the P2P EA has been designed to tackle large instances of computationally expensive problems, we will assess its behaviour under these conditions, by performing a scalability analysis in five different scenarios using the massively multimodal deceptive problem as a benchmark. In all cases, the P2P EA reaches the success criterion without a penalty on the runtime. We show that the key to the algorithm resilience is to ensure enough peers at the beginning of the experiment; even if some of them leave, those that remain contain enough information to guarantee a reliable convergence.

Keywords: COMPUTING AND MATHEMATICS JOURNALS; Computing Science, Applications and Software

Document Type: Research article

DOI: http://dx.doi.org/10.1504/IJHPSA.2008.024210

Affiliations: 1: Department of Architecture and Computer Technology, University of Granada, Periodista Daniel Saucedo, 18071 Granada, Spain. 2: LASEEB-ISR/IST, University of Lisbon, Av. Rovisco Pais 1049-001 Lisbon, Portugal

Publication date: 2009-03-29

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