Resilience to churn of a peer-to-peer evolutionary algorithm

被引：24

作者：

Laredo, Juan L.J. ^{[1
]}

Castillo, Perdo A. ^{[1
]}

Mora, A.M. ^{[1
]}

Merelo, M. ^{[1
]}

Fernandes, C. ^{[2
]}

机构：

[1] Department of Architecture and Computer Technology, University of Granada, 18071 Granada, Periodista Daniel Saucedo

[2] LASEEB-ISR/IST, University of Lisbon, 1049-001 Lisbon, Av. Rovisco Pais

来源：

International Journal of High Performance Systems Architecture | 2008年 / 1卷 / 04期

关键词：

Churn; Evolutionary computation; Evolvable agent; Fault tolerance analysis; Peer-to-peer computing; Scalability;

D O I：

10.1504/IJHPSA.2008.024210

中图分类号：

学科分类号：

摘要：

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. Copyright © 2008, Inderscience Publishers.

引用

页码：260 / 268

页数：8

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