The use of multiple objective genetic algorithm in self-healing network

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

2 Scopus Citations
View graph of relations

Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)104-128
Journal / PublicationApplied Soft Computing Journal
Volume2
Issue number2
Publication statusPublished - 2002

Abstract

This paper presents a genetic algorithm based method to solve the capacity and routing assignment problem arising from the design of self-healing networks using the virtual path (VP) concept. Past research has revealed that the pre-planned backup protection method and the path restoration scheme can provide a good compromise between the reserved amount of spare capacity and the failure restoration time. Our aim is to minimize the sum of working and backup capacity usage while a set of customer traffic demands can still be satisfied and the traffic is 100% restorable under a single point of failure. A searching technique, genetic algorithm (GA), is proposed to perform this optimization. There are several advantages of using a genetic algorithm which includes lower computational cost in reaching a reasonably good virtual path routing scheme and less complex mathematical formulation. Another technique, exhaustive-like search, is also utilized in order to compare their results. Moreover, we implement two restoration schemes for multicast connections, link restoration and path restoration, for comparison purposes. Most of the past research mainly focused on the unicast traffic, but our method works for both unicast traffic and multicast traffic. © 2002 Elsevier Science B.V. All rights reserved.

Research Area(s)

  • Genetic algorithm, Network, Self-healing