GLOA: A New Job Scheduling Algorithm for Grid Computing

TitleGLOA: A New Job Scheduling Algorithm for Grid Computing
Publication TypeJournal Article
Year of Publication2013
AuthorsPooranian, Z., M. Shojafar, J. H. Abawajy, and M. Singhal
JournalInternational Journal of Interactive Multimedia and Artificial Intelligence
IssueSpecial Issue on Artificial Intelligence and Social Application
Date Published03/2013

The purpose of grid computing is to produce a virtual supercomputer by using free resources available through widespread networks such as the Internet. This resource distribution, changes in resource availability, and an unreliable communication infrastructure pose a major challenge for efficient resource allocation. Because of the geographical spread of resources and their distributed management, grid scheduling is considered to be a NP-complete problem. It has been shown that evolutionary algorithms offer good performance for grid scheduling. This article uses a new evaluation (distributed) algorithm inspired by the effect of leaders in social groups, the group leaders' optimization algorithm (GLOA), to solve the problem of scheduling independent tasks in a grid computing system. Simulation results comparing GLOA with several other evaluation algorithms show that GLOA produces shorter makespans.

KeywordsArtificial Intelligence, Distributed Computing, Grid computing, Job Scheduling, Makespan
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