GLOA : a new job scheduling algorithm for grid computing
Data(s) |
01/01/2013
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Resumo |
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. |
Identificador | |
Idioma(s) |
eng |
Publicador |
Imal-Software |
Relação |
http://dro.deakin.edu.au/eserv/DU:30058862/pooranian-gloaanewjob-2013.pdf http://doi.org/10.9781/ijimai.2013.218 |
Direitos |
2013, Imal-Software |
Palavras-Chave | #artificial intelligence #distributed computing #grid computing #job scheduling #makespan |
Tipo |
Journal Article |