An efficient meta-heuristic algorithm for grid computing

Zahra Pooranian, Mohammad Shojafar, Jemal H. Abawajy, Ajith Abraham
  • Journal of Combinatorial Optimization, July 2013, Springer Science + Business Media
  • DOI: 10.1007/s10878-013-9644-6

An efficient meta-heuristic algorithm for grid computing

What is it about?

A grid computing system consists of a group of programs and resources that are spread across machines in the grid. A grid system has a dynamic environment and decentralized distributed resources, so it is important to provide efficient scheduling for applications. Task scheduling is an NP-hard problem and deterministic algorithms are inadequate and heuristic algorithms such as particle swarm optimization (PSO) are needed to solve the problem. PSO is a simple parallel algorithm that can be applie

Why is it important?

Apply several AI methods in Grid scheduling regarding makespan and completion time point -point for multi-types of workloads, VMs, CPU unitilization and computation parameters

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The following have contributed to this page: Mohammad Shojafar, Prof. Dr. Ajith Abraham, and Professor Jemal Abawajy