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