Sciweavers

Share
IJCSA
2007

Multiprocessor Scheduling Using Hybrid Particle Swarm Optimization with Dynamically Varying Inertia

8 years 4 months ago
Multiprocessor Scheduling Using Hybrid Particle Swarm Optimization with Dynamically Varying Inertia
The problem of task assignment in heterogeneous computing systems has been studied for many years with many variations. We have developed a new hybrid approximation algorithm. The proposed hybrid heuristic model involves Particle Swarm Optimization (PSO) Algorithm and Simulated Annealing (SA) algorithm. This PSO/SA performs static allocation of tasks in a heterogeneous distributed computing system in a manner that is designed to minimize the cost. Particle Swarm Optimization with dynamically reducing inertia is implemented which yields better result than fixed inertia. The experimental results manifest that the proposed hybrid method is effective and efficient in finding near optimal solutions.
S. N. Sivanandam, P. Visalakshi, A. Bhuvaneswari
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2007
Where IJCSA
Authors S. N. Sivanandam, P. Visalakshi, A. Bhuvaneswari
Comments (0)
books