Multiprocessor Scheduling Using Particle Swarm Optimization

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Provided by: International Journal of the Computer, the Internet and Management (IJCIM)
Topic: Hardware
Format: PDF
The problem of task assignment in heterogeneous computing systems has been studied for many years with many variations. The authors have developed a new hybrid approximation algorithm and also a parallel version of Particle Swarm Optimization to solve the task assignment problem. 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 (PSO) with dynamically reducing inertia is implemented which yields better result than fixed inertia.
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