An IPSO Algorithm for Grid Task Scheduling Based on Satisfaction Rate

This paper proposes an Immune Particle Swarm Optimization (IPSO) algorithm and a model of grid task scheduling based on satisfaction rate that address multi-objective optimization problems of task scheduling in dynamic and heterogeneous grid environments. The IPSO algorithm is implemented in simulation environment of grid task scheduling according to the objective function based on satisfaction rate. The simulation results demonstrate that such a method which employs the IPSO algorithm has better performance than the existing methods that use particle swarm optimization (PSO) in global optimization capacity, searching speed and avoiding prematurity.