Hybrid PSO for job scheduling to minimize makespan in heterogeneous grids

Grid computing federates heterogeneous resources distributed over different geographical domains with the perspective of providing high computational power in the most seamless way. Grid environment is a decisive and cost effective intelligent paradigm that facilitates fixing of complex parallel application by co-coordinating resources (storage space, software applications, computers, sensors) and sharing data. Heterogeneity of resources in grid paradigm has faced major scheduling issues. The paper suggests hybridized algorithm for scheduling parallel jobs. The algorithm put together features of Particle swarm optimization, cuckoo search and genetic algorithm to resolve various scheduling issues.