Comparison of Efficient Job Scheduling Mechanisms Used in Grid Computing: A Review

Availability of fast and reliable internet, high speed networks and powerful computers led to the emergence of a new paradigm known as Grid Computing. Grid computing is a form of distributed computing which enables the users to share the heterogeneousresources which are geographically dispersed to solve a complex problem.The heterogeneous nature and tremendous amount of resources makes Grid scheduling a challenging task.Heuristic scheduling is widely used in grid environment due to its advantage over time and cost.We have performed comparative study on Simulated Annealing algorithms (SA), Taboo search algorithms (TS) are categorized under Local search based .Ant Colony scheduling algorithms (ACS), Genetic algorithms (GA),Particle Swarm Optimization Algorithm (POS) are categorized under Population Based. Motivation of this memorandum is to encourage the amateur researcher in the field of grid computing, so they understand easily the concept of scheduling and can contribute in the development more scheduling algorithm. This study provides a comparative analysis on various scheduling algorithm potentials.