Analytical study of job scheduling using variants of Ant Colony Optimization technique in grid

As communication was the major perspective of traditional networks, grid computing focuses on figuring the problems by using unprocessed CPU cycles that cannot be resolved by stand-alone computers. Grid being an earthly distributed network of computers provides a clear, coordinated, consistent and reliable computing medium to various applications. Owing to the heterogeneity of resources in a grid environment, job scheduling is problematic and therefore, needs competent schedulers. The paper provides a comparative analysis of various Ant colony optimization variants based on their effectiveness in determining optimal or near optimal solutions. The conclusion drawn from the survey explores ACO's effectiveness in solving the various scheduling problems. However, uncertainty in convergence time and early Designation of the initial and the extreme point hinders optimal scheduling. With the support of literature survey, not only assured guidelines are extracted for ACO algorithm but also, promising directions are provided for future work.