A Survey on Dynamic Job Scheduling in Grid Environment Based on Heuristic Algorithms
It addresses the problem of efficient resource allocation in distributed computing for various sciences, but is incremental as it reviews existing methods.
This paper surveys heuristic algorithms for dynamic job scheduling in grid computing environments, aiming to improve job throughput and resource utilization.
Computational Grids are a new trend in distributed computing systems. They allow the sharing of geographically distributed resources in an efficient way, extending the boundaries of what we perceive as distributed computing. Various sciences can benefit from the use of grids to solve CPU-intensive problems, creating potential benefits to the entire society. Job scheduling is an integrated part of parallel and distributed computing. It allows selecting correct match of resource for a particular job and thus increases the job throughput and utilization of resources. Job should be scheduled in an automatic way to make the system more reliable, accessible and less sensitive to subsystem failures. This paper provides a survey on various heuristic algorithms, used for scheduling in grid.