Open AccessDYNAMIC JOB SCHEDULING IN GRID COMPUTING
Author(s) -
Jani Kuntesh Ketan,
Arpita Shah
Publication year - 2016
Publication title -
international journal of computer and communication technology
Language(s) - English
Resource type - Journals
eISSN - 2231-0371
pISSN - 0975-7449
DOI - 10.47893/ijcct.2016.1364
Subject(s) - computer science , distributed computing , grid computing , job scheduler , dynamic priority scheduling , fair share scheduling , grid , scheduling (production processes) , two level scheduling , tardiness , rate monotonic scheduling , job shop scheduling , symmetric multiprocessor system , schedule , mathematical optimization , cloud computing , operating system , mathematics , geometry
Grid computing is growing rapidly in the distributed heterogeneous systems for utilizing and sharing large-scale resources to solve complex scientific problems. Scheduling is the most recent topic used to achieve high performance in grid environments. It aims to find a suitable allocation of resources for each job. A typical problem which arises during this task is the decision of scheduling. It is about an effective utilization of processor to minimize tardiness time of a job, when it is being scheduled. Scheduling jobs to resources in grid computing is complicated due to the distributed and heterogeneous nature of the resources. The efficient scheduling of independent jobs in a heterogeneous computing environment is an important problem in domains such as grid computing. In general, finding optimal schedule for such an environment using the traditional sequential method is an NP-hard problem whereas heuristic approaches will provide near optimal solutions for complex problems. The Ant colony algorithm, which is one of the heuristic algorithms, suits well for the grid scheduling environment using stigmeric communication.