Abstract
Grid computing enlarge with computing platform which is collection of heterogeneous computing resources connected by a network across dynamic and geographically dispersed organization to form a distributed high performance computing infrastructure. Grid computing solves the complex computing problems amongst multiple machines. Grid computing solves the large scale computational demands in a high performance computing environment. The main emphasis in the grid computing is given to the resource management and the job scheduler .The goal of the job scheduler is to maximize the resource utilization and minimize the processing time of the jobs. Existing approaches of Grid scheduling doesn’t give much emphasis on the performance of a Grid scheduler in processing time parameter. Schedulers allocate resources to the jobs to be executed using the First come First serve algorithm. In this paper, we have provided an optimize algorithm to queue of the scheduler using various scheduling methods like Shortest Job First, First in First out, Round robin. The job scheduling system is responsible to select best suitable machines in a grid for user jobs. The management and scheduling system generates job schedules for each machine in the grid by taking static restrictions and dynamic parameters of jobs and machines into consideration. The main purpose of this paper is to develop an efficient job scheduling algorithm to maximize the resource utilization and minimize processing time of the jobs. Queues can be optimized by using various scheduling algorithms depending upon the performance criteria to be improved e.g. response time, throughput. The work has been done in MATLAB using the parallel computing toolbox.
Highlights
Grid computing, originally motivated by wide-area sharing of computational resources [1], has evolved to be mainstream technologies for enabling large-scale virtual organization [2]
The main purpose of this paper is to develop an efficient job scheduling algorithm to maximize the resource utilization and minimize processing time of the jobs, how they are grouped and allocated to resources in dynamic environment
An algorithm is designed for an efficient job scheduling algorithm to maximize the resource utilization and minimize processing time of the jobs
Summary
Originally motivated by wide-area sharing of computational resources [1], has evolved to be mainstream technologies for enabling large-scale virtual organization [2]. Ian Foster of the US department of energy’s Argonne National labs and university of Chicago has given a demonstration to create one super “meta computer” called I way.The term “Grid” refers to systems and application that integrate resources and services distributed across multiple control domains [3].Computational grids provide large-scale resource sharing, such as personal computer, clusters, MPPs, Data Base, and online instructions, which may be crossdomain, dynamic and heterogeneous[4]. In a Grid computing environment, scheduler is responsible for selecting the suitable machines or computing resources in Grid for processing jobs to achieve high system throughput, but there exist several applications with a large number of lightweight jobs [5].Job scheduling with light weight gives low performance in terms of processing time and communication time.
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