JOURNAL ARTICLE

Load balanced job scheduling approach for grid environment

Abstract

Grid computing is a way of combining computers across a network to form a distributed supercomputer to perform complex computations. In the commercial world, grid aims to maximize the utilization of an organization's computing resources by making them shareable across applications. A grid environment can be classified into two types: Computing grids and data grids. In computing grid, job scheduling is an important task. Load Balancing is a technique which is used to distribute the workload equally across multiple computers to enhance resource utilization and to reduce the response time in grid environment. Main goal of load balancing is to balance the load across all the processors. It improves the throughput of grid resources. A good Scheduling algorithm should assign jobs to resources efficiently and balance the system load. Hierarchical Load Balanced Algorithm is used to solve the problem in grid environment.The proposed system Enhanced Hierarchical Load Balance Algorithm is designed to schedule the jobs and also to improve the overall performance of the system in terms of resource utilization and user satisfaction. It also reduces the makespan of the jobs. If the resource capacity satisfies the need of the user then the job will be done within particular time period.

Keywords:
Computer science Grid computing Distributed computing Load balancing (electrical power) Grid Workload Job scheduler Supercomputer Scheduling (production processes) Schedule Job shop scheduling Load management DRMAA Parallel computing Operating system Mathematical optimization Cloud computing

Metrics

8
Cited By
1.81
FWCI (Field Weighted Citation Impact)
11
Refs
0.88
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Distributed and Parallel Computing Systems
Physical Sciences →  Computer Science →  Computer Networks and Communications
Parallel Computing and Optimization Techniques
Physical Sciences →  Computer Science →  Hardware and Architecture
Cloud Computing and Resource Management
Physical Sciences →  Computer Science →  Information Systems

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