Earticle

초록

영어

Grid computing is a promising technology for future computing platforms and is expected to provide easier access to remote computational resources that are usually locally limited. Scheduling is one of the active research topics in grid environments. The goal of grid task scheduling is to achieve high system throughput and to allocate various computing resources to applications. The Complexity of scheduling problem increases with the size of the grid and becomes highly difficult to solve effectively. Many different methods have been proposed to solve this problem. Some of these methods are based on heuristic techniques that provide an optimal or near optimal solution for large grids. In this paper, a new heuristic algorithm for scheduling meta-tasks in grid computing system is presented which tries to consider the execution time and machine state simultaneously by a mapping function. According to the experimental results, the proposed algorithm confidently demonstrates its competitiveness with previously proposed algorithms.

목차

Abstract
 1. Introduction
 2. Problem Definition
 3. Related Works
  3.1. Opportunistic Load Balancing (OLB)
  3.2. Minimum Execution Time (MET)
  3.3. Minimum Completion Time (MCT)
  3.4. Min-min
  3.5. Max-min
  3.6. SA Based Methods
  3.7. GA Based Method
  3.8. GSA method
 4. Proposed Approach
 5. Experimental Results
  5.1. Benchmark Description
  5.2. Makespan
  5.3. Execution Times
 6. Conclusion
 References

키워드

저자

• Sadegh Nejatzadeh [ Shahid Beheshti University ]
• Mahmood Karamipour [ K. N. Toosi University of technology ]
• Mohammad Eskandari [ Shahid Beheshti University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Grid and Distributed Computing

• 간기

  격월간

• pISSN

  2005-4262

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605