An Improved Ant Algorithm for Grid Scheduling Problem Using Biased Initial Ants
The efficient scheduling of independent computational jobs in a heterogeneous computing (HC) environment is an important problem in domains such as grid computing. Finding optimal schedules for such an environment is (in general) an NP-hard problem, and so heuristic approaches must be used. The goal of grid task scheduling is to achieve high system throughput and to allocate various computing resources to applications. 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 we introduce a new task scheduling algorithm based on Ant Colony Optimization (ACO). According to the experimental results, the proposed algorithm confidently demonstrates its competitiveness with previously proposed algorithms.
Grid computing grid Scheduling ACO Elitism ETC Matrix
Mojtaba MadadyarAdeh Jamshid Bagherzadeh
Sama Technical and Vocational training school, Islamic Azad University, Urmia Branch Urmia, Iran Department of computer Engineering Urmia, Iran
国际会议
上海
英文
373-378
2011-03-11（万方平台首次上网日期，不代表论文的发表时间）