An intelligent method for static task scheduling in heterogeneous distributed systems using ant colony algorithm

Abstract

Task matching and static scheduling in heterogeneous distributed computing systems is of particular importance, given the optimal use of existing computing machines and spending less time for scheduling algorithm. Removing this problem using classical algorithms such as dynamic programming and backtracking requires a huge computing time; so, many attempts have taken through using innovative approaches. Of innovative methods, genetic algorithm and ant colony algorithm are of great significance. This paper proposes the new algorithm naming ant colony technique for scheduling. Algorithm computing time depends on the number of tasks in scheduling problem. Simulations and comparisons show that the proposed algorithm significantly reduces response time or task static time in comparison to genetic algorithm. While, the response time or time for the latest task finishing time slightly declines.