Maximizing availability for task scheduling in on-demand computing-based transaction processing system using ant colony optimization

摘要

Maximization of availability and minimization of the makespan for transaction scheduling in anrnon-demand computing system is an emerging problem. The existing approaches to find the exactrnsolutions for this problem are limited. This paper proposes a task scheduling algorithm using antrncolony optimization (MATS_ACO) to solve the mentioned problem. In this method, first, availabilityrnof the systemis computed,andthen, the transactions are scheduled using theforagingbehaviorrnof ants to find the optimal solutions.We also modify two known meta-heuristic algorithms suchrnas genetic algorithm (GA) and extremal optimization (EO) to obtain transaction scheduling algorithmsrnfor the purpose of comparison with our proposed algorithm. The compared results showrnthat the proposed algorithm performs better than others.