Task scheduling using multi-objective hamming discrete particle swarm optimisation in distributed systems
by S. Sarathambekai; K. Umamaheswari
International Journal of Swarm Intelligence (IJSI), Vol. 2, No. 2/3/4, 2016

Abstract: Task Scheduling (TS) is one of the crucial issues in distributed systems (DS). Finding an optimal schedule for such an environment is NP-hard. Heuristics/meta-heuristics are the efficient technologies for solving NP-hard problems. The well-known existing meta-heuristics such as differential evolution and genetic algorithm need evolutionary operators for finding the solution. Discrete particle swarm optimisation (DPSO) is a recent meta-heuristic technique, which does not need such type of operators to find the optimal solution. This paper presents a modified DPSO. The proposed modified DPSO uses hamming distance to update the particles in the swarm. This kind of distance-based updating technique ensures that all the particles fly only towards the leader particle. Make span, flow time and reliability cost are performance measures to evaluate the efficiency of the proposed DPSO algorithm. Computational simulations are performed based on a set of benchmark instances to evaluate the performance of the proposed algorithm.

Online publication date: Sat, 24-Dec-2016

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