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Task scheduling problem in heterogeneous systems is the process of allocatingtasks of an application to heterogeneous processors interconnected byhigh-speed networks, so that minimizing the finishing time of application asmuch as possible. Tasks are processing units of application and haveprecedenceconstrained, communication and also, are presented by DirectedAcyclic Graphs (DAGs). Evolutionary algorithms are well suited for solving taskscheduling problem in heterogeneous environment. In this paper, we propose ahybrid heuristic-based Artificial Immune System (AIS) algorithm for solving thescheduling problem. In this regard, AIS with some heuristics and SingleNeighbourhood Search (SNS) technique are hybridized. Clonning and immune-removeoperators of AIS provide diversity, while heuristics and SNS provideconvergence of algorithm into good solutions, that is balancing betweenexploration and exploitation. We have compared our method with somestate-of-the art algorithms. The results of the experiments show the validityand efficiency of our method.

Hybrid Heuristic-Based Artificial Immune System for Task Scheduling