PERFORMANCE COMPARISON OF SIX EFFICIENT PURE HEURISTICS FOR SCHEDULING META-TASKS ON HETEROGENEOUS DISTRIBUTED ENVIRONMENTS

Scheduling is one of the core steps to e-ciently exploit the capabilities of heterogeneous distributed computing systems and represents an NP-complete problem. Therefore, using meta-heuristic algorithms is a suitable approach in order to cope with its di-culty. In many meta-heuristic algorithms, generating individ- uals in the initial step has an important efiect on the convergence behavior of the algorithm and flnal solutions. Using some pure heuristics for generating one or more near-optimal individuals in the initial step can improve the flnal solutions obtained by meta-heuristic algorithms. Pure heuristics may be used solitary for generating schedules in many real-world situations in which using the meta-heuristic methods are too di-cult or inappropriate. Difierent criteria can be used for evaluating the e-ciency of scheduling algorithms, the most important of which are makespan and ∞owtime. In this paper, we propose an e-cient pure heuristic method and then we compare the performance with flve popular heuristics for minimizing makespan and ∞owtime in heterogeneous distributed computing systems. We investigate the efiect of these pure heuristics for initializing simulated annealing meta-heuristic approach for scheduling tasks on heterogeneous environments.

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