Dynamic task scheduling for irregular network topologies

In this study, a heterogeneous computing environment is employed as a computational platform. In order to increase the efficiency of the system, a dynamic task-scheduling algorithm is proposed, which balances the load among the nodes of the system. The technique is dynamic, nonpreemptive, adaptive, and it uses a mixed centralised and decentralised policies. Based on the divide and conquer principle, the algorithm models the system as hypergrids and then balances the load among them. Recursively, the hypergrids of dimension k are divided into grids of dimensions k-1, until the dimension is 1. Then, all the nodes of the system are almost equally loaded. The optimum dimension of the hypergrid is chosen in order to achieve the best performance. The simulation results demonstrate the effectiveness of this technique. In addition, we determined the critical points representing lower bounds for which the algorithm should be effective and therefore should be triggered.

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