Abstracts

Load Management for Load Balancing on Heterogeneous Platforms: A Comparison of Traditional and Neural Network Based Approaches

In this paper we compare simple load metrics with neural networks which have been trained to predict the expected delay of an application from the sampled load informations. The results show that the proposed load metric performs well in heterogeneous environments. Further, neural networks can improve the performance of load balancing facilities.

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