Influence of Inaccurate Performance Prediction on Task Scheduling in a Grid Environment

Yuanyuan ZHANG  Yasushi INOGUCHI  

IEICE TRANSACTIONS on Information and Systems   Vol.E89-D   No.2   pp.479-486
Publication Date: 2006/02/01
Online ISSN: 1745-1361
DOI: 10.1093/ietisy/e89-d.2.479
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Section on Parallel/Distributed Computing and Networking)
Category: Performance Evaluation
grid computing,  task scheduling,  performance prediction,  task selection,  processor selection,  

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Efficient task scheduling is critical for achieving high performance in grid computing systems. Existing task scheduling algorithms for grid environments usually assume that the performance prediction for both tasks and resources is perfectly accurate. In practice, however, it is very difficult to achieve such an accurate prediction in a heterogeneous and dynamic grid environment. Therefore, the performance of a task scheduling algorithm may be significantly influenced by prediction inaccuracy. In this paper, we study the influence of inaccurate predictions on task scheduling in the contexts of task selection and processor selection, which are two critical phases in task scheduling algorithms. We develop formulas for the misprediction degree, which is defined as the probability that the predicted values for the performances of tasks and processors reveal different orders from their real values. Based on these formulas, we also investigate the effect of several key parameters on the misprediction degree. Finally, we conduct extensive simulation for the sensitivities of some existing task scheduling algorithms to the prediction errors.