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Prediction-Based Dynamic Load-Sharing Heuristics
June 1993 (vol. 4 no. 6)
pp. 638-648

Presents dynamic load-sharing heuristics that use predicted resource requirements ofprocesses to manage workloads in a distributed system. A previously developed statisticalpattern-recognition method is employed for resource prediction. Whilenonprediction-based heuristics depend on a rapidly changing system status, the newheuristics depend on slowly changing program resource usage patterns. Furthermore,prediction-based heuristics can be more effective since they use future requirementsrather than just the current system state. Four prediction-based heuristics, twocentralized and two distributed, are presented. Using trace driven simulations, they arecompared against random scheduling and two effective nonprediction based heuristics.Results show that the prediction-based centralized heuristics achieve up to 30% betterresponse times than the nonprediction centralized heuristic, and that theprediction-based distributed heuristics achieve up to 50% improvements relative to theirnonpredictive counterpart.

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Index Terms:
Index Termsload-sharing; predicted resource requirements; distributed system; resource prediction;trace driven simulations; distributed processing; pattern recognition
Citation:
K.K. Goswami, M. Devarakonda, R.K. Iyer, "Prediction-Based Dynamic Load-Sharing Heuristics," IEEE Transactions on Parallel and Distributed Systems, vol. 4, no. 6, pp. 638-648, June 1993, doi:10.1109/71.242159
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