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• W1512394060 abstract "We present scalable QoS optimization algorithms for allocating resources to tasks in a multi-processor environment. Given a set of tasks, each of which is capable of running at one of several different QoS levels, the algorithms can select a QoS operating point, the number of replicas for fault-tolerance and the processors on which to run the replicas so as to maximize overall system QoS. The algorithms are extensions of Q-RAM (QoS-based Resource Allocation Model) [5] and fix two deficiencies with the basic algorithm. The first is that the existing algorithm is weak in making resource trade-off decisions such as to which processor to map a task. The second was that it was not scalable to very large numbers of resources such as in a large multi-processor system. In this paper we present two new algorithms which significantly enhance the ability of Q-RAM to make resource tradeoff decisions. We also introduce a hierarchical decomposition scheme which enables QoS optimization to be performed on problems with thousands of resources and thousands of tasks." @default.
• W1512394060 created "2016-06-24" @default.
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• W1512394060 date "2004-06-22" @default.
• W1512394060 modified "2023-09-23" @default.
• W1512394060 title "Scalable resource allocation for multi-processor QoS optimization" @default.
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• W1512394060 doi "https://doi.org/10.1109/icdcs.2003.1203464" @default.
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