Grid resource management
Journal of Parallel and Distributed Computing
Journal of Parallel and Distributed Computing
Resource allocation strategies for the economic computational grid
International Journal of Networking and Virtual Organisations
Decentralized management of bi-modal network resources in a distributed stream processing platform
Journal of Parallel and Distributed Computing
Leveraging public resource pools to improve the service compliances of computing utilities
HiPC'04 Proceedings of the 11th international conference on High Performance Computing
Evaluating economic-based entity strategies for the computational grid
International Journal of Business Information Systems
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Cycle-harvesting is a significant part of the Grid computing landscape. However, creating commercial servicecontracts based on resources made available by cycle-harvesting is a significant challenge: the characteristics ofthe harvested resources are inherently stochastic; and secondly, in a commercial environment, purchasers can expectproviders to optimize against the quality of service (QoS)definitions. The essential point for creating commerc allyvaluable QoS definitions is to guarantee a set of statisticalparameters for each contract instance. Here we describean appropriate QoS definition, Hard Statistical QoS (HSQ),and show how this can be implemented using a hybridstochastic-deterministic system. We analyze algorithm behavior analytically using a distribution-free approach versus the expected proportion of deterministic resources required for an HSQ specification. We conclude that commercial service contracts based on cycle-harvested resourcesare viable both from a conceptual point of view and quantitatively.