2012 · 83 citations · 20 references
ComputingCloud ComputingCloud Performance OptimizationEnergy ManagementQueuing TheoryCloud Resource ManagementEnergy StorageEnergy Storage IntegrationResource SchedulingWorkload PlacementWorkload SchedulingCloud Computing SystemsCloud Data CentersData Center Energy OptimizationEnergy Cost OptimizationGeneratorsReal-time MonitoringWorkloadWorkload Flexibility
Because of their intermittency and inter-temporal variations, the integration of renewable energy resources is usually very challenging. Some of the previously proposed solutions, such as the use of energy storage units and fast-responding generators, are costly and may not be desirable in practice. Instead, in this paper, we argue that due to the workload flexibility in the Internet and Cloud Computing data centers they can offer a unique opportunity to tackle the challenges in integrating renewable energy resources. Moreover, by running data centers with behind-the-meter renewable generators, we can significantly reduce not only data centers' energy cost but also their Carbon Footprint. To achieve these objectives, we propose to optimally distribute the workload among geographically dispersed data centers such that we can benefit from the location diversity of different types of available renewable energy resources. The quality-of-service is guaranteed by real-time monitoring of the queue lengths and effectively stabilizing short queue lengths in each data center. Simulation results, based on various experimental data, show that the proposed design can significantly reduce data centers' cost of electricity while maintaining quality-of-service.
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