An efficient green control algorithm in cloud computing for cost optimization
Cloud computing is a new paradigm for delivering remote computing resources through a
network. However, achieving an energy-efficiency control and simultaneously satisfying a
performance guarantee have become critical issues for cloud providers. In this paper, three
power-saving policies are implemented in cloud systems to mitigate server idle power. The
challenges of controlling service rates and applying the N-policy to optimize operational cost
within a performance guarantee are first studied. A cost function has been developed in …
network. However, achieving an energy-efficiency control and simultaneously satisfying a
performance guarantee have become critical issues for cloud providers. In this paper, three
power-saving policies are implemented in cloud systems to mitigate server idle power. The
challenges of controlling service rates and applying the N-policy to optimize operational cost
within a performance guarantee are first studied. A cost function has been developed in …
Cloud computing is a new paradigm for delivering remote computing resources through a network. However, achieving an energy-efficiency control and simultaneously satisfying a performance guarantee have become critical issues for cloud providers. In this paper, three power-saving policies are implemented in cloud systems to mitigate server idle power. The challenges of controlling service rates and applying the N-policy to optimize operational cost within a performance guarantee are first studied. A cost function has been developed in which the costs of power consumption, system congestion and server startup are all taken into consideration. The effect of energy-efficiency controls on response times, operating modes and incurred costs are all demonstrated. Our objectives are to find the optimal service rate and mode-switching restriction, so as to minimize cost within a response time guarantee under varying arrival rates. An efficient green control (EGC) algorithm is first proposed for solving constrained optimization problems and making costs/performances tradeoffs in systems with different power-saving policies. Simulation results show that the benefits of reducing operational costs and improving response times can be verified by applying the power-saving policies combined with the proposed algorithm as compared to a typical system under a same performance guarantee.
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