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Cloud computing clusters distributed computers to provide applications as services and on-demand resources over Internet. From the perspective of average and total energy consumption, such consolidated resource enhances the energy efficiency on both clients and servers. However, cloud computing has a different power consumption pattern from the traditional storage oriented Internet services. The computation oriented implementation of cloud service broadens the gap between the peak power demand and base power demand of a data center. A higher peak demand implies the need of feeder capacity expansion, which requires a considerable investment. This study proposes a computation related approach to lessen the increasing power demand of cloud service data centers. Through appropriated designs, some frequently used computing algorithms can be performed by either clients or servers. As a model presented in this paper, such client-server balanced computation resource integration suggests an energy-efficient and cost-effective cloud service data center.

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Cloud computing refers to clusters of distributed computers that provide applications as services and on-demand resources over Internet. Theoretically, such consolidated resource enhances the energy efficiency of both clients and servers. However, this paper presents that cloud computing is a panacea for enhancing energy efficiency only under some certain conditions. The computing resources of cloud computing are located at remote machines. With current technologies, a quick way to construct cloud computing architecture is to use web pages as service interface via HTTP protocol. Pioneers in exploring cloud computing, such as Google, AmazonWeb, Microsoft Azure, Yahoo, and IBM all take this approach. Through appropriated designs, sorting, one of the most frequently used algorithms, required by a web page is able to be executed and succeed by either clients or servers. This paper constructs and validates a generalized model that suggests an energy-efficient sorting process for a web page.