Toward green service in cloud: From the perspective of scheduling

In this paper, we address energy-oriented service in cloud computing environment. Specifically, we consider a generic cloud scenario where different kinds of servers provide multi-class service without knowing the user demand in advance. In general, this work provides a green scheduling in the cloud by explicitly addressing 1) the number of the server for each service, and 2) a dynamic scheduling scheme that specifies how to assign the users to different servers. At first, energy-aware scheduling in cloud is formulated by an optimization problem where QoS constraint is expressed by a probability formulation. Then, we propose a random dynamic scheduling scheme to deal with the demand uncertainty based on Monto-Carlo sampling. Moreover, we show that the proposed scheduling scheme possesses a desirable property since it inherits from the problem of known user demand. Subsequently, we present exact steps to implement the proposed scheduling. Finally, numerical simulation results are provided to validate its efficiency.