A Novel Cost Optimization Method for Mobile Cloud Computing by Capacity Planning of Green Data Center With Dynamic Pricing

Abstract

Due to the large volume of data, high processing time, and power consumption, operators are looking for ways to reduce the energy consumption and subsequently optimize the energy consumption of data centers. Appropriate pricing of services and control of user demands along with considering renewable energy in the data center lead to a reduction in energy consumption of both users and data centers. The proposed methods for simultaneous reduction in the cost of energy consumption and an increase in the number of processed demands in data centers are not very practical. This paper proposed the capacity planning with dynamic pricing algorithm considering different factors in energy consumption reduction in green data centers of the fourth/fifth generation of mobile system networks delivering mobile cloud computing services. The proposed algorithm determines the optimal number of servers and addresses the tradeoff between the cost of operation and the delay of services. A penalty function for cost was derived and various scenarios were designed and different qualities of services were considered using the Lyapunov optimization to set up the simulation environment. The provided results illustrate the efficiency of the proposed scheme and validate the mathematical model.