Study on Energy Minimization Data Transmission Strategy in Mobile Cloud Computing

Abstract

With the rapid expansion of mobile cloud computing and its wide appliance, as well as the improvement of user's performance requirements for mobile terminals, it is an inevitable trend for mobile cloud computing to shift the complex computing and storage requirements of mobile terminals to the cloud for processing. Therefore, it is one of the problems to be solved in the green cloud computing that how to reduce the energy consumption of the mobile terminal and the cloud and how to improve the energy efficiency and the user experience during the data transmission process. In this paper, we focus on energy optimization in the data transfer process of mobile cloud computing. Based on the optimal stopping theory, an average transmission energy strategy for minimizing unit data is proposed with a given data generated rate and transmission delay. We construct a data transmission queue model with multiple application scenarios. Based on the secretarial problem of minimizing the average absolute ranking of candidates, an admission rule that is superior to the top k candidates is proposed to minimize the average energy consumption of unit data. Indeed, the rule has been proved that it has the best K. value. The experimental results show that the optimization strategy proposed in this paper has lower average energy per unit of data, more excellent energy efficiency, and better detection efficiency.