A Data Transmission Strategy with Energy Minimization Based on Optimal Stopping Theory in Mobile Cloud Computing

Xin Zheng,Gang Zheng,Yuting Lu,Yu Nan,Fangsu Wang,Ruiqing Song,Gaocai Wang,Qifei Zhao

doi:10.1155/2019/1257150

Abstract

Considering the widespread use of mobile devices and the increased performance requirements of mobile users, shifting the complex computing and storage requirements of mobile terminals to the cloud is an effective way to solve the limitation of mobile terminals, which has led to the rapid development of mobile cloud computing. How to reduce and balance the energy consumption of mobile terminals and clouds in data transmission, as well as improve energy efficiency and user experience, is one of the problems that green cloud computing needs to solve. This paper focuses on energy optimization in the data transmission process of mobile cloud computing. Considering that the data generation rate is variable, because of the instability of the wireless connection, combined with the transmission delay requirement, a strategy based on the optimal stopping theory to minimize the average transmission energy of the unit data is proposed. By constructing a data transmission queue model with multiple applications, an admission rule that is superior to the top candidates is proposed by using secretary problem of selecting candidates with the lowest average absolute ranking. Then, it is proved that the rule has the best candidate. Finally, experimental results show that the proposed optimization strategy has lower average energy per unit of data, higher energy efficiency, and better average scheduling period.

Highlights

When the transmission power of the mobile terminal is given, in order to cope with the randomness and unpredictability of the wireless connection, the mobile terminal selects a channel with good quality, that is, the transmission rate is large to transmit data, which is beneficial to reducing the average energy consumption of the transmission data
When the channel state changes randomly, the mobile terminal selects a better time to transmit data according to the temporary channel condition information, which is a distributed opportunistic scheduling problem [11]. e distributed opportunistic scheduling problem can be solved by the optimal stopping theory [12, 13]
Is paper proposes an optimal transmission strategy based on secretary problem (OTSSP) of optimal stopping theory: following the rule that it is better than the top k candidates

Summary

Theoretical Background and Problem Description

E research goal of this paper is to optimize the energy consumption generated by mobile terminals transmitting data to the cloud in MCC under the condition of satisfying transmission delay. Q(mt) is a queue in which application m needs to transmit data with the cloud at the beginning of time slot t. Erefore, the above queue model describes time-varying and unpredictable data transmission between mobile terminals and the cloud. When the mobile terminal selects a transmission time with a large transmission rate, the amount of transmission data in the transmission delay can be increased, and the average energy consumption of the transmission unit data. At is, k candidates in the first round interview would not be hired; starting with the k + 1 th candidate, if he is better than the top k candidates, the candidate will be hired; otherwise, the one will be interviewed until the last one

Data Transmission Energy Consumption Optimization Strategy

Simulation Results and Analysis

Conclusions and Further Work