Energy-efficient computation offloading strategy for the terminal in mobile cloud environment

被引:0
|
作者
Zhang W. [1 ]
Cao B. [2 ]
Zhou X. [1 ]
机构
[1] School of Information and Control Engineering, Xi'an Univ. of Architecture and Technology, Xi'an
[2] School of Telecommunications Engineering, Xidian Univ., Xi'an
来源
| 1600年 / Science Press卷 / 44期
关键词
Computation offloading; Minimizing energy consumption; Mobile cloud; Smart mobile terminal;
D O I
10.3969/j.issn.1001-2400.2017.03.030
中图分类号
学科分类号
摘要
As the popularity of smart mobile terminals increase in recent years, mobile applications are becoming more diverse and complex These applications require large amounts of computing resources and energy. Therefore, there is an urgent need for new technologies capable of improving the computing performance and battery life of mobile terminals. Orienting to LTE, an energy efficient computation offloading strategy for mobile terminals is proposed which can be used in mobile cloud environment. By taking the transmitting power and CPU speed as constraints, the strategy analyzes requirements of an application program, the mobile terminal's computing power and the status of fading channel; afterwards it optimizes the transmitting power and CPU computing resources sensibly. It can minimize the mobile terminal's energy consumption by implementing reasonable computation offloading. Simulation results show that the proposed strategy can save a mobile terminal's energy consumption, and it does not bring obvious additional delay simultaneously. © 2017, The Editorial Board of Journal of Xidian University. All right reserved.
引用
收藏
页码:175 / 180
页数:5
相关论文
共 10 条
  • [1] Aijaz A., Aghvami H., Amani M., A Survey on Mobile Data Offloading: Technical and Business Perspectives, IEEE Wireless Communications, 20, 2, pp. 104-112, (2013)
  • [2] Flores H., Hui P., Tarkoma S., Et al., Mobile Code Offloading: from Concept to Practice and Beyond, IEEE Communications Magazine, 53, 3, pp. 80-88, (2015)
  • [3] Zhang W., Guo B., Shen Y., Et al., Comtutation Offloading on Intelligent Mobile Terminals, Chinese Journal of Computers, 39, 5, pp. 1021-1038, (2016)
  • [4] Segata M., Bloessl B., Sommer C., Et al., Towards Energy Efficient Smart Phone Applications: Energy Models for Offloading Tasks Into the Cloud, Proceedings of the 2014 IEEE International Conference on Communications, pp. 2394-2399, (2014)
  • [5] Barbera M.V., Kosta S., Mei A., Et al., To Offload or Not to Offload? the Bandwidth and Energy Costs of Mobile Cloud Computing, Proceedings of the 2013 IEEE INFOCOM, pp. 1285-1293, (2013)
  • [6] Lee K., Shin I., User Mobility-aware Decision Making for Mobile Computation Offloading, Proceedings of the 2013 IEEE 1st International Conference on Cyber-physical Systems, Networks, and Applications, pp. 116-119, (2013)
  • [7] Wen Y., Zhang W., Luo H., Energy-optimal Mobile Application Execution: Taming Resource-poor Mobile Devices with Cloud Clones, Proceedings of the 2012 IEEE INFOCOM, pp. 2716-2720, (2012)
  • [8] Mohan L., Mathur N., Reddy Y.R., Mobile App Usability Index (MAUI) for Improving Mobile Banking Adoption, Proceedings of the 10th International Conference on Evaluation of Novel Approaches to Software Engineering, pp. 313-320, (2015)
  • [9] Polyanskiy Y., Poor H.V., Verdu S., Channel Coding Rate in the Finite Blocklength Regime, IEEE Transactions on Information Theory, 56, 5, pp. 2307-2359, (2010)
  • [10] Jensen A.R., Lauridsen M., Mogensen P., Et al., LTE UE Power Consumption Model: for System Level Energy and Performance Optimization, Proceedings of the IEEE Vehicular Technology Conference, pp. 1-5, (2012)