[1] Muharum A M, Joyejob V T, Hurbungs V, et al. Enersave API:android-based power saving fram-ework for mobile devices[J]. Future Computing and Informatics Journal, 2017, 2(1):48-64.
[2] Eom B, Lee C, Lee H, et al. An adaptive remote display scheme to deliver mobile cloud services[J]. IEEE Transactions on Consumer Electronics, 2014, 60(3):540-547.
[3] Mazza D, Tarchi D, Corazza G E. A partial offloading technique for wireless mobile cloud computing in smart cities[C]//European Conference on Networks and Communications.[S. l.]:IEEE, 2014:1-5.
[4] Gu X, Messer A, Greenberg I, et al. Adaptive off-loading for pervasive computing[J]. IEEE Pervasive Computing, 2015, 3(3):66-73.
[5] 殷波, 王颖, 孟洛明, 等. 综合迁移成本和通信成本的云计算节能策略[J]. 北京邮电大学学报, 2012(1):68-71. Yin B, Wang Y, Meng L M, et al. A new virtual machine migration strategy based on migration cost and communication cost for power saving in cloud[J]. Journal of Beijing University of Posts and Telecommunications, 2012(1):67-71.
[6] 王安. 面向节能的移动网络传输关键技术研究[D]. 北京:北京邮电大学, 2013.
[7] 徐九韵, 管超, 杨丹, 等. 一种基于协同过滤与BG/NBD模型数据预测的智能手机节能策略[J]. 计算机集成制造系统, 2017, 23(5):1139-1146. Xu J Y, Guan C, Yang D, et al. Smartphone energy-efficiency strategy based on collaborative filtering and BG/NBD model[J]. Computer Integrated Manufacturing Systems, 2017, 23(5):1139-1146.
[8] Liu Fangming, Shu Peng. AppATP:an energy conserving adaptive mobile-cloud transmission Protocol[J]. IEEE Transactions on Computers, 2015, 64(11):3051-3063. |