Adaptive Application Offloading Decision and Transmission Scheduling for Mobile Cloud Computing

作     者：Junyi Wang Jie Peng Yanheng Wei Didi Liu Jielin Fu 

作者机构：Guangxi Key Lab of Wireless Wideband Communication & Signal Processing Guilin 541004 China Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai 200000 China School of Telecommunication Engineering Xi'an University Xi'an 710049 China Sci. and Tech. on Info. Transmission and Dissemination in Communication Networks Lab. Shijiazhuang 050000 China 

出 版 物：《China Communications》 (中国通信（英文版）)

年 卷 期：2017年第14卷第3期

页      面：169-181页

核心收录：

学科分类：0810[工学-信息与通信工程] 080904[工学-电磁场与微波技术] 0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 0839[工学-网络空间安全] 08[工学] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 081001[工学-通信与信息系统] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by National Natural Science Foundation of China (Grant No.61261017, No.61571143 and No.61561014) Guangxi Natural Science Foundation (2013GXNSFAA019334 and 2014GXNSFAA118387) Key Laboratory of Cognitive Radio and Information Processing, Ministry of Education (No.CRKL150112) Guangxi Key Lab of Wireless Wideband Communication & Signal Processing (GXKL0614202, GXKL0614101 and GXKL061501) Sci.and Tech.on Info.Transmission and Dissemination in Communication Networks Lab (No.ITD-U14008/KX142600015) Graduate Student Research Innovation Project of Guilin University of Electronic Technology (YJCXS201523) 

主　　题：mobile cloud computing application offloading decision transmission scheduling scheme Lyapunov optimization 

摘      要：Offloading application to cloud can augment mobile devices computation capabilities for the emerging resource-hungry mobile application, however it can also consume both much time and energy for mobile device offloading application remotely to cloud. In this paper, we develop a newly adaptive application offloading decision-transmission scheduling scheme which can solve above problem efficiently. Specifically, we first propose an adaptive application offloading model which allows multiple target clouds coexisting. Second, based on Lyapunov optimization theory, a low complexity adaptive offloading decision-transmission scheduling scheme has been proposed. And the performance analysis is also given. Finally, simulation results show that,compared with that all applications are executed locally, mobile device can save 68.557% average execution time and 67.095% average energy consumption under situations.