Tradeoff between execution speedup and reliability for compute-intensive code offloading in mobile device cloud

被引:0
作者
Sajeeb Saha
Md. Ahsan Habib
Tamal Adhikary
Md. Abdur Razzaque
Md. Mustafizur Rahman
机构
[1] University of Dhaka,Green Networking Research Group, Department of Computer Science and Engineering
来源
Multimedia Systems | 2019年 / 25卷
关键词
Mobile device cloud; Compute-intensive; Code offloading; Execution speedup; Reliability; MILP;
D O I
暂无
中图分类号
学科分类号
摘要
With the advent of different mobile computing technologies, mobile devices have opened up a plethora of computational infrastructure to provide improved performance for compute-intensive applications to the end users. Mobile Device Cloud (MDC) technology brings the code offloading mechanism from distant cloud to neighbor mobile devices. However, the major challenges of code offloading in MDC systems include maximization of computation speedup and reliability; unfortunately, these two performance parameters often oppose each other. In this paper, an optimization framework, namely TESAR, has been devised to tradeoff between application execution speedup and reliability while maintaining device energy within a predefined range. We also provide an algorithm for developing a dependency tree among the modules of an application so as to allow higher number of parallel executions, wherever and whenever it is possible. The emulation results of the proposed algorithm outperform the relevant state-of-the-art works in terms of application completion time, communication latency and rescheduling overhead.
引用
收藏
页码:577 / 589
页数:12
相关论文
共 42 条
[1]  
Huang D(2012)A dynamic offloading algorithm for mobile computing Wirel. Commun. IEEE Trans. 11 1991-1995
[2]  
Wang P(2013)A framework for partitioning and execution of data stream applications in mobile cloud computing ACM SIGMETRICS Perform. Eval. Rev. 40 23-32
[3]  
Niyato D(2015)Just-in-time code offloading for wearable computing Emerg. Topics Comput. IEEE Trans. 3 74-83
[4]  
Yang L(2016)Efficient computation offloading decision in mobile cloud computing over 5g network Mob. Netw. Appl. 21 777-792
[5]  
Cao J(2009)The case for vm-based cloudlets in mobile computing Pervasive Comput. IEEE 8 14-23
[6]  
Yuan Y(2016)Maximizing quality of experience through context-aware mobile application scheduling in cloudlet infrastructure Softw. Pract. Exp. 46 1525-1545
[7]  
Li T(2016)Efficient multi-user computation offloading for mobile-edge cloud computing IEEE/ACM Trans. Netw. 24 2795-2808
[8]  
Han A(2014)Mobility-assisted opportunistic computation offloading Commun. Lett. IEEE 18 1779-1782
[9]  
Chan A(2007)The case for energy-proportional computing Computer 40 33-37
[10]  
Cheng Z(2015)Exploiting mobile crowdsourcing for pervasive cloud services: challenges and solutions IEEE Commun. Mag. 53 98-105