4.7 Article

A Multi-Task Oriented Framework for Mobile Computation Offloading

期刊

IEEE TRANSACTIONS ON CLOUD COMPUTING
卷 10, 期 1, 页码 187-201

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCC.2019.2952346

关键词

Computation offloading; mobile cloud computing; offloading service; multi-task offloading; Lyapunov-optimization

资金

  1. National Natural Science Foundation of China [61772352, 61572323, 61932014]
  2. Science and Technology Planning Project of Sichuan Province [2019YFG0400, 2018GZDZX0031, 2018GZDZX0004, 2017GZDZX0003, 2018JY0182, 19ZDYF1286]

向作者/读者索取更多资源

This study proposes and implements a lightweight computation offloading framework to support offloading of compute-intensive tasks and efficient server deployment. The effectiveness of the framework in reducing energy consumption, boosting performance, and handling intensive offloading requests is demonstrated through experiments and simulations.
Computation offloading has become popular in recent years as it is an effective way to reduce the energy consumption and enhance the performance of smartphones. To deal with the heterogeneous architectures between the smartphone and the server, and to simplify deployment of the server, we propose and implement a lightweight offloading framework which supports offloading of compute-intensive tasks and deploying the server efficiently. Based on this framework, generic and developer-customized offloading services could be provided for different third-party applications. Furthermore, we design a multi-task offloading tactic for the framework to deal with intensive offloading requests from various mobile devices. When receiving an offloading request, the master node in server-side determines whether this task should be offloaded or not and which VM should handle this task, so that the overall execution time and energy consumption are optimized. We implement this framework and evaluate it by comparing the execution time, energy consumption and CPU utilization rate among three execution modes with three applications. We also conduct experiments of the multi-task offloading tactic in simulation environment. Experimental results indicate that this framework effectively reduces energy consumption and boosts performance for compute-intensive tasks, and the multi-task offloading tactic is valid for intensive offloading requests.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据