计算机科学
计算卸载
能源消耗
任务(项目管理)
软件部署
服务器
移动设备
分布式计算
云计算
节点(物理)
嵌入式系统
计算机网络
操作系统
边缘计算
生态学
管理
结构工程
工程类
经济
生物
作者
Junyu Lu,Qiang Li,Bing Guo,Jie Li,Shen Yan,Gongliang Li,Hong Su
标识
DOI:10.1109/tcc.2019.2952346
摘要
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.
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