FUNOff: Offloading Applications at Function Granularity for Mobile Edge Computing

被引:1
作者
Chen, Xing [1 ]
Li, Ming [1 ]
Zhong, Hao [2 ]
Chen, Xiaona [1 ]
Ma, Yun [3 ]
Hsu, Ching-Hsien [4 ]
机构
[1] Fuzhou Univ, Coll Comp & Data Sci, Fujian Prov Key Lab Network Comp & Intelligent Inf, Fuzhou 350118, Peoples R China
[2] Shanghai Jiao Tong Univ, Dept Comp Sci & Engn, Shanghai 200240, Peoples R China
[3] Peking Univ, Sch Elect Engn & Comp Sci, Beijing 100871, Peoples R China
[4] Asia Univ, Dept Comp Sci & Informat Engn, Taichung 413, Taiwan
基金
中国国家自然科学基金;
关键词
Mobile edge computing; computation offloading; code analysis; object-oriented application; software adaptation; CLOUD; ALLOCATION; ALGORITHM; SYSTEM;
D O I
10.1109/TMC.2023.3240741
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Mobile edge computing (MEC) offers a promising technology that deploys computing resources closer to mobile devices for improving performance. Most of the existing studies support on-demand remote execution of the computing tasks in applications through program transformation, but they commonly assume that mobile devices merely resort to a single server for computation offloading, which cannot make full use of the scattered and changeable computing resources. Thus, for object-oriented applications, we propose a novel approach, called FUNOff, to support the dynamic offloading of applications in MEC at the function granularity. First, we extract a call tree via code analysis and locate the function invocations that are suitable for offloading. Next, we refactor the code of related object functions according to a specific program structure. Finally, we make offloading decisions referring to the context at runtime and send function invocations to multiple remote servers for execution. We evaluate the proposed FUNOff on two real-world applications. The results show that, compared with other approaches, FUNOff better supports the computation offloading of object-oriented applications in MEC, which reduces the response time by 10.7%-58.2%.
引用
收藏
页码:1717 / 1734
页数:18
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