文献类型：期刊文献

英文题名：A multi-stage heuristic method for service caching and task offloading to improve the cooperation between edge and cloud computing

作者：Chen, Xiaoqian[1];Gao, Tieliang[2];Gao, Hui[1];Liu, Baoju[3];Chen, Ming[4];Wang, Bo[4]

第一作者：陈晓前

通讯作者：Gao, TL[1];Wang, B[2]

机构：[1]Xinxiang Univ, Management Ctr Informatizat, Xinxiang, Henan, Peoples R China;[2]Xinxiang Univ, Key Lab Data Anal & Financial Risk Predict, Xinxiang, Henan, Peoples R China;[3]Pingdingshan Univ, Sch Informat Engn, Pingdingshan, Peoples R China;[4]Zhengzhou Univ Light Ind, Software Engn Coll, Zhengzhou, Peoples R China

第一机构：新乡学院

通讯机构：[1]corresponding author), Xinxiang Univ, Key Lab Data Anal & Financial Risk Predict, Xinxiang, Henan, Peoples R China;[2]corresponding author), Zhengzhou Univ Light Ind, Software Engn Coll, Zhengzhou, Peoples R China.|[11071]新乡学院;

年份：2022

卷号：8

外文期刊名：PEERJ COMPUTER SCIENCE

收录：;EI(收录号：20223012398888);Scopus(收录号：2-s2.0-85134535580);WOS:【SCI-EXPANDED(收录号:WOS:000821564200001)】；

基金：The research was supported by the Key Scientific and Technological Projects of Henan Province (Grant No. 222102210218, 202102210174, 212102210096, 212102210104), the Key Scientific Research Projects of Henan Higher School (Grant No. 20B520039, 21A520050), the National Natural Science Foundation of China (Grant No. 61902021, 61872043, 61975187, 62072414), the Doctoral Fund of Pingdingshan University (No. PXY-BSQD-2022004), the Qin Xin Talents Cultivation Program, Beijing Information Science and Technology University (No. QXTCP B201904), and the fund of the Beijing Key Laboratory of Internet Culture and Digital Dissemination Research (Grant No. ICDDXN004).

语种：英文

外文关键词：Task offloading; Service caching; Edge cloud; Edge computing

摘要：Edge-cloud computing has attracted increasing attention recently due to its efficiency on providing services for not only delay-sensitive applications but also resourceintensive requests, by combining low-latency edge resources and abundant cloud resources. A carefully designed strategy of service caching and task offloading helps to improve the user satisfaction and the resource efficiency. Thus, in this article, we focus on joint service caching and task offloading problem in edge-cloud computing environments, to improve the cooperation between edge and cloud resources. First, we formulated the problem into a mix-integer nonlinear programming, which is proofed as NP-hard. Then, we proposed a three-stage heuristic method for solving the problem in polynomial time. In the first stages, our method tried to make full use of abundant cloud resources by pre-offloading as many tasks as possible to the cloud. Our method aimed at making full use of low-latency edge resources by offloading remaining tasks and caching corresponding services on edge resources. In the last stage, our method focused on improving the performance of tasks offloaded to the cloud, by re-offloading some tasks from cloud resources to edge resources. The performance of our method was evaluated by extensive simulated experiments. The results show that our method has up to 155%, 56.1%, and 155% better performance in user satisfaction, resource efficiency, and processing efficiency, respectively, compared with several classical and state-of-the-art task scheduling methods.