Multi-Dimensional QoS Evaluation and Optimization of Mobile Edge Computing for IoT: A Survey

被引:14
作者
Huang, Jiwei [1 ,2 ]
Liu, Fangzheng [1 ,2 ]
Zhang, Jianbing [1 ,2 ]
机构
[1] China Univ Petr, Beijing Key Lab Petr Data Min, Beijing 102249, Peoples R China
[2] China Univ Petr, Dept Comp Sci & Technol, Beijing 102249, Peoples R China
关键词
Internet of things; Mobile edge computing; Quality of service; Quality of service evaluation; Quality of service optimization; PERFORMANCE EVALUATION; RESOURCE-ALLOCATION; SERVICE MIGRATION; DELAY; CLOUD; DEPENDABILITY; MECHANISM; INTERNET; SYSTEM; THINGS;
D O I
10.23919/cje.2023.00.264
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
With the evolvement of the Internet of things (IoT), mobile edge computing (MEC) has emerged as a promising computing paradigm to support IoT data analysis and processing. In MEC for IoT, the differentiated requirements on quality of service (QoS) have been growing rapidly, making QoS a multi-dimensional concept including several attributes, such as performance, dependability, energy efficiency, and economic factors. To guarantee the QoS of IoT applications, theories and techniques of multi-dimensional QoS evaluation and optimization have become important theoretical foundations and supporting technologies for the research and application of MEC for IoT, which have attracted significant attention from both academia and industry. This paper aims to survey the existing studies on multi-dimensional QoS evaluation and optimization of MEC for IoT, and provide insights and guidance for future research in this field. This paper summarizes the multi-dimensional and multi-attribute QoS metrics in IoT scenarios, and then several QoS evaluation methods are presented. For QoS optimization, the main research problems in this field are summarized, and optimization models as well as their corresponding solutions are elaborated. We take notice of the booming of edge intelligence in artificial intelligence-empowered IoT scenarios, and illustrate the new research topics and the state-of-the-art approaches related to QoS evaluation and optimization. We discuss the challenges and future research directions.
引用
收藏
页码:859 / 874
页数:16
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