物联网中多设备多服务器的移动边缘计算任务卸载技术综述  

Survey on Task Offloading Techniques for Mobile Edge Computing with Multi-devices and Multi-servers in Internet of Things

作　　者：梁俊斌[1,2] 田凤森 蒋婵 王天舒[4] LIANG Jun-bin;TIAN Feng-sen;JIANG Chan;WANG Tian-shu(School of Computer and Electronic Information,Guangxi University,Nanning 530004,China;Guangxi Key Laboratory of Multimedia Communication and Network Technology,Nanning 530004,China;Guangxi University Xingjian College of Science and Liberal Arts,Nanning 530005,China;Neusoft Group(Nanning)Co.,Ltd.,Nanning 530007,China)

机构地区：[1]广西大学计算机与电子信息学院,南宁530004 [2]广西多媒体通信与网络技术重点实验室,南宁530004 [3]广西大学行健文理学院,南宁530005 [4]东软集团(南宁)有限公司,南宁530007

出　　处：《计算机科学》2021年第1期16-25,共10页Computer Science

基　　金：国家自然科学基金项目(61562005);广西重点研发计划项目(桂科AB19259006);广西自然科学基金项目(2019GXNSFAA185042,2018GXNSFBA281169)。

摘　　要：随着物联网(Internet of Things,IoT)技术的快速发展,出现了大量具有不同功能的设备(如多种带不同传感器的智能家居设备、移动智能交通设备、智能物流或仓储管理设备等),它们相互连接,被广泛应用于智能城市、智慧工厂等领域。然而,这些物联网设备的处理能力有限,很难满足延迟敏感、计算密集型应用的需求。移动边缘计算(Mobile Edge Computing,MEC)的出现有效解决了这一问题。物联网设备可以将任务卸载到MEC服务器上,借助它们完成相应的计算任务。这些服务器通常由网络运营商部署在网络边缘,即靠近用户端的网络接入层,用于汇聚用户网络的网络层面。某一段时间内,物联网设备可能处于多个MEC服务器的覆盖区域中,多个设备共享服务器有限的计算和通信资源。在这个复杂环境下,制定一个任务卸载和资源分配方案,使得任务完成的时延或物联网设备的能耗达到最优化,是一个NP-难问题。目前,已有许多工作对这一问题进行了研究,并取得了一定的成果,但在实际的应用中仍面临着一些问题。为了更深入地推进该领域的研究,文中对近几年的最新研究成果进行了分析、归纳和总结,对比分析了它们的优缺点,并对未来的工作进行了展望。With the rapid development of the Internet of Things(IoT)technology,there are a large number of devices with different functions(such as a variety of smart home equipment,mobile intelligent transportation devices,intelligent logistics or warehouse management equipment,etc.,with different sensors),which are connected to each other and widely used in intelligent cities,smart factories and other fields.However,the limited processing power of these IoT devices makes it difficult to meet the demand for delay-sensitive,computation-intensive applications.The emergence of mobile edge computing(MEC)effectively solves this problem.IoT devices can offload tasks to edge servers and use them to perform computing tasks.These servers are usually deployed by the network operator at the edge of the network,that is,the network access layer close to the client,which is used to aggregate the user network.At a certain time,IoT devices may be in the coverage area of multiple edge servers,and they share the limited computing and communication resources of the servers.In this complex environment,it is an NP-hard problem to formulate a task offloading and resource allocation scheme to optimize the delay of task completion or the energy consumption of IoT devices.At present,lots of work has been done on this issue and make some progress,but some problems still exist in the practical application.In order to further promote the research in this field,this paper analyzes and summarizes the latest achievements in recent years,compares their advantages and disadvantages,and looks forward to the future work.

关 键 词：物联网 移动边缘计算 任务卸载 资源分配 卸载决策 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]