发布时间：2017-11-28

文章标题：课题组关于边缘计算的综述文章被SCI期刊IEEE ACCESS接收

内容：

 课题组文章"A Survey on the Edge Computing for the Internet of Things" 作者Yu W, Liang F, He XF, Hatcher. G.W., Lu C, Lin J, Yang XY. 被被SCI期刊IEEE ACCESS接收。

文章摘要：The Internet of Things (IoT) now permeates our daily lives, providing important measurement and collection tools to inform our every decision. Millions of sensors and devices are continuously producing data and exchanging important messages via self-organizing machine-to-machine (M2M) networks. However, the unfettered increase in devices and communication, in generating massive data of unprecedented scale, will consume significant bandwidth and network resources, especially in the context of the traditional cloud computing structure. As a result, delay in exchanging messages will be prodigious and pervasive, and QoS for IoT applications will be impossible to satisfy. As a strategy to mitigate the escalation in resource congestion, edge computing has emerged as a new strategy to solve IoT and localized computing needs. Compared with the well-known cloud computing, edge computing will migrate data computation or storage to the network ``edge'', near the end users. Thus, many computation nodes distributed across the network can offload the computational stress away from the centralized data center, and can significantly reduce the latency in message exchange. In addition, the distributed structure can balance network traffic and avoid the traffic peaks in IoT networks, reducing the transmission latency between edge/cloudlet servers and end users, reducing response times for real-time IoT applications in comparison with traditional cloud services. Furthermore, by transferring computation and communication overhead from nodes with limited battery supply to nodes with significant power resources, the system can extend the lifetime of the individual nodes. In this paper, we offer a comprehensive survey, analyzing how edge computing improves the performance of an IoT networks. We categorize edge computing into different groups based on architecture, and analyze their performance by comparing network latency, bandwidth occupation, energy consumption, and overhead. Also, we consider security issues in edge computing, evaluating the availability, integrity, and confidentiality of security strategies of each group, and propose a framework for security evaluation of IoT networks with edge computing. Finally, we compare the performance of various IoT applications (Smart City, Smart Grid, Smart Transportation, etc.) in edge computing and traditional cloud computing architectures.