面向物联网的边云协同实体搜索方法

doi:10.19678/j.issn.1000-3428.0055501

计算机工程 ›› 2020, Vol. 46 ›› Issue (8): 43-49. doi: 10.19678/j.issn.1000-3428.0055501

面向物联网的边云协同实体搜索方法

王汝言^1,2,3, 刘宇哲^1,2,3, 张普宁^1,2,3, 亢旭源^1,2,3, 李学芳^1,2,3

1. 重庆邮电大学通信与信息工程学院, 重庆 400065;
2. 重庆高校市级光通信与网络重点实验室, 重庆 400065;
3. 泛在感知与互联重庆市重点实验室, 重庆 400065

收稿日期:2019-07-16 修回日期:2019-09-12 发布日期:2019-09-27
作者简介:王汝言(1969-),男,教授、博士,主研方向为泛在网络、多媒体信息处理;刘宇哲(通信作者),硕士研究生;张普宁,讲师、博士;亢旭源、李学芳,硕士研究生。
基金资助:
国家自然科学基金（61871062，61901071）；重庆市高校创新团队建设计划（CXTDX201601020）；重庆市自然科学基金面上项目（cstc2019jcyj-msxm1238）；重庆市教委科学技术研究项目（KJQN201800615）；第五批重庆市高校优秀人才支持计划（渝教人发[2017]29号）。

Edge and Cloud Collaborative Entity Search Method for Internet of Things

WANG Ruyan^1,2,3, LIU Yuzhe^1,2,3, ZHANG Puning^1,2,3, KANG Xuyuan^1,2,3, LI Xuefang^1,2,3

1. School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China;
2. Chongqing Key Laboratory of Optical Communication and Network, Chongqing 400065, China;
3. Chongqing Key Laboratory of Ubiquitous Sensing and Networking, Chongqing 400065, China

Received:2019-07-16 Revised:2019-09-12 Published:2019-09-27

摘要/Abstract

摘要： 针对物联网搜索的高实时性要求及物理实体的强时变性特点，提出面向物联网的边云协同实体搜索方法。结合云计算与边缘计算各自的优势，构建边云协同实体搜索系统架构，提高物联网实体的搜索效率。考虑到嵌入物理实体的传感器通信能力有限，设计基于深度信念网络的实体识别算法，通过将热门与冷门实体状态信息分别存储于边缘服务器与云端，节省边缘服务器的存储空间与计算开销。仿真结果表明，与云端数据共享搜索方法SeDaSC和层次化搜索方法LHPM相比，该方法提高了实体状态信息搜索的实时性与准确性。

关键词: 物联网搜索, 边缘计算, 实体识别, 实体搜索, 边云协同

Abstract: To address high demands for real-time performance of search of Internet of Things(IoT) entities and the time-varying feature of physical entities,this paper proposes an Edge and Cloud Collaborative Entity Search Method(ECCS) for IoT.The method takes advantages of edge computing and cloud computing to construct entity search system architecture based on edge and cloud collaboration,so as to improve the search efficiency of IoT entities.Furthermore,to address limited communication capabilities of sensors of embedded physical entities,an entity identification algorithm based on Deep Belief Network(DBN) is proposed,which stores the status information of popular entities and unpopular entities respectively on the edge server and cloud to reduce the storage and computing cost of the edge server.Simulation results demonstrate that the proposed method can effectively improve the real-time performance and accuracy of search of entity status information compared with the cloud data sharing search method(SeDaSC) and the hierarchical search method(LHPM).

Key words: Internet of Things(IoT) search, edge computing, entity identification, entity search, edge and cloud collaboration

中图分类号:

TP393

王汝言, 刘宇哲, 张普宁, 亢旭源, 李学芳. 面向物联网的边云协同实体搜索方法[J]. 计算机工程, 2020, 46(8): 43-49.

WANG Ruyan, LIU Yuzhe, ZHANG Puning, KANG Xuyuan, LI Xuefang. Edge and Cloud Collaborative Entity Search Method for Internet of Things[J]. Computer Engineering, 2020, 46(8): 43-49.

http://www.ecice06.com/CN/Y2020/V46/I8/43

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