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物联网搜索技术综述
引用本文:高云全,李小勇,方滨兴.物联网搜索技术综述[J].通信学报,2015,36(12):57-76.
作者姓名:高云全  李小勇  方滨兴
作者单位:1. 北京邮电大学 可信分布式计算与服务教育部重点实验室,北京 100876; 2. 安徽工业大学 计算机科学与技术学院,安徽 马鞍山 243032
基金项目:国家自然科学基金资助项目(61370069);霍英东基金资助项目(132032);教育部新世纪优秀人才基金资助项目(NCET-12-0794);安徽工业大学校青年基金资助项目(QZ201412)
摘    要:随着物联网的普及和发展,物联网搜索是摆在学术界和工业界面前迫切需要解决的问题,物联网搜索因此成为当前的一个研究热点。面对越来越多的传感器以及它们所产生的数据,只有结合智能的物联网搜索,才能体现这些数据的生命力。与传统的Baidu、Google、Bing、Yahoo等搜索引擎不同,物联网搜索从搜索对象、物理网数据的特点(大规模的、实时变化的、高度动态的、异构的、复杂的安全环境等)到物联网搜索的架构均与传统互联网不同,这导致了物联网搜所面临的挑战将更大。由此,阐述了物联网搜索的概念、特点、相关技术,对现有的典型系统和算法进行了比较性总结,分析了目前研究中存在的问题和挑战,并展望了其未来的发展方向。

关 键 词:物联网  搜索引擎  综述  意图理解  情景感知

Survey on the search of Internet of Things
Yun-quan GAO,Xiao-yong LI,Bin-xing FANG.Survey on the search of Internet of Things[J].Journal on Communications,2015,36(12):57-76.
Authors:Yun-quan GAO  Xiao-yong LI  Bin-xing FANG
Affiliation:1. Key Laboratory of Trustworthy Distributed Computing and Service,Ministry of Education,Beijing University of Posts and Telecommunications,Beijing 100876,China;2. School of Computer Science and Technology,Anhui University of Technology,Ma'anshan 243032,China
Abstract:With the popularization and development of the Internet of Things,the search of Internet of Things urgently needs to be solved in academia and industry and becomes a hot research topic.With the increasing data generated by sensors,only the search of IoT makes this data valuable.However,different from the traditional Internet search engines (such as Baidu,Google,Bing,Yahoo,etc),the search of IoT has different search objects and search architecture and data in the Internet of Things are massive,real-time,highly dynamic,heterogeneous,highly insecure.The above characteristics make search of IoT face more challenges.Firstly,the concept,characteristics,related technologies of search of IoT were summarized and presented.Secondly,several typical systems and related algorithms were described in detail.Finally,the current problems,the challenges and research prospects of this field for future were presented
Keywords:Internet of Things  search engine  survey  intention understanding  context awareness
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