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Title:
IoT-SVKSearch: A real-time multimodal search engine mechanism for the internet of things
Author: Ding, Zhiming (1) ; Chen, Zhikui (2) ; Yang, Qi (3)
Corresponding Author: Ding, Z.(zhiming@nfs.iscas.ac.cn)
Keyword: search engines ; index methods ; sensor networks ; spatial-temporal databases ; internet of things ; information retrieval for big data
Source: International Journal of Communication Systems
Issued Date: 2014
Volume: 27, Issue:6, Pages:871-897
Indexed Type: SCI ; EI
Department: (1) Institute of Software, Chinese Academy of Sciences, Beijing 100190, China; (2) School of Software Technology, Dalian University of Technology, Dalian 116620, China; (3) National Center of ITS Engineering and Technology, Beijing 100088, China
Abstract: Recent advances on the Internet of Things (IoT) have posed great challenges to the search engine community. IoT systems manage huge numbers of heterogeneous sensors and/or monitoring devices, which continuously monitor the states of real-world objects, and most data are generated automatically through sampling. The sampling data are dynamically changing so that the IoT search engine should support real-time retrieval. Additionally, the IoT search involves not only keyword matches but also spatial-temporal searches and value-based approximate searches, as IoT sampling data are generally from spatial-temporal scenario. To meet these challenges, we propose a 'Hybrid Real-time Search Engine Framework for the Internet of Things based on Spatial-Temporal, Value-based, and Keyword-based Conditions' ('IoT-SVK Search Engine' or simply 'IoT-SVKSearch' for short) in this paper. The experiments show that the IoT-SVK search engine has satisfactory performances in supporting real-time, multi-modal retrieval of massive sensor sampling data in the IoT. Copyright © 2013 John Wiley & Sons, Ltd.
English Abstract: Recent advances on the Internet of Things (IoT) have posed great challenges to the search engine community. IoT systems manage huge numbers of heterogeneous sensors and/or monitoring devices, which continuously monitor the states of real-world objects, and most data are generated automatically through sampling. The sampling data are dynamically changing so that the IoT search engine should support real-time retrieval. Additionally, the IoT search involves not only keyword matches but also spatial-temporal searches and value-based approximate searches, as IoT sampling data are generally from spatial-temporal scenario. To meet these challenges, we propose a 'Hybrid Real-time Search Engine Framework for the Internet of Things based on Spatial-Temporal, Value-based, and Keyword-based Conditions' ('IoT-SVK Search Engine' or simply 'IoT-SVKSearch' for short) in this paper. The experiments show that the IoT-SVK search engine has satisfactory performances in supporting real-time, multi-modal retrieval of massive sensor sampling data in the IoT. Copyright © 2013 John Wiley & Sons, Ltd.
Language: 英语
WOS ID: WOS:000337607000005
Citation statistics:
Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/16858
Appears in Collections:软件所图书馆_期刊论文

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Recommended Citation:
Ding, Zhiming ,Chen, Zhikui ,Yang, Qi . IoT-SVKSearch: A real-time multimodal search engine mechanism for the internet of things[J]. International Journal of Communication Systems,2014-01-01,27(6):871-897.
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