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论文类型：期刊论文

发表时间：2014-06-01

发表刊物：INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS

收录刊物：SCIE、EI、Scopus

卷号：27

期号：6,SI

页面范围：871-897

ISSN号：1074-5351

关键字：search engines; index methods; sensor networks; spatial-temporal databases; internet of things; information retrieval for big data

摘要：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 (c) 2013 John Wiley & Sons, Ltd.