DocumentCode :
3424885
Title :
A Hybrid Search Engine Framework for the Internet of Things Based on Spatial-Temporal, Value-Based, and Keyword-Based Conditions
Author :
Zhiming Ding ; Xu Gao ; Limin Guo ; Qi Yang
Author_Institution :
Inst. of Software, Beijing, China
fYear :
2012
fDate :
20-23 Nov. 2012
Firstpage :
17
Lastpage :
25
Abstract :
In recent years, the Internet of Things (IoT) has become a hot research issue and is changing the way how people live and work. IoT has a lot of benefits and meanwhile, it also brings about great challenges to the search engine community. In this paper, we analyze the challenges in the IoT search engine technology and propose a "Hybrid Search Engine Framework for the Internet of Things based on Spatial-Temporal, Value-based, and Keyword-based Conditions" ("IoT-SVK Search Engine" for short). The experimental results show that the IoT-SVK search engine has satisfactory performances in supporting multi-modal retrieval conditions, and provides a good solution for real-time retrieval of massive sensor sampling data in the Internet of Things.
Keywords :
Internet of Things; sampling methods; search engines; sensor fusion; spatiotemporal phenomena; Internet of Things; IoT search engine technology; IoT-SVK search engine; hybrid search engine framework; keyword-based conditions; multimodal retrieval conditions; real-time sensor sampling data retrieval; search engine community; spatial-temporal conditions; value-based conditions; Indexes; Internet; Monitoring; Search engines; Servers; Temperature measurement; Temperature sensors; Internet of Things; IoT Sampling Data; Search Engine; Spatial-Temporal Data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Green Computing and Communications (GreenCom), 2012 IEEE International Conference on
Conference_Location :
Besancon
Print_ISBN :
978-1-4673-5146-1
Type :
conf
DOI :
10.1109/GreenCom.2012.13
Filename :
6468290
Link To Document :
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