Abstract
With the Internet of Things (IoT) becoming a major component of our daily life, IoT search engines, which can crawl heterogeneous data sources and search in highly dynamic contexts, attract increasing attention from users, industry, and the research community. While considerable effort has been devoted to designing IoT search engines for finding a particular mobile object device, or a list of object devices that fit the query terms description, relatively little attention has been paid to enabling so-called spatial-temporal-keyword query description. This paper identifies an important efficiency problem in existing IoT search engines that simply apply a keyword or spatial-temporal matching to identify object devices that satisfy the query requirement, but that do not simultaneously consider the spatial-temporal-keyword aspect. To shed light on this line of research, we present a novel SMSTK search engine, the core of which is a coding enabled index called STK-tree that seamlessly integrates spatial-temporal-keyword proximity. Further, we propose efficient algorithms for processing range queries. Extensive experiments suggest that SMSTK search engine enables efficient query processing in spatial-temporal-keyword-based object device search.
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Acknowledgment
The authors gratefully acknowledge the financial support partially from the National Natural Science Foundation of China (No. 61702232, No. 61772479 and No. 61662021), and partially from the higher school research fund from Jiangsu University (No. 1291170040).
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Tang, J., Zhou, Z. (2019). Searching the Internet of Things Using Coding Enabled Index Technology. In: Li, S. (eds) Green, Pervasive, and Cloud Computing. GPC 2018. Lecture Notes in Computer Science(), vol 11204. Springer, Cham. https://doi.org/10.1007/978-3-030-15093-8_6
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DOI: https://doi.org/10.1007/978-3-030-15093-8_6
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