dc.contributor.authorLi, Yanhong
dc.contributor.authorHuang, Ziqing
dc.contributor.authorZhu, Rongbo
dc.contributor.authorLi, Guohui
dc.contributor.authorShu, Lihchyun
dc.contributor.authorTian, Shasha
dc.contributor.authorMa, Maode
dc.identifier.citationLi, Y., Huang, Z., Zhu, R., Li, G., Shu, L., Tian, S., et al. (2017). Parameterized Spatio-Textual Publish/Subscribe in Road Sensor Networks. IEEE Access, 5, 22940-22952.en_US
dc.description.abstractHuge amounts of data that are geo-tagged and associated with text information are being generated at an unprecedented scale in road sensor networks. Publish/subscribe system is one kind of important applications for analyzing and processing these huge mounts of data in road sensor networks, which is required to support millions of subscriptions and filter a message in milliseconds. Since the messages arrive continuously at a high speed, rapid processing of the messages is definitely a challenge. This paper mainly addresses the issue of parameterized spatio-textual publish/subscribe problem in road sensor networks. First, with considering both the network distance and textual similarity of the subscriptions and messages, the road network structure, together with the subscriptions and the messages will be partitioned and organized efficiently, and a combined index structure, called basic indexing architecture, is proposed. Second, several effective pruning techniques which consider both location information and textual information are presented to cut down the processing overhead. Moreover, by employing these pruning techniques into the basic indexing architecture, an more efficient index, called enhanced indexing architecture, is presented. Third, an efficient processing algorithm is designed to improve the scalability. Finally, extensive simulations are conducted to show the efficiency and scalability of the proposed methods in road sensor networks.en_US
dc.format.extent13 p.en_US
dc.relation.ispartofseriesIEEE Accessen_US
dc.rights© 2017 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.en_US
dc.subjectSpatio-temporal Databaseen_US
dc.titleParameterized Spatio-Textual Publish/Subscribe in Road Sensor Networksen_US
dc.typeJournal Article
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.versionPublished versionen_US

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