Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/41033
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dc.titleDistributed, concurrent range monitoring of spatial-network constrained mobile objects
dc.contributor.authorLu, H.
dc.contributor.authorHUANG ZHIYONG
dc.contributor.authorJensen, C.S.
dc.contributor.authorXu, L.
dc.date.accessioned2013-07-04T08:18:04Z
dc.date.available2013-07-04T08:18:04Z
dc.date.issued2007
dc.identifier.citationLu, H., HUANG ZHIYONG, Jensen, C.S., Xu, L. (2007). Distributed, concurrent range monitoring of spatial-network constrained mobile objects. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 4605 LNCS : 403-422. ScholarBank@NUS Repository.
dc.identifier.isbn9783540735397
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/41033
dc.description.abstractThe ability to continuously monitor the positions of mobile objects is important in many applications. While most past work has been set in Euclidean spaces, the mobile objects relevant in many applications are constrained to spatial networks. This paper addresses the problem of range monitoring of mobile objects in this setting, in which network distance is concerned. An architecture is proposed where the mobile clients and a central server share computation, the objective being to obtain scalability by utilizing the capabilities of the clients. The clients issue location reports to the server, which is in charge of data storing and query processing. The server associates each range monitoring query with the network-edge portions it covers. This enables incremental maintenance of each query, and it also enables shared maintenance of concurrent queries by identifying the overlaps among such queries. The mobile clients contribute to the query processing by encapsulating their host edge portion identifiers in their reports to the server. Extensive empirical studies indicate that the paper's proposal is efficient and scalable, in terms of both query load and moving-object load. © Springer-Verlag Berlin Heidelberg 2007.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume4605 LNCS
dc.description.page403-422
dc.identifier.isiutNOT_IN_WOS
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