Hashing Moving Objects

Song, Zhexuan; Roussopoulos, Nick

doi:10.1007/3-540-44498-x_13

Cited by 46 publications

(33 citation statements)

References 9 publications

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“…For reducing the indexrestructuring load, a hash-index method is proposed (Song, 2001). This method dissects the entire area into grids and then stores the number of grids in the database.…”

Section: Hash Indexmentioning

confidence: 99%

Grouping Method for Neighbor Objects of Moving Object Using Hash Index

Lee

Kim

2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:A location-based social network (LBSNS) is a social network service (SNS) that is based on a user's location, unlike SNS, and facilitates additional activities like neighbour-user search and group formation in real time. This research examined the efficiency of a real-time grouping method for extracted neighbour objects on a WMTS (Web Map Tile Service) for which a hash index was used. As a result, the suggested method is not different from buffering a neighbour area according to the average number of returned data per 1 km 2 , and the required time is shorter than that of buffering.

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Section: Hash Indexmentioning

confidence: 99%

Grouping Method for Neighbor Objects of Moving Object Using Hash Index

Lee

Kim

2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Existing algorithms for continuous spatio-temporal query processing focus mainly on materializing incoming spatio-temporal data in disk-based index structures (e.g., hash tables [12,49], grid files [21,39,44], the Btree [29], the R-tree [33,35], and the TPR-tree [48,52]). Thus, it is implicitly assumed that all incoming data can be stored.…”

Section: Spatio-temporal Databasesmentioning

confidence: 99%

SOLE: scalable on-line execution of continuous queries on spatio-temporal data streams

Mokbel

Aref

2007

The VLDB Journal

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This paper presents the Scalable On-Line Execution algorithm (SOLE, for short) for continuous and on-line evaluation of concurrent continuous spatiotemporal queries over data streams. Incoming spatiotemporal data streams are processed in-memory against a set of outstanding continuous queries. The SOLE algorithm utilizes the scarce memory resource efficiently by keeping track of only the significant objects. In-memory stored objects are expired (i.e., dropped) from memory once they become insignificant. SOLE is a scalable algorithm where all the continuous outstanding queries share the same buffer pool. In addition, SOLE is presented as a spatio-temporal join between two input streams, a stream of spatio-temporal objects and a stream of spatio-temporal queries. To cope with intervals of high arrival rates of objects and/or queries, SOLE utilizes a load-shedding approach where some of the stored objects are dropped from memory. SOLE is implemented as a pipelined query operator that can be combined with traditional query operators in a query execution plan to support a wide variety of continuous queries. Performance experiments based on a real implementation of SOLE inside a prototype of a data stream management system show the scalability and efficiency of SOLE in highly dynamic environments.

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“…In order to reduce the cost of update, hashing technique uses a location pre-processing module that plays the role of a filter between a database and moving objects reporting their locations [6]. The location pre-processing module synchronizes its own hashing function with the hashing function used in the database and stores the location of moving objects into the database using bucket information obtained by entering the location of moving objects into the hashing function.…”

Section: Hashing Techniquementioning

confidence: 99%

“…Recently, hashing technique [6], Lazy Update R-tree(LUR-tree) [1], etc. have been proposed for the efficient management of the current location of moving objects.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Location Index for the Semantic Search of Moving Objects

Kim

Shin

Kang

et al. 2007

Software Technologies for Embedded and Ubiquitous Systems

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Abstract. In moving object databases, researches on the spatio-temporal access method are very important for the efficient search of moving object location in ITS, LBS, and Telematics. Recently, researches are being made actively on the efficient management of the current location of moving objects and on the estimation of future location using information such as the current location and moving pattern of moving objects. In this paper, we propose Map-Based Rtree(MBR-tree), which is a new current location index structure for indexing the current location of moving objects in an urban area, a 2-dimentional space. MBR-tree is an index which forms the MBR(Minimum Bounding Rectangle) of R-tree nodes using static objects(or fixed objects) on the map. Because moving objects generally moves within a static object, if the MBR is formed using static objects, we can reduce the cost of updating the index of the current location of moving objects. In addition, it shows superior performance in semantic search that searches in a specific building or place (e.g. "Who are in Konkuk university?") rather than in an arbitrary area. Finally, to test the index proposed in this paper, we compared its performance with that of hashing technique and Lazy Update R-tree using various datasets and proved the superiority of its performance.

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Hashing Moving Objects

Cited by 46 publications

References 9 publications

Grouping Method for Neighbor Objects of Moving Object Using Hash Index

Grouping Method for Neighbor Objects of Moving Object Using Hash Index

SOLE: scalable on-line execution of continuous queries on spatio-temporal data streams

An Efficient Location Index for the Semantic Search of Moving Objects

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