FDSI-Tree: A Fully Distributed Spatial Index Tree for Efficient &amp; Power-Aware Range Queries in Sensor Networks

Eo, Sang Hun; Pandey, Suraj; Kim, Myung-Keun; Oh, Y. D.; Bae, Hae-Young

doi:10.1007/11611257_23

Cited by 9 publications

(2 citation statements)

References 20 publications

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“…-Fully distributed spatial index [108] Load distribution in query processing [109,229] Moving objects indices for past, current, and future locations [37,73,115,118,139,230,237], and [133] -Fully distributed spatial index [46] Distributed spatial clustering Route determination using trajectories [128] [20,130] Indexing past and future locations [25,160] Update tolerant grid based index [231] Motion adaptive index [59] Robust B+tree based index [80] Skyline query processing [75] Reverse nearest neighbor query processing [10] [136] Cluster based algorithm fr spatial query processing [142] Distributed range query [217] -Hilbert curve based data partitioning [129] Distributed quadtree based indexing [204] Indexing future trajectories [26] Geometric and probabilistic approach for indexing [192] Exclusive closest pairs in query processing [126] Distributed and continuous query processing [106,150] [121,225] Grid based spatial index [48] Spatiotemporal indices and query processing algorithms [40,49,235,246], and [30] Reducing communication cost in distributed query processing [116] Online scalable query execution [131] 2009 -Parallel spatial join [248] Distributed index for error prone data broadcast [251] Euclidean restriction based nearest neighboring algorithm…”

Section: Concurrency Controlmentioning

confidence: 99%

Indexing of real time geospatial data by IoT enabled devices: Opportunities, challenges and design considerations

Chaudhry

Yousaf

Khan

2020

AIS

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We are moving towards 'smart' world in which industries, such as healthcare, smart cities, transportation, and agriculture have started using IoT (Internet of Things). These applications involve huge number of sensors and devices that generate high volume of real time data. To perform useful analytics on this data, location and spatial awareness characteristics of devices need to be considered. Wide range of location-based services and sensors in GIS have to manage moving objects that change their position with respect to time. These applications generate voluminous amount of real time geospatial data that demands an effective query processing mechanism to minimize the response time of a query. Indexing is one of the traditional ways to minimize the response time of a query by pruning the search space. In this paper, we performed a detailed survey of the literature regarding the indexing of real time geospatial data generated by IoT enabled devices. Some major challenges relevant to indexing of moving objects are highlighted. Various important index design considerations are also discussed. The goal is to help researchers in understanding the principles, methods, and challenges in the indexing of real time geospatial data. This will also aid in identifying the future research opportunities.

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Section: Concurrency Controlmentioning

confidence: 99%

Indexing of real time geospatial data by IoT enabled devices: Opportunities, challenges and design considerations

Chaudhry

Yousaf

Khan

2020

AIS

View full text Add to dashboard Cite

show abstract

“…Hence, an efficient access method for spatio-temporal databases is even more important than for conventional databases. Numerous indexing methods have been proposed, however, most of them are usually customized either specifically for temporal data or for spatial data, and most of them cannot adequately handle integrated spatio-temporal data (Ang and Tan, 1995;Berchtold et al, 1996;Ciaccia et al, 1997;Curtis and Michael, 1991;Eo et al, 2006;Ibrahim and Christos, 1993;Kim et al, 2007;Lin, 2008Lin, , 2012Saltenis and Jensen, 2002;Stantic et al, 2010;Zhu et al, 2007). This is because indexing methods often divide the spatiotemporal index into two parts, temporal index and spatial index.…”

Section: Introductionmentioning

confidence: 99%