Definitions
Recently, several big data stream management systems (DSMS, for short) have been developed to provide an infrastructure to process streamed big data. Big spatial DSMSs constitute a special class of big DSMSs that are optimized to process large amounts of spatial data streams. The main idea behind most big spatial DSMSs is to leverage the spatial properties of the incoming data stream to fairly distribute the workload across multiple distributed processes. When processing big spatial data streams, it is important to maintain high throughput and low latency.
Overview
Spatial data is ubiquitous. It is continuously being generated at a large scale. This is due to the popularity of GPS-enabled devices, e.g., smartphones, smart-watches, personal activity trackers, and GPS-navigation devices. Efficient processing of this streamed big spatial data requires higher computational resources than the...
References
Abdelhamid AS, Tang M, Aly AM, Mahmood AR, Qadah T, Aref WG, Basalamah S (2016) Cruncher: distributed in-memory processing for location-based services. In: IEEE 32nd international conference on data engineering (ICDE). IEEE, pp 1406–1409
Apatche Hadoop (2017) Apatche Hadoop. http://hadoop.apache.org/
Aly AM, Sallam A, Gnanasekaran BM, Nguyen-Dinh LV, Aref WG, Ouzzani M, Ghafoor A (2012) M3: stream processing on main-memory mapreduce. In: ICDE, pp 1253–1256
Chen Z, Cong G, Zhang Z, Fuz TZ, Chen L (2017) Distributed publish/subscribe query processing on the spatio-textual data stream. In: IEEE 33rd international conference on data engineering (ICDE). IEEE, pp 1095–1106
Choi D, Song S, Kim B, Bae I (2015) Processing moving objects and traffic events based on spark streaming. In: 8th international conference on disaster recovery and business continuity (DRBC). IEEE, pp 4–7
Gedik B, Liu L (2006) Mobieyes: a distributed location monitoring service using moving location queries. IEEE Trans Mobile Comput 5(10):1384–1402
Lee Y, Song S (2015) Distributed indexing methods for moving objects based on spark stream. Int J Contents 11(1):69–72
Mahmood AR, Aly AM, Qadah T, Rezig EK, Daghistani A, Madkour A, Abdelhamid AS, Hassan MS, Aref WG, Basalamah S (2015) Tornado: a distributed spatio-textual stream processing system. PVLDB 8(12): 2020–2023
Mahmood AR, Daghistani A, Aly AM, Aref WG, Tang M, Basalamah S, Prabhakar S (2017) Adaptive processing of spatial-keyword data over a distributed streaming cluster. arXiv preprint, arXiv:170902533
Mokbel MF, Aref WG (2005) Gpac: generic and progressive processing of mobile queries over mobile data. In: Proceedings of the 6th international conference on mobile data management. ACM, pp 155–163
Mokbel MF, Aref WG (2008) Sole: scalable on-line execution of continuous queries on spatio-temporal data streams. VLDB J 17(5):971–995
Mokbel MF, Xiong X, Aref WG (2004a) Sina: Scalable incremental processing of continuous queries in spatio-temporal databases. In: Proceedings of the 2004 ACM SIGMOD international conference on management of data. ACM, pp 623–634
Mokbel MF, Xiong X, Aref WG, Hambrusch SE, Prabhakar S, Hammad MA (2004b) Place: a query processor for handling real-time spatio-temporal data streams. In: Proceedings of the thirtieth international conference on very large data bases, VLDB endowment, vol 30, pp 1377–1380
Neumeyer L, Robbins B, Nair A, Kesari A (2010) S4: distributed stream computing platform. In: IEEE international conference on data mining workshops (ICDMW). IEEE, pp 170–177
Ooi BC, McDonell KJ, Sacks-Davis R (1987) Spatial kd-tree: an indexing mechanism for spatial databases. In: IEEE COMPSAC, sn. vol 87, p 85
Song G (2016) Parallel and continuous join processing for data stream. PhD thesis, Université Paris-Saclay
Toshniwal A, Taneja S, Shukla A, Ramasamy K, Patel JM, Kulkarni S, Jackson J, Gade K, Fu M, Donham J et al (2014) Storm@ twitter. In: Proceedings of the 2014 ACM SIGMOD international conference on management of data. ACM, pp 147–156
Wang X, Zhang W, Zhang Y, Lin X, Huang Z (2017) Top-k spatial-keyword publish/subscribe over sliding window. VLDB J 26(3):301–326
Wu S, Kumar V, Wu KL, Ooi BC (2012) Parallelizing stateful operators in a distributed stream processing system: how, should you and how much? In: Proceedings of the 6th ACM international conference on distributed event-based systems. ACM, pp 278–289
Xiong X, Mokbel MF, Aref WG (2005) SEA-CNN: scalable processing of continuous k-nearest neighbor queries in spatio-temporal databases. In: Proceedings of the 21st international conference on data engineering, ICDE 2005. IEEE, pp 643–654
Xiong X, Elmongui HG, Chai X, Aref WG (2007) Place: a distributed spatio-temporal data stream management system for moving objects. In: International conference on mobile data management. IEEE, pp 44–51
Yu Z, Liu Y, Yu X, Pu KQ (2015) Scalable distributed processing of k nearest neighbor queries over moving objects. IEEE Trans Knowl Data Eng 27(5):1383–1396
Zaharia M, Das T, Li H, Shenker S, Stoica I (2012) Discretized streams: an efficient and fault-tolerant model for stream processing on large clusters. HotCloud 12:10–10
Zakhary V, Elmongui HG, Nagi MH (2013) Mobiplace*: a distributed framework for spatio-temporal data streams processing utilizing mobile clients processing power. In: International conference on mobile and ubiquitous systems: computing, networking, and services. Springer, pp 78–88
Zhang F, Zheng Y, Xu D, Du Z, Wang Y, Liu R, Ye X (2016) Real-time spatial queries for moving objects using storm topology. ISPRS Int J Geo-Inf 5(10):178
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Mahmood, A.R., Aref, W.G. (2018). Streaming Big Spatial Data. In: Sakr, S., Zomaya, A. (eds) Encyclopedia of Big Data Technologies. Springer, Cham. https://doi.org/10.1007/978-3-319-63962-8_70-1
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DOI: https://doi.org/10.1007/978-3-319-63962-8_70-1
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Latest
Streaming Big Spatial Data- Published:
- 26 November 2022
DOI: https://doi.org/10.1007/978-3-319-63962-8_70-3
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Streaming Big Spatial Data
- Published:
- 22 February 2018
DOI: https://doi.org/10.1007/978-3-319-63962-8_70-1
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Streaming Big Spatial Data- Published:
- 24 February 2012
DOI: https://doi.org/10.1007/978-3-319-63962-8_70-2