{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,5,28]],"date-time":"2024-05-28T02:49:18Z","timestamp":1716864558051},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2017,6,20]],"date-time":"2017-06-20T00:00:00Z","timestamp":1497916800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Computing"],"published-print":{"date-parts":[[2018,1]]},"DOI":"10.1007\/s00607-017-0563-8","type":"journal-article","created":{"date-parts":[[2017,6,20]],"date-time":"2017-06-20T19:53:07Z","timestamp":1497988387000},"page":"3-20","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["A parallel online trajectory compression approach for supporting big data workflow"],"prefix":"10.1007","volume":"100","author":[{"given":"Wei","family":"Han","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ze","family":"Deng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junde","family":"Chu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peng","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tejal","family":"Shah","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,6,20]]},"reference":[{"key":"563_CR1","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1007\/s13740-012-0004-y","volume":"1","author":"S Bowers","year":"2012","unstructured":"Bowers S, Workflow S (2012) Provenance, and data modeling challenges and approaches. J Data Semant 1:19\u201330. doi:\n                        10.1007\/s13740-012-0004-y","journal-title":"J Data Semant"},{"issue":"6","key":"563_CR2","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1109\/MCSE.2011.73","volume":"13","author":"RE Bryant","year":"2011","unstructured":"Bryant RE (2011) Data-intensive scalable computing for scientific applications. Comput Sci Eng 13(6):25\u201333","journal-title":"Comput Sci Eng"},{"key":"563_CR3","volume-title":"OpenMP: portable shared memory parallel programming","author":"B Chapman","year":"2007","unstructured":"Chapman B, Jost G, van der Pas R (2007) OpenMP: portable shared memory parallel programming. MIT Press, Cambridge"},{"key":"563_CR4","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1016\/j.ins.2014.01.015","volume":"275","author":"CLP Chen","year":"2014","unstructured":"Chen CLP, Zhang C-Y (2014) Data-intensive applications, challenges, techniques and technologies: a survey on big data. Inf Sci 275:314\u2013347","journal-title":"Inf Sci"},{"key":"563_CR5","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.inffus.2016.11.015","volume":"36","author":"Y Chen","year":"2017","unstructured":"Chen Y, Wang L, Li F, Bo D, Choo K-KR, Hassan H, Qin W (2017) Air quality data clustering using EPLS method. Inf Fusion 36:225\u2013232","journal-title":"Inf Fusion"},{"key":"563_CR6","doi-asserted-by":"crossref","unstructured":"Davidson SB, Freire J (2008) Provenance and scientific workflows: challenges and opportunities. In: SIGMOD08, June 9C12, Vancouver, BC, Canada, ACM 978-1-60558-102-6\/08\/06","DOI":"10.1145\/1376616.1376772"},{"key":"563_CR7","doi-asserted-by":"crossref","first-page":"1369","DOI":"10.1109\/TPDS.2011.308","volume":"23","author":"J Diaz","year":"2012","unstructured":"Diaz J, Mu\u00f1oz-Caro C, Ni\u00f1o A (2012) A survey of parallel programming modelsand tools in the multi and many-core era. IEEE Trans Parallel Distrib Syst 23:1369\u20131386","journal-title":"IEEE Trans Parallel Distrib Syst"},{"key":"563_CR8","doi-asserted-by":"crossref","first-page":"112","DOI":"10.3138\/FM57-6770-U75U-7727","volume":"10","author":"DH Douglas","year":"1973","unstructured":"Douglas DH, Peucker TK (1973) Algorithms for the reduction of the number of points required to represent a line or its caricature. Can Cartogr 10:112\u2013122","journal-title":"Can Cartogr"},{"key":"563_CR9","first-page":"763","volume":"4835","author":"J Gudmundsson","year":"2007","unstructured":"Gudmundsson J, Katajainen J, Merrick D, Ong C, Wolle T (2007) Compressing spatio-temporal trajectories. LNCS 4835:763\u2013775","journal-title":"LNCS"},{"issue":"12","key":"563_CR10","first-page":"2531","volume":"50","author":"C Guo","year":"2013","unstructured":"Guo C, Fang Y, Liu JN, Wan Y (2013) Study on social awareness computation methods for location-based services. J Comput Res Dev 50(12):2531\u20132542","journal-title":"J Comput Res Dev"},{"key":"563_CR11","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.sysarc.2016.07.002","volume":"72","author":"F Huang","year":"2017","unstructured":"Huang F, Tao J, Xiang Y, Liu P, Dong L, Wang L (2017) Parallel compressive sampling matching pursuit algorithm for compressed sensing signal reconstruction with OpenCL. J Syst Archit Embed Syst Des 72:51\u201360","journal-title":"J Syst Archit Embed Syst Des"},{"key":"563_CR12","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1007\/s00778-011-0237-7","volume":"20","author":"R Lange","year":"2011","unstructured":"Lange R, Drr F, Rothermel K (2011) Efficient real-time trajectory tracking. VLDB J 20:671\u2013694","journal-title":"VLDB J"},{"key":"563_CR13","doi-asserted-by":"crossref","first-page":"2827","DOI":"10.1109\/TKDE.2016.2598171","volume":"28","author":"J Liu","year":"2016","unstructured":"Liu J, Zhao K, Sommer P, Shang S, Kusy B, Lee J-G, Jurdak R (2016) A novel framework for online amnesic trajectory compression in resource constrained environments. IEEE Trans Knowl Data Eng 28:2827\u20132841","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"563_CR14","doi-asserted-by":"crossref","unstructured":"Liu J, Zhao K, Sommer P, Shang S, Kusy B, Jurdak R (2015) Bounded quadrant system: error-bounded trajectory compression on the go. In: The IEEE international conference on data engineering (ICDE), pp 987\u2013998","DOI":"10.1109\/ICDE.2015.7113350"},{"key":"563_CR15","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.future.2014.10.029","volume":"51","author":"Y Ma","year":"2015","unstructured":"Ma Y, Haiping W, Wang L, Huang B, Ranjan R, Zomaya AY, Jie W (2015) Remote sensing big data computing: challenges and opportunities. Future Gen Comput Syst 51:47\u201360","journal-title":"Future Gen Comput Syst"},{"key":"563_CR16","first-page":"765","volume":"2992","author":"N Meratnia","year":"2004","unstructured":"Meratnia N, de By RA (2004) Spatiotemporal compression techniques for moving point objects. LNCS 2992:765\u2013782","journal-title":"LNCS"},{"key":"563_CR17","doi-asserted-by":"crossref","unstructured":"Meratnia N, de By RA (2004) Spatiotemporal compression techniques for moving point objects. In: International conference on extending database technology (EDBT), pp 765\u2013782","DOI":"10.1007\/978-3-540-24741-8_44"},{"key":"563_CR18","doi-asserted-by":"crossref","unstructured":"Meratnia N, de By RA (2004) Spatiotemporal compression techniques for moving point objects. In: Proceedings of the 9th international conference on extending database technology (EDBT), pp 765\u2013782","DOI":"10.1007\/978-3-540-24741-8_44"},{"issue":"9","key":"563_CR19","doi-asserted-by":"crossref","first-page":"2489","DOI":"10.1002\/cpe.3049","volume":"27","author":"Y Miao","year":"2015","unstructured":"Miao Y, Wang L, Liu D, Ma Y, Zhang W, Chen L (2015) A Web 2.0-based science gateway for massive remote sensing image processing. Concurr Comput Pract Exp 27(9):2489\u20132501","journal-title":"Concurr Comput Pract Exp"},{"key":"563_CR20","doi-asserted-by":"crossref","unstructured":"Muckell J et al (2011) SQUISH: an online approach for GPS trajectory compression. In: Proceedings of the 2nd international conference on computing for geospatial research & applications. ACM","DOI":"10.1145\/1999320.1999333"},{"key":"563_CR21","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1007\/s10707-013-0184-0","volume":"18","author":"J Muckell","year":"2014","unstructured":"Muckell J, Olsen PW Jr, Hwang J-H, Lawson CT, Ravi SS (2014) Compression of trajectory data: a comprehensive evaluation and new approach. Geoinformatica 18:435\u2013460","journal-title":"Geoinformatica"},{"key":"563_CR22","unstructured":"Popa IS, Zeitouni K, Oria V, Kharrat A (2014) Spatio-temporal compression of trajectories in road networks. Geoinformatica, vol, preprint"},{"key":"563_CR23","doi-asserted-by":"publisher","unstructured":"Quercia D, Lathia N, Calabrese F, Di Lorenzo G, Crowcroft J (2010) Recommending social events from mobile phone location data (PDF). In: 2010 IEEE international conference on data mining, p 971. doi:\n                        10.1109\/ICDM.2010.152\n                        \n                    . ISBN 978-1-4244-9131-5","DOI":"10.1109\/ICDM.2010.152"},{"issue":"9","key":"563_CR24","doi-asserted-by":"crossref","first-page":"892","DOI":"10.1080\/17538947.2016.1158328","volume":"9","author":"W Song","year":"2016","unstructured":"Song W, Liu P, Wang L (2016) Sparse representation-based correlation analysis of non-stationary spatiotemporal big data. Int J Digit Earth 9(9):892\u2013913","journal-title":"Int J Digit Earth"},{"key":"563_CR25","doi-asserted-by":"crossref","unstructured":"Trajcevski G, Cao H, Scheuermanny P, Wolfsonz O, Vaccaro D (2006) On-line data reduction and the quality of history in moving objects databases. In: ACM international workshop on data engineering for wireless and mobile access (MobiDE), pp 19\u201326","DOI":"10.1145\/1140104.1140110"},{"key":"563_CR26","unstructured":"Tuning CUDA applications for Kepler (2015)"},{"key":"563_CR27","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1145\/3147.3165","volume":"11","author":"JS Vitter","year":"1985","unstructured":"Vitter JS (1985) Random sampling with a reservoir. ACM TOMS 11:37\u201357","journal-title":"ACM TOMS"},{"issue":"4","key":"563_CR28","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1109\/MCSE.2014.52","volume":"16","author":"L Wang","year":"2014","unstructured":"Wang L, Ke L, Liu P, Ranjan R, Chen L (2014) IK-SVD: dictionary learning for spatial big data via incremental atom update. Comput Sci Eng 16(4):41\u201352","journal-title":"Comput Sci Eng"},{"key":"563_CR29","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.knosys.2014.10.004","volume":"79","author":"L Wang","year":"2015","unstructured":"Wang L, Geng H, Liu P, Ke L, Kolodziej J, Ranjan R, Zomaya AY (2015) Particle swarm optimization based dictionary learning for remote sensing big data. Knowl Based Syst 79:43\u201350","journal-title":"Knowl Based Syst"},{"issue":"2","key":"563_CR30","doi-asserted-by":"crossref","first-page":"793","DOI":"10.1007\/s10586-016-0569-6","volume":"19","author":"L Wang","year":"2016","unstructured":"Wang L, Song W, Liu P (2016) Link the remote sensing big data to the image features via wavelet transformation. Clust Comput 19(2):793\u2013810","journal-title":"Clust Comput"},{"issue":"1","key":"563_CR31","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1007\/s00500-016-2246-3","volume":"21","author":"L Wang","year":"2017","unstructured":"Wang L, Zhang J, Liu P, Choo K-KR, Huang F (2017) Spectral-spatial multi-feature-based deep learning for hyperspectral remote sensing image classification. Soft Comput 21(1):213\u2013221","journal-title":"Soft Comput"},{"key":"563_CR32","doi-asserted-by":"crossref","unstructured":"Yuan J, Zheng Y, Xie X, Sun G (2011) Driving with knowledge from the physical world. In: KDD, pp 949\u2013960","DOI":"10.1145\/2020408.2020462"},{"key":"563_CR33","first-page":"32","volume":"33","author":"Y Zheng","year":"2010","unstructured":"Zheng Y, Xie X, Ma WY (2010) Geolife: a collaborative social networking service among user, location and trajectory. IEEE Data Eng Bull 33:32\u201340","journal-title":"IEEE Data Eng Bull"}],"container-title":["Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00607-017-0563-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00607-017-0563-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00607-017-0563-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2018,2,21]],"date-time":"2018-02-21T15:25:52Z","timestamp":1519226752000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00607-017-0563-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,6,20]]},"references-count":33,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2018,1]]}},"alternative-id":["563"],"URL":"https:\/\/doi.org\/10.1007\/s00607-017-0563-8","relation":{},"ISSN":["0010-485X","1436-5057"],"issn-type":[{"value":"0010-485X","type":"print"},{"value":"1436-5057","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,6,20]]}}}