{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,9]],"date-time":"2025-09-09T21:29:12Z","timestamp":1757453352027,"version":"3.37.3"},"reference-count":52,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2020,8,5]],"date-time":"2020-08-05T00:00:00Z","timestamp":1596585600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2020,8,5]],"date-time":"2020-08-05T00:00:00Z","timestamp":1596585600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Cloud Comp"],"published-print":{"date-parts":[[2020,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Data management systems commonly use bitmap indices to increase the efficiency of querying scientific data. Bitmaps are usually highly compressible and can be queried directly using fast hardware-supported bitwise logical operations. The processing of bitmap queries is inherently parallel in structure, which suggests they could benefit from concurrent computer systems. In particular, bitmap-range queries offer a highly parallel computational problem, and the hardware features of graphics processing units (GPUs) offer an alluring platform for accelerating their execution.In this paper, we present four GPU algorithms and two CPU-based algorithms for the parallel execution of bitmap-range queries. We show that in 98.8% of our tests, using real and synthetic data, the GPU algorithms greatly outperform the parallel CPU algorithms. For these tests, the GPU algorithms provide up to 54.1 \u00d7 speedup and an average speedup of 11.5\u00d7 over the parallel CPU algorithms. In addition to enhancing performance, augmenting traditional bitmap query systems with GPUs to offload bitmap query processing allows the CPU to process other requests.<\/jats:p>","DOI":"10.1186\/s13677-020-00191-w","type":"journal-article","created":{"date-parts":[[2020,8,5]],"date-time":"2020-08-05T07:02:39Z","timestamp":1596610959000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Parallel acceleration of CPU and GPU range queries over large data sets"],"prefix":"10.1186","volume":"9","author":[{"given":"Mitchell","family":"Nelson","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zachary","family":"Sorenson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joseph M.","family":"Myre","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0022-6192","authenticated-orcid":false,"given":"Jason","family":"Sawin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Chiu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,8,5]]},"reference":[{"key":"191_CR1","doi-asserted-by":"publisher","unstructured":"Norris RP (2010) Data challenges for next-generation radio telescopes In: Proceedings of the 2010 Sixth IEEE International Conference on e-Science Workshops. E-SCIENCEW \u201910, 21\u201324.. IEEE. https:\/\/doi.org\/10.1109\/esciencew.2010.13.","DOI":"10.1109\/esciencew.2010.13"},{"key":"191_CR2","doi-asserted-by":"publisher","unstructured":"Stockinger K (2001) Design and implementation of bitmap indices for scientific data In: International Database Engineering and Application Symposium, 47\u201357. https:\/\/doi.org\/10.1109\/ideas.2001.938070.","DOI":"10.1109\/ideas.2001.938070"},{"key":"191_CR3","doi-asserted-by":"publisher","unstructured":"Kesheng W, Koegler W, Chen J, Shoshani A (2003) Using bitmap index for interactive exploration of large datasets In: International Conference on Scientific and Statistical Database Management, 65\u201374. https:\/\/doi.org\/10.1109\/ssdm.2003.1214955.","DOI":"10.1109\/ssdm.2003.1214955"},{"key":"191_CR4","doi-asserted-by":"publisher","unstructured":"Antoshenkov G (1995) Byte-aligned bitmap compression In: Proceedings DCC\u201995 Data Compression Conference, 476.. IEEE. https:\/\/doi.org\/10.1109\/dcc.1995.515586.","DOI":"10.1109\/dcc.1995.515586"},{"key":"191_CR5","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1007\/978-3-642-23091-2_32","volume-title":"Database and Expert Systems Applications","author":"F Corrales","year":"2011","unstructured":"Corrales F, Chiu D, Sawin J (2011) Variable length compression for bitmap indices. In: Hameurlain A, Liddle SW, Schewe K-D, Zhou X (eds)Database and Expert Systems Applications, 381\u2013395.. Springer, Berlin."},{"key":"191_CR6","doi-asserted-by":"publisher","unstructured":"Deli\u00e8ge F, Pedersen TB (2010) Position list word aligned hybrid: Optimizing space and performance for compressed bitmaps In: International Conference on Extending Database Technology. EDBT \u201910, 228\u2013239. https:\/\/doi.org\/10.1145\/1739041.1739071.","DOI":"10.1145\/1739041.1739071"},{"issue":"2","key":"191_CR7","first-page":"1382","volume":"3","author":"F Fusco","year":"2010","unstructured":"Fusco F, Stoecklin MP, Vlachos M (2010) Net-fli: On-the-fly compression, archiving and indexing of streaming network traffic. VLDB 3(2):1382\u20131393.","journal-title":"VLDB"},{"key":"191_CR8","unstructured":"Wu K, Otoo EJ, Shoshani A, Nordberg H (2001) Notes on design and implementation of compressed bit vectors. Technical Report LBNL\/PUB-3161, Lawrence Berkeley National Laboratory."},{"key":"191_CR9","doi-asserted-by":"publisher","unstructured":"Wu K, Otoo EJ, Shoshani A (2002) Compressing bitmap indexes for faster search operations In: Proceedings 14th International Conference on Scientific and Statistical Database Management, 99\u2013108.. IEEE. https:\/\/doi.org\/10.1109\/ssdm.2002.1029710.","DOI":"10.1109\/ssdm.2002.1029710"},{"issue":"1","key":"191_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1132863.1132864","volume":"31","author":"K Wu","year":"2006","unstructured":"Wu K, Otoo EJ, Shoshani A (2006) Optimizing bitmap indices with efficient compression. ACM Trans. Database Syst. 31(1):1\u201338.","journal-title":"ACM Trans. Database Syst."},{"key":"191_CR11","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1007\/978-3-642-15251-1_26","volume-title":"International Conference on Database and Expert Systems Applications","author":"W Andrzejewski","year":"2010","unstructured":"Andrzejewski W, Wrembel R (2010) GPU-WAH: Applying GPUs to compressing bitmap indexes with word aligned hybrid In: International Conference on Database and Expert Systems Applications, 315\u2013329.. Springer, Berlin."},{"key":"191_CR12","first-page":"627","volume":"40","author":"W Andrzejewski","year":"2011","unstructured":"Andrzejewski W, Wrembel R (2011) GPU-PLWAH: GPU-based implementation of the PLWAH algorithm for compressing bitmaps. Control Cybern 40:627\u2013650.","journal-title":"Control Cybern"},{"key":"191_CR13","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1145\/3365109.3368789","volume-title":"Proceedings of the 6th IEEE\/ACM International Conference on Big Data Computing, Applications and Technologies. BDCAT \u201919","author":"M Nelson","year":"2019","unstructured":"Nelson M, Sorenson Z, Myre JM, Sawin J, Chiu D (2019) Gpu acceleration of range queries over large data sets In: Proceedings of the 6th IEEE\/ACM International Conference on Big Data Computing, Applications and Technologies. BDCAT \u201919, 11\u201320.. Association for Computing Machinery, New York."},{"key":"191_CR14","unstructured":"CUDA C (2019) Best practice guide. https:\/\/docs.nvidia.com\/cuda\/cuda-c-best-practices-guide. Accessed 1 Mar 2020."},{"issue":"4","key":"191_CR15","doi-asserted-by":"publisher","first-page":"1318","DOI":"10.1007\/s11227-014-1366-8","volume":"71","author":"Y Djenouri","year":"2015","unstructured":"Djenouri Y, Bendjoudi A, Mehdi M, Nouali-Taboudjemat N, Habbas Z (2015) Gpu-based bees swarm optimization for association rules mining. J Supercomput 71(4):1318\u20131344.","journal-title":"J Supercomput"},{"issue":"9","key":"191_CR16","doi-asserted-by":"publisher","first-page":"3836","DOI":"10.1002\/cpe.3836","volume":"29","author":"Y Djenouri","year":"2017","unstructured":"Djenouri Y, Bendjoudi A, Habbas Z, Mehdi M, Djenouri D (2017) Reducing thread divergence in gpu-based bees swarm optimization applied to association rule mining. Concurr Comput Pract Experience 29(9):3836.","journal-title":"Concurr Comput Pract Experience"},{"key":"191_CR17","doi-asserted-by":"publisher","unstructured":"Tran N-P, Lee M, Choi DH (2015) Memory-efficient parallelization of 3D lattice Boltzmann flow solver on a GPU In: 2015 IEEE 22nd International Conference on High Performance Computing (HiPC), 315\u2013324.. IEEE. https:\/\/doi.org\/10.1109\/hipc.2015.49.","DOI":"10.1109\/hipc.2015.49"},{"issue":"3","key":"191_CR18","first-page":"28","volume":"14","author":"N Weber","year":"2017","unstructured":"Weber N, Goesele M (2017) MATOG: array layout auto-tuning for CUDA. ACM Trans Archit Code Optim (TACO) 14(3):28.","journal-title":"ACM Trans Archit Code Optim (TACO)"},{"issue":"1","key":"191_CR19","first-page":"46","volume":"5","author":"L Dagum","year":"1998","unstructured":"Dagum L, Menon R (1998) OpenMP: An industry-standard API for shared-memory programming. Comput Sci Eng 5(1):46\u201355.","journal-title":"Comput Sci Eng"},{"key":"191_CR20","unstructured":"Lichman M (2013) UCI Machine Learning Repository. http:\/\/archive.ics.uci.edu\/ml. Accessed 1 Aug 2019."},{"issue":"2","key":"191_CR21","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1109\/TIT.1982.1056489","volume":"28","author":"S Lloyd","year":"1982","unstructured":"Lloyd S (1982) Least squares quantization in pcm. IEEE Trans Inf Theory 28(2):129\u2013137.","journal-title":"IEEE Trans Inf Theory"},{"issue":"4","key":"191_CR22","doi-asserted-by":"publisher","first-page":"648","DOI":"10.1016\/j.jbi.2011.02.008","volume":"44","author":"M Sariyar","year":"2011","unstructured":"Sariyar M, Borg A, Pommerening K (2011) Controlling false match rates in record linkage using extreme value theory. J Biomed Inf 44(4):648\u2013654.","journal-title":"J Biomed Inf"},{"key":"191_CR23","unstructured":"Bonneville Power Administration, http:\/\/www.bpa.gov."},{"issue":"5","key":"191_CR24","doi-asserted-by":"publisher","first-page":"323","DOI":"10.1080\/00107510500052444","volume":"46","author":"M Newman","year":"2005","unstructured":"Newman M (2005) Power laws, pareto distributions and zipf\u2019s law. Contemp Phys 46(5):323\u2013351.","journal-title":"Contemp Phys"},{"issue":"3","key":"191_CR25","doi-asserted-by":"publisher","first-page":"451","DOI":"10.1145\/1816038.1816021","volume":"38","author":"VW Lee","year":"2010","unstructured":"Lee VW, Kim C, Chhugani J, Deisher M, Kim D, Nguyen AD, Satish N, Smelyanskiy M, Chennupaty S, Hammarlund P, et al (2010) Debunking the 100X GPU vs. CPU myth: an evaluation of throughput computing on CPU and GPU. ACM SIGARCH Comput Archit News 38(3):451\u2013460.","journal-title":"ACM SIGARCH Comput Archit News"},{"issue":"16","key":"191_CR26","doi-asserted-by":"publisher","first-page":"644","DOI":"10.1016\/j.ipl.2010.05.018","volume":"110","author":"A Colantonio","year":"2010","unstructured":"Colantonio A, Di Pietro R (2010) Concise: Compressed \u2019n\u2019 composable integer set. Inf Process Lett 110(16):644\u2013650.","journal-title":"Inf Process Lett"},{"key":"191_CR27","doi-asserted-by":"publisher","unstructured":"Guzun G, Canahuate G, Chiu D, Sawin J (2014) A tunable compression framework for bitmap indices In: 2014 IEEE 30th International Conference on Data Engineering, 484\u2013495.. IEEE. https:\/\/doi.org\/10.1109\/icde.2014.6816675.","DOI":"10.1109\/icde.2014.6816675"},{"key":"191_CR28","doi-asserted-by":"publisher","unstructured":"van Schaik SJ, de Moor O (2011) A memory efficient reachability data structure through bit vector compression In: Proceedings of the 2011 ACM SIGMOD International Conference on Management of Data. SIGMOD \u201911, 913\u2013924. https:\/\/doi.org\/10.1145\/1989323.1989419.","DOI":"10.1145\/1989323.1989419"},{"key":"191_CR29","doi-asserted-by":"publisher","unstructured":"Chou J, Howison M, Austin B, Wu K, Qiang J, Bethel EW, Shoshani A, R\u00fcbel O, Prabhat Ryne RD (2011) Parallel index and query for large scale data analysis In: International Conference for High Performance Computing, Networking, Storage and Analysis. SC \u201911, 30\u201313011. https:\/\/doi.org\/10.1145\/2063384.2063424.","DOI":"10.1145\/2063384.2063424"},{"key":"191_CR30","doi-asserted-by":"publisher","unstructured":"Dong B, Byna S, Wu K (2014) Parallel query evaluation as a scientific data service In: 2014 IEEE International Conference on Cluster Computing (CLUSTER), 194\u2013202. https:\/\/doi.org\/10.1109\/cluster.2014.6968765.","DOI":"10.1109\/cluster.2014.6968765"},{"key":"191_CR31","doi-asserted-by":"publisher","unstructured":"Yildiz B, Wu K, Byna S, Shoshani A (2019) Parallel membership queries on very large scientific data sets using bitmap indexes. Concurr Comput Pract Experience:5157. https:\/\/doi.org\/10.1002\/cpe.5157.","DOI":"10.1002\/cpe.5157"},{"key":"191_CR32","doi-asserted-by":"publisher","unstructured":"Su Y, Agrawal G, Woodring J (2012) Indexing and parallel query processing support for visualizing climate datasets In: 2012 41st International Conference on Parallel Processing, 249\u2013258.. IEEE. https:\/\/doi.org\/10.1109\/icpp.2012.33.","DOI":"10.1109\/icpp.2012.33"},{"key":"191_CR33","doi-asserted-by":"publisher","unstructured":"Dongarra J, Gates M, Haidar A, Kurzak J, Luszczek P, Tomov S, Yamazaki I (2014) Accelerating numerical dense linear algebra calculations with GPUs. Numer Comput GPUs:1\u201326. https:\/\/doi.org\/10.1007\/978-3-319-06548-9_1.","DOI":"10.1007\/978-3-319-06548-9_1"},{"issue":"5-6","key":"191_CR34","doi-asserted-by":"publisher","first-page":"232","DOI":"10.1016\/j.parco.2009.12.005","volume":"36","author":"S Tomov","year":"2010","unstructured":"Tomov S, Dongarra J, Baboulin M (2010) Towards dense linear algebra for hybrid GPU accelerated manycore systems. Parallel Comput 36(5-6):232\u2013240.","journal-title":"Parallel Comput"},{"key":"191_CR35","doi-asserted-by":"publisher","unstructured":"Tomov S, Nath R, Ltaief H, Dongarra J (2010) Dense linear algebra solvers for multicore with GPU accelerators In: 2010 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW), 1\u20138.. IEEE. https:\/\/doi.org\/10.1109\/ipdpsw.2010.5470941.","DOI":"10.1109\/ipdpsw.2010.5470941"},{"key":"191_CR36","doi-asserted-by":"publisher","unstructured":"Bell N, Hoberock J (2012) Thrust: A productivity-oriented library for CUDA In: GPU Computing Gems Jade Edition, 359\u2013371. https:\/\/doi.org\/10.1016\/b978-0-12-811986-0.00033-9.","DOI":"10.1016\/b978-0-12-811986-0.00033-9"},{"key":"191_CR37","unstructured":"Merrill D (2016) Cub: Cuda unbound. http:\/\/nvlabs.github.io\/cub. Accessed 1 Aug 2019."},{"key":"191_CR38","doi-asserted-by":"publisher","unstructured":"Bailey P, Myre J, Walsh SD, Lilja DJ, Saar MO (2009) Accelerating lattice Boltzmann fluid flow simulations using graphics processors In: 2009 International Conference on Parallel Processing, 550\u2013557.. IEEE. https:\/\/doi.org\/10.1109\/icpp.2009.38.","DOI":"10.1109\/icpp.2009.38"},{"issue":"4","key":"191_CR39","doi-asserted-by":"publisher","first-page":"332","DOI":"10.1002\/cpe.1645","volume":"23","author":"J Myre","year":"2011","unstructured":"Myre J, Walsh SD, Lilja D, Saar MO (2011) Performance analysis of single-phase, multiphase, and multicomponent lattice-Boltzmann fluid flow simulations on GPU clusters. Concurr Comput Pract Experience 23(4):332\u2013350.","journal-title":"Concurr Comput Pract Experience"},{"issue":"12","key":"191_CR40","doi-asserted-by":"publisher","first-page":"2353","DOI":"10.1016\/j.cageo.2009.05.001","volume":"35","author":"SD Walsh","year":"2009","unstructured":"Walsh SD, Saar MO, Bailey P, Lilja DJ (2009) Accelerating geoscience and engineering system simulations on graphics hardware. Comput Geosci 35(12):2353\u20132364.","journal-title":"Comput Geosci"},{"key":"191_CR41","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1145\/1735688.1735706","volume-title":"Proceedings of the 3rd Workshop on General-Purpose Computation on Graphics Processing Units. GPGPU-3","author":"P Bakkum","year":"2010","unstructured":"Bakkum P, Skadron K (2010) Accelerating sql database operations on a gpu with cuda In: Proceedings of the 3rd Workshop on General-Purpose Computation on Graphics Processing Units. GPGPU-3, 94\u2013103.. ACM, New York."},{"key":"191_CR42","doi-asserted-by":"publisher","unstructured":"Fusco F, Vlachos M, Dimitropoulos X, Deri L (2013) Indexing million of packets per second using gpus In: Proceedings of the 2013 Conference on Internet Measurement Conference. IMC \u201913, 327\u2013332. https:\/\/doi.org\/10.1145\/2504730.2504756.","DOI":"10.1145\/2504730.2504756"},{"key":"191_CR43","doi-asserted-by":"publisher","first-page":"16046","DOI":"10.1109\/ACCESS.2018.2816039","volume":"6","author":"X Nguyen","year":"2018","unstructured":"Nguyen X, Hoang T, Nguyen H, Inoue K, Pham C (2018) An FPGA-based hardware accelerator for energy-efficient bitmap index creation. IEEE Access 6:16046\u201316059.","journal-title":"IEEE Access"},{"key":"191_CR44","doi-asserted-by":"publisher","unstructured":"Haas S, Karnagel T, Arnold O, Laux E, Schlegel B, Fettweis G, Lehner W (2016) Hw\/sw-database-codesign for compressed bitmap index processing In: 2016 IEEE 27th International Conference on Application-specific Systems, Architectures and Processors (ASAP), 50\u201357. https:\/\/doi.org\/10.1109\/asap.2016.7760772.","DOI":"10.1109\/asap.2016.7760772"},{"key":"191_CR45","unstructured":"Heimel M, Markl V (2012) A first step towards gpu-assisted query optimization. In: Bordawekar R Lang CA (eds)International Workshop on Accelerating Data Management Systems Using Modern Processor and Storage Architectures - ADMS, 33\u201344.. VLDB endowment."},{"key":"191_CR46","doi-asserted-by":"publisher","unstructured":"Gosink LJ, Wu K, Bethel EW, Owens JD, Joy KI (2009) Data parallel bin-based indexing for answering queries on multi-core architectures. In: Winslett M (ed)Scientific and Statistical Database Management, 110\u2013129. https:\/\/doi.org\/10.1007\/978-3-642-02279-1_9.","DOI":"10.1007\/978-3-642-02279-1_9"},{"issue":"8","key":"191_CR47","doi-asserted-by":"publisher","first-page":"1195","DOI":"10.1016\/j.jpdc.2013.03.015","volume":"73","author":"J Kim","year":"2013","unstructured":"Kim J, Kim S-G, Nam B (2013) Parallel multi-dimensional range query processing with r-trees on gpu. J Parallel Distrib Comput 73(8):1195\u20131207.","journal-title":"J Parallel Distrib Comput"},{"key":"191_CR48","doi-asserted-by":"publisher","unstructured":"Wu K, Otoo E, Shoshani A (2004) On the performance of bitmap indices for high cardinality attributes In: VLDB\u201904, 24\u201335. https:\/\/doi.org\/10.1016\/b978-012088469-8.50006-1.","DOI":"10.1016\/b978-012088469-8.50006-1"},{"key":"191_CR49","doi-asserted-by":"publisher","unstructured":"Slechta R, Sawin J, McCamish B, Chiu D, Canahuate G (2014) Optimizing query execution for variable-aligned length compression of bitmap indices In: International Database Engineering & Applications Symposium, 217\u2013226. https:\/\/doi.org\/10.1145\/2628194.2628252.","DOI":"10.1145\/2628194.2628252"},{"key":"191_CR50","doi-asserted-by":"publisher","unstructured":"Chmiel J, Morzy T, Wrembel R (2009) Hobi: Hierarchically organized bitmap index for indexing dimensional data In: Data Warehousing and Knowledge Discovery, 87\u201398. https:\/\/doi.org\/10.1007\/978-3-642-03730-6_8.","DOI":"10.1007\/978-3-642-03730-6_8"},{"issue":"12","key":"191_CR51","doi-asserted-by":"publisher","first-page":"1382","DOI":"10.14778\/2824032.2824038","volume":"8","author":"P Nagarkar","year":"2015","unstructured":"Nagarkar P, Candan KS, Bhat A (2015) Compressed spatial hierarchical bitmap (cshb) indexes for efficiently processing spatial range query workloads. Proc VLDB Endow 8(12):1382\u20131393.","journal-title":"Proc VLDB Endow"},{"issue":"5","key":"191_CR52","doi-asserted-by":"publisher","first-page":"709","DOI":"10.1002\/spe.2325","volume":"46","author":"S Chambi","year":"2016","unstructured":"Chambi S, Lemire D, Kaser O, Godin R (2016) Better bitmap performance with roaring bitmaps. Softw Pract Exper 46(5):709\u2013719.","journal-title":"Softw Pract Exper"}],"container-title":["Journal of Cloud Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13677-020-00191-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13677-020-00191-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13677-020-00191-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,4]],"date-time":"2021-08-04T23:10:02Z","timestamp":1628118602000},"score":1,"resource":{"primary":{"URL":"https:\/\/journalofcloudcomputing.springeropen.com\/articles\/10.1186\/s13677-020-00191-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8,5]]},"references-count":52,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2020,12]]}},"alternative-id":["191"],"URL":"https:\/\/doi.org\/10.1186\/s13677-020-00191-w","relation":{},"ISSN":["2192-113X"],"issn-type":[{"type":"electronic","value":"2192-113X"}],"subject":[],"published":{"date-parts":[[2020,8,5]]},"assertion":[{"value":"25 March 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 July 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 August 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare that they have no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"44"}}