{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,8]],"date-time":"2025-11-08T17:49:25Z","timestamp":1762624165368,"version":"3.37.3"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2019,4,3]],"date-time":"2019-04-03T00:00:00Z","timestamp":1554249600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"published-print":{"date-parts":[[2019,9]]},"DOI":"10.1007\/s11227-019-02797-7","type":"journal-article","created":{"date-parts":[[2019,4,4]],"date-time":"2019-04-04T04:59:27Z","timestamp":1554353967000},"page":"5760-5781","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["SAIR: significance-aware approach to improve QoR of big data processing in case of budget constraint"],"prefix":"10.1007","volume":"75","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1121-1914","authenticated-orcid":false,"given":"Hossein","family":"Ahmadvand","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maziar","family":"Goudarzi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,4,3]]},"reference":[{"key":"2797_CR1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/978-3-031-01741-4","volume-title":"The datacenter as a computer: an introduction to the design of warehouse-scale machines","author":"LA Barroso","year":"2013","unstructured":"Barroso LA, Clidaras J, H\u00f6lzle U (2013) The datacenter as a computer: an introduction to the design of warehouse-scale machines, vol 8.3, 2nd edn. Morgan & Claypool, San Rafael, pp 1\u2013154","edition":"2"},{"key":"2797_CR2","first-page":"1","volume":"2007","author":"J Gantz","year":"2012","unstructured":"Gantz J, Reinsel D (2012) The digital universe in 2020: big data, bigger digital shadows, and biggest growth in the far east. IDC iView IDC Anal Future 2007:1\u201316","journal-title":"IDC iView IDC Anal Future"},{"issue":"2","key":"2797_CR3","doi-asserted-by":"publisher","first-page":"166","DOI":"10.1109\/LCA.2016.2636293","volume":"16","author":"H Ahmadvand","year":"2017","unstructured":"Ahmadvand H, Goudarzi M (2017) Using data variety for efficient progressive big data processing in warehouse-scale computers. IEEE Comput Archit Lett 16(2):166\u2013169","journal-title":"IEEE Comput Archit Lett"},{"key":"2797_CR4","unstructured":"Fekete J-D, Primet R (2016) Progressive analytics: a computation paradigm for exploratory data analysis. arXiv preprint arXiv, vol. 1607.05162"},{"key":"2797_CR5","first-page":"62","volume":"48","author":"S Mittal","year":"2016","unstructured":"Mittal S (2016) A survey of techniques for approximate computing. ACM CSUR 48:62","journal-title":"ACM CSUR"},{"issue":"2","key":"2797_CR6","first-page":"12","volume":"14","author":"K Parasyris","year":"2017","unstructured":"Parasyris K, Vassiliadis V, Antonopoulos CD, Lalis S, Bellas N (2017) Significance-aware program execution on unreliable hardware. ACM TACO 14(2):12","journal-title":"ACM TACO"},{"key":"2797_CR7","doi-asserted-by":"crossref","unstructured":"Zhao Y, Calheiros RN, Gange G, Ramamohanarao K, Buyya R (2015) SLA-based resource scheduling for big data analytics as a service in cloud computing environments. In: 2015 44th International Conference on Parallel Processing (ICPP)","DOI":"10.1109\/ICPP.2015.60"},{"key":"2797_CR8","doi-asserted-by":"crossref","unstructured":"Honjo T, Oikawa K (2013) Hardware acceleration of hadoop mapreduce. In: 2013 IEEE International Conference on in Big Data","DOI":"10.1109\/BigData.2013.6691562"},{"key":"2797_CR9","doi-asserted-by":"crossref","unstructured":"Shan Y, Wang B, Yan J, Wang Y, Xu N, Yang H (2010) FPMR: MapReduce framework on FPGA. In: Proceedings of the 18th Annual ACM\/SIGDA International Symposium on Field Programmable Gate Arrays","DOI":"10.1145\/1723112.1723129"},{"key":"2797_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.jnca.2014.07.022","volume":"46","author":"I Polato","year":"2014","unstructured":"Polato I, R\u00e9 R, Goldman A, Kon F (2014) A comprehensive view of Hadoop research\u2014a systematic literature review. J Netw Comput Appl 46:1\u201325","journal-title":"J Netw Comput Appl"},{"issue":"10","key":"2797_CR11","doi-asserted-by":"publisher","first-page":"2720","DOI":"10.1109\/TPDS.2014.2358556","volume":"26","author":"L Mashayekhy","year":"2015","unstructured":"Mashayekhy L, Movahed Nejad M, Grosu D, Zhang Q, Shi W (2015) Energy-aware scheduling of mapreduce jobs for big data applications. IEEE Trans Parallel Distrib Syst 26(10):2720\u20132733","journal-title":"IEEE Trans Parallel Distrib Syst"},{"key":"2797_CR12","doi-asserted-by":"publisher","first-page":"1726","DOI":"10.14778\/2556549.2556557","volume":"6","author":"B Chandramouli","year":"2013","unstructured":"Chandramouli B, Goldstein J, Quamar A (2013) Scalable progressive analytics on big data in the cloud. Proc VLDB Endow 6:1726\u20131737","journal-title":"Proc VLDB Endow"},{"key":"2797_CR13","unstructured":"Condie T, Conway N, Alvaro P, Hellerstein JM, Elmeleegy K, Sears R (2010) MapReduce online. In Nsdi"},{"key":"2797_CR14","unstructured":"Wang Y, Shi W (2013) On optimal budget-driven scheduling algorithms for MapReduce jobs in the hetereogeneous cloud. Technical report TR-13\u201302, Carleton University"},{"key":"2797_CR15","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1145\/2786763.2694351","volume":"43","author":"I Goiri","year":"2015","unstructured":"Goiri I, Bianchini R, Nagarakatte S, Nguyen TD (2015) Approxhadoop: bringing approximations to mapreduce frameworks. ACM SIGARCH Comput Archit News 43:383\u2013397","journal-title":"ACM SIGARCH Comput Archit News"},{"issue":"1","key":"2797_CR16","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1186\/s40537-019-0185-4","volume":"6","author":"H Ahmadvand","year":"2019","unstructured":"Ahmadvand H, Goudarzi M, Foroutan F (2019) Gapprox: using Gallup approach for approximation in big data processing. J Big Data 6(1):20","journal-title":"J Big Data"},{"key":"2797_CR17","doi-asserted-by":"crossref","unstructured":"Vassiliadis V, Riehme J, Deussen J, Parasyris K, Antonopoulos CD, Bellas N, Lalis S, Naumann U (2016) Towards automatic significance analysis for approximate computing. In: 2016 IEEE\/ACM International Symposium on Code Generation and Optimization (CGO)","DOI":"10.1145\/2854038.2854058"},{"key":"2797_CR18","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.bdr.2016.07.001","volume":"6","author":"Y Chen","year":"2016","unstructured":"Chen Y, An A (2016) Approximate parallel high utility itemset mining. Big Data Res 6:26\u201342","journal-title":"Big Data Res"},{"key":"2797_CR19","doi-asserted-by":"crossref","unstructured":"Zamani AR, AbdelBaky M, Balouek-Thomert D, Rodero I, Parashar M (2017) Supporting data-driven workflows enabled by large scale observatories. In: IEEE 13th International Conference on e-Science (e-Science), Auckland, New Zealand","DOI":"10.1109\/eScience.2017.95"},{"issue":"3","key":"2797_CR20","doi-asserted-by":"publisher","first-page":"109","DOI":"10.14778\/3021924.3021928","volume":"10","author":"X Zhang","year":"2016","unstructured":"Zhang X, Wang J, Yin J (2016) Sapprox: enabling efficient and accurate approximations on sub-datasets with distribution-aware online sampling. Proc VLDB Endow 10(3):109\u2013120","journal-title":"Proc VLDB Endow"},{"issue":"4","key":"2797_CR21","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1007\/s41019-018-0074-4","volume":"3","author":"K Li","year":"2018","unstructured":"Li K, Li G (2018) Approximate query processing: what is new and where to go? Data Sci Eng 3(4):379\u2013397","journal-title":"Data Sci Eng"},{"key":"2797_CR22","doi-asserted-by":"crossref","unstructured":"Agarwal S, Mozafari B, Panda A, Milner H, Madden S, Stoica I (2013) BlinkDB: queries with bounded errors and bounded response times on very large data. In: Proceedings of the European Conference on Computer Systems (EuroSys)","DOI":"10.1145\/2465351.2465355"},{"key":"2797_CR23","unstructured":"Zheng C, Zhan J, Jia Z, Zhang L (2013) Characterizing os behavior of scale-out data center workloads. In: The Seventh Annual Workshop on the Interaction amongst Virtualization, Operating Systems and Computer Architecture (WIVOSCA 2013)"},{"key":"2797_CR24","doi-asserted-by":"crossref","unstructured":"Lee Y, Lee Y (2011) Detecting ddos attacks with hadoop. In: Proceedings of The ACM CoNEXT Student Workshop","DOI":"10.1145\/2079327.2079334"},{"key":"2797_CR25","doi-asserted-by":"crossref","unstructured":"Thusoo A, Shao Z, Anthony S, Borthakur D, Jain N, Sarma JS, Murthy R, Liu H (2010) Data warehousing and analytics infrastructure at Facebook. In: Proceedings of the 2010 ACM SIGMOD International Conference on Management of Data","DOI":"10.1145\/1807167.1807278"},{"key":"2797_CR26","doi-asserted-by":"crossref","unstructured":"Kaur N, Sood SK (2017) Efficient resource management system based on 4Vs of big data streams. Big Data Research","DOI":"10.1016\/j.bdr.2017.02.002"},{"issue":"1","key":"2797_CR27","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1109\/TBDATA.2016.2638860","volume":"4","author":"Y Jiang","year":"2018","unstructured":"Jiang Y, Huang Z, Tsang DHK (2018) Towards max\u2013min fair resource allocation for stream big data analytics in shared clouds. IEEE Trans Big Data 4(1):130\u2013137","journal-title":"IEEE Trans Big Data"},{"issue":"2","key":"2797_CR28","first-page":"11","volume":"2","author":"J Kelley","year":"2017","unstructured":"Kelley J, Stewart C, Morris N, Tiwari D, He Y, Elnikety S (2017) Obtaining and managing answer quality for online data-intensive services. ACM TOMPECS 2(2):11","journal-title":"ACM TOMPECS"},{"issue":"12","key":"2797_CR29","doi-asserted-by":"publisher","first-page":"5150","DOI":"10.1007\/s11227-017-2074-y","volume":"73","author":"C Li","year":"2017","unstructured":"Li C, Zhu L, Liu Y, Luo Y (2017) Resource scheduling approach for multimedia cloud content management. J Supercomput 73(12):5150\u20135172","journal-title":"J Supercomput"},{"issue":"2","key":"2797_CR30","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1109\/TBDATA.2016.2632744","volume":"4","author":"J Wang","year":"2018","unstructured":"Wang J, Zhang X, Yin J, Wang R, Wu H, Han D (2018) Speed up big data analytics by unveiling the storage distribution of sub-datasets. IEEE Trans Big Data 4(2):231\u2013244","journal-title":"IEEE Trans Big Data"},{"key":"2797_CR31","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1145\/1061318.1061320","volume":"30","author":"D Papadias","year":"2005","unstructured":"Papadias D, Tao Y, Fu G, Seeger B (2005) Progressive skyline computation in database systems. ACM TODS 30:41\u201382","journal-title":"ACM TODS"},{"key":"2797_CR32","first-page":"301","volume":"1","author":"K-L Tan","year":"2001","unstructured":"Tan K-L, Eng P-K, Ooi BC (2001) Efficient progressive skyline computation. VLDB 1:301\u2013310","journal-title":"VLDB"},{"key":"2797_CR33","unstructured":"Zhang D, Du Y, Xia T, Tao Y (2006) Progressive computation of the min-dist optimal-location query. In: Proceedings of the 32nd International Conference on Very Large Data Bases"},{"key":"2797_CR34","doi-asserted-by":"crossref","unstructured":"Krishnan DR, Quoc DL, Bhatotia P, Fetzer C, Rodrigues R (2016) IncApprox: a data analytics system for incremental approximate computing. In: Proceedings of the 25th International Conference on World Wide Web. International World Wide Web Conferences Steering Committee","DOI":"10.1145\/2872427.2883026"},{"issue":"1","key":"2797_CR35","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1177\/1094342017701278","volume":"32","author":"J Conejero","year":"2018","unstructured":"Conejero J, Corella S, Badia RM, Labarta J (2018) Task-based programming in COMPSs to converge from HPC to big data. Int J High Perform Comput Appl 32(1):45\u201360","journal-title":"Int J High Perform Comput Appl"},{"key":"2797_CR36","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2018.2823330","author":"C Qiu","year":"2018","unstructured":"Qiu C, Shen H, Chen L (2018) Towards green cloud computing: demand allocation and pricing policies for cloud service brokerage. IEEE Trans Big Data. https:\/\/doi.org\/10.1109\/TBDATA.2018.2823330","journal-title":"IEEE Trans Big Data"},{"issue":"6","key":"2797_CR37","doi-asserted-by":"publisher","first-page":"1452","DOI":"10.1016\/j.future.2012.01.008","volume":"29","author":"R Mian","year":"2012","unstructured":"Mian R, Martin P, Vazquez-Poletti JL (2012) Provisioning data analytic workloads in a cloud. Future Gen Comput Syst 29(6):1452\u20131458","journal-title":"Future Gen Comput Syst"},{"issue":"10","key":"2797_CR38","doi-asserted-by":"publisher","first-page":"5314","DOI":"10.1007\/s11227-018-2426-2","volume":"74","author":"M Malekimajd","year":"2018","unstructured":"Malekimajd M, Ardagna D, Ciavotta M, Gianniti E, Passacantando M, Rizzi AM (2018) An optimization framework for the capacity allocation. J Supercomput 74(10):5314\u20135348","journal-title":"J Supercomput"},{"key":"2797_CR39","unstructured":"BigDataBench. http:\/\/prof.ict.ac.cn\/ . Accessed 15 Feb 2019"},{"key":"2797_CR40","volume-title":"Sampling techniques","author":"WG Cochran","year":"2007","unstructured":"Cochran WG (2007) Sampling techniques. Wiley, Hoboken"},{"issue":"1","key":"2797_CR41","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1145\/1327452.1327492","volume":"51","author":"J Dean","year":"2008","unstructured":"Dean J, Ghemawat S (2008) MapReduce: simplified data processing on large clusters. Commun ACM 51(1):107\u2013113","journal-title":"Commun ACM"},{"key":"2797_CR42","unstructured":"Welcome to Apache\u2122 Hadoop\u00ae! http:\/\/hadoop.apache.org\/ . Accessed 15 Feb 2019"},{"key":"2797_CR43","unstructured":"Apache Spark\u2122\u2014lightning-fast cluster computing. http:\/\/www.spark-project.org\/ . Accessed 15 Feb 2019"},{"key":"2797_CR44","unstructured":"RDD Programming Guide. https:\/\/spark.apache.org\/docs\/latest\/rdd-programming-guide.html . Accessed 15 Feb 2019"},{"key":"2797_CR45","doi-asserted-by":"crossref","unstructured":"Wang L, Zhan J, Luo C, Zhu Y, Yang Q, He Y, Gao W, Jia Z, Shi Y, Zhang S, Zheng C, Lu G, Zhan K, Li X, Qiu B (2014) Bigdatabench: a big data benchmark suite from internet services. In: 2014 IEEE 20th International Symposium on High Performance Computer Architecture (HPCA)","DOI":"10.1109\/HPCA.2014.6835958"},{"key":"2797_CR46","unstructured":"UCI Machine Learning Repository. https:\/\/archive.ics.uci.edu\/ml\/datasets\/MHEALTH%20Dataset . Accessed 15 Feb 2019"},{"key":"2797_CR47","unstructured":"Sample CSV Data. https:\/\/support.spatialkey.com\/spatialkey-sample-csv-data\/ . Accessed 15 Feb 2019"},{"issue":"1","key":"2797_CR48","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1214\/ss\/1177013815","volume":"1","author":"B Efron","year":"1986","unstructured":"Efron B, Tibshirani R (1986) Bootstrap methods for standard errors, confidence intervals, and other measures of statistical accuracy. Stat Sci 1(1):54\u201375","journal-title":"Stat Sci"},{"key":"2797_CR49","unstructured":"Amazon EC2 Dedicated Instances. https:\/\/aws.amazon.com\/ec2\/purchasing-options\/dedicated-instances\/ . Accessed 15 Feb 2019"},{"key":"2797_CR50","volume-title":"Sampling: design and analysis","author":"SL Lohr","year":"2009","unstructured":"Lohr SL (2009) Sampling: design and analysis. Cengage Learning, Boston"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-019-02797-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11227-019-02797-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-019-02797-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,15]],"date-time":"2023-09-15T10:49:46Z","timestamp":1694774986000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11227-019-02797-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,4,3]]},"references-count":50,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2019,9]]}},"alternative-id":["2797"],"URL":"https:\/\/doi.org\/10.1007\/s11227-019-02797-7","relation":{},"ISSN":["0920-8542","1573-0484"],"issn-type":[{"type":"print","value":"0920-8542"},{"type":"electronic","value":"1573-0484"}],"subject":[],"published":{"date-parts":[[2019,4,3]]},"assertion":[{"value":"3 April 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}