{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T00:13:07Z","timestamp":1743120787605,"version":"3.40.3"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030656201"},{"type":"electronic","value":"9783030656218"}],"license":[{"start":{"date-parts":[[2020,12,12]],"date-time":"2020-12-12T00:00:00Z","timestamp":1607731200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,12,12]],"date-time":"2020-12-12T00:00:00Z","timestamp":1607731200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-65621-8_19","type":"book-chapter","created":{"date-parts":[[2020,12,11]],"date-time":"2020-12-11T12:32:07Z","timestamp":1607689927000},"page":"289-298","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Load Balancing Approach for a MapReduce Job Running on a Heterogeneous Hadoop Cluster"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2486-4949","authenticated-orcid":false,"given":"Kamalakant Laxman","family":"Bawankule","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9188-0140","authenticated-orcid":false,"given":"Rupesh Kumar","family":"Dewang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5994-6007","authenticated-orcid":false,"given":"Anil Kumar","family":"Singh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,12,12]]},"reference":[{"key":"19_CR1","doi-asserted-by":"crossref","unstructured":"Ahmad, F., Chakradhar, S.T., Raghunathan, A., Vijaykumar, T.: Tarazu: optimizing mapreduce on heterogeneous clusters. In: ACM SIGARCH Computer Architecture News, vol. 40, pp. 61\u201374. ACM (2012)","DOI":"10.1145\/2189750.2150984"},{"key":"19_CR2","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1016\/j.future.2014.09.001","volume":"42","author":"JC Anjos","year":"2015","unstructured":"Anjos, J.C., Carrera, I., Kolberg, W., Tibola, A.L., Arantes, L.B., Geyer, C.R.: Mra++: scheduling and data placement on mapreduce for heterogeneous environments. Future Gen. Comput. Syst. 42, 22\u201335 (2015)","journal-title":"Future Gen. Comput. Syst."},{"issue":"1","key":"19_CR3","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1145\/1327452.1327492","volume":"51","author":"J Dean","year":"2008","unstructured":"Dean, J., Ghemawat, S.: Mapreduce: simplified data processing on large clusters. Commun. ACM 51(1), 107\u2013113 (2008)","journal-title":"Commun. ACM"},{"key":"19_CR4","unstructured":"Gandhi, R., Xie, D., Hu, Y.C.: $$\\{$$PIKACHU$$\\}$$: how to rebalance load in optimizing mapreduce on heterogeneous clusters. In: 2013 $$\\{$$USENIX$$\\}$$ Annual Technical Conference ($$\\{$$USENIX$$\\}$$$$\\{$$ATC$$\\}$$ 13), pp. 61\u201366 (2013)"},{"key":"19_CR5","doi-asserted-by":"crossref","unstructured":"Ghemawat, S., Gobioff, H., Leung, S.T.: The google file system. In: Proceedings of the Nineteenth ACM Symposium on Operating Systems Principles, pp. 29\u201343 (2003)","DOI":"10.1145\/1165389.945450"},{"key":"19_CR6","doi-asserted-by":"crossref","unstructured":"Hou, X., Thomas, J.P., Varadharajan, V.: Dynamic workload balancing for Hadoop mapreduce. In: Proceedings of the 2014 IEEE Fourth International Conference on Big Data and Cloud Computing, pp. 56\u201362 (2014)","DOI":"10.1109\/BDCloud.2014.103"},{"key":"19_CR7","doi-asserted-by":"crossref","unstructured":"Huang, S., Huang, J., Dai, J., Xie, T., Huang, B.: The hibench benchmark suite: characterization of the mapreduce-based data analysis. In: 2010 IEEE 26th International Conference on Data Engineering Workshops (ICDEW 2010), pp. 41\u201351. IEEE (2010)","DOI":"10.1109\/ICDEW.2010.5452747"},{"key":"19_CR8","doi-asserted-by":"crossref","unstructured":"Kwon, Y., Balazinska, M., Howe, B., Rolia, J.: Skewtune: mitigating skew in mapreduce applications. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 25\u201336. ACM (2012)","DOI":"10.1145\/2213836.2213840"},{"key":"19_CR9","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1016\/j.bdr.2014.07.002","volume":"1","author":"CW Lee","year":"2014","unstructured":"Lee, C.W., Hsieh, K.Y., Hsieh, S.Y., Hsiao, H.C.: A dynamic data placement strategy for Hadoop in heterogeneous environments. Big Data Res. 1, 14\u201322 (2014)","journal-title":"Big Data Res."},{"key":"19_CR10","unstructured":"Liu, Z., Liu, Y., Wang, B., Gong, Z.: A novel run-time load balancing method for mapreduce. In: 2015 4th International Conference on Computer Science and Network Technology (ICCSNT), vol. 1, pp. 150\u2013154. IEEE (2015)"},{"key":"19_CR11","doi-asserted-by":"crossref","unstructured":"Lu, W., Chen, L., Yuan, H., Wang, L., Xing, W., Yang, Y.: Improving mapreduce performance by using a new partitioner in yarn. In: The 23rd International Conference on Distributed Multimedia Systems, Visual Languages and Sentient Systems, pp. 24\u201333 (2017)","DOI":"10.18293\/DMS2017-002"},{"key":"19_CR12","doi-asserted-by":"publisher","first-page":"423","DOI":"10.1016\/j.future.2018.07.043","volume":"90","author":"NS Naik","year":"2019","unstructured":"Naik, N.S., Negi, A., BR, T.B., Anitha, R.: A data locality based scheduler to enhance mapreduce performance in heterogeneous environments. Future Gen. Comput. Syst. 90, 423\u2013434 (2019)","journal-title":"Future Gen. Comput. Syst."},{"key":"19_CR13","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1016\/j.jpdc.2016.04.001","volume":"95","author":"PP Nghiem","year":"2016","unstructured":"Nghiem, P.P., Figueira, S.M.: Towards efficient resource provisioning in mapreduce. J. Parallel Distrib. Comput. 95, 29\u201341 (2016)","journal-title":"J. Parallel Distrib. Comput."},{"key":"19_CR14","unstructured":"Paravastu, R., Scarlat, R., Chandrasekaran, B.: Adaptive load balancing in mapreduce using flubber. Duke University Project Report (2012)"},{"key":"19_CR15","first-page":"1","volume":"10","author":"K Shvachko","year":"2010","unstructured":"Shvachko, K., Kuang, H., Radia, S., Chansler, R., et al.: The Hadoop distributed file system. MSST. 10, 1\u201310 (2010)","journal-title":"MSST."},{"key":"19_CR16","volume-title":"Hadoop: The Definitive Guide","author":"T White","year":"2012","unstructured":"White, T.: Hadoop: The Definitive Guide. O\u2019Reilly Media, Inc., Massachusetts (2012)"},{"key":"19_CR17","doi-asserted-by":"crossref","unstructured":"Yan, W., Li, C., Du, S., Mao, X.: An optimization algorithm for heterogeneous Hadoop clusters based on dynamic load balancing. In: 2016 17th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT), pp. 250\u2013255. IEEE (2016)","DOI":"10.1109\/PDCAT.2016.061"},{"key":"19_CR18","unstructured":"Zaharia, M., Konwinski, A., Joseph, A.D., Katz, R.H., Stoica, I.: Improving mapreduce performance in heterogeneous environments. In: Osdi, vol. 8, p. 7 (2008)"}],"container-title":["Lecture Notes in Computer Science","Distributed Computing and Internet Technology"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-65621-8_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,12,15]],"date-time":"2020-12-15T00:27:12Z","timestamp":1607992032000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-65621-8_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12,12]]},"ISBN":["9783030656201","9783030656218"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-65621-8_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020,12,12]]},"assertion":[{"value":"12 December 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICDCIT","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Distributed Computing and Internet Technology","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bhubaneswar","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 January 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 January 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icdcit2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icdcit.ac.in\/17th-icdcit-2021\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"99","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"13","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"13% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.5","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"6","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}