{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,29]],"date-time":"2025-09-29T08:25:58Z","timestamp":1759134358036},"reference-count":27,"publisher":"Institute of Electronics, Information and Communications Engineers (IEICE)","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEICE Trans. Inf. &amp; Syst."],"published-print":{"date-parts":[[2017]]},"DOI":"10.1587\/transinf.2016edp7346","type":"journal-article","created":{"date-parts":[[2017,3,31]],"date-time":"2017-03-31T22:24:36Z","timestamp":1490999076000},"page":"813-821","source":"Crossref","is-referenced-by-count":17,"title":["Dynamic Scheduling of Workflow for Makespan and Robustness Improvement in the IaaS Cloud"],"prefix":"10.1587","volume":"E100.D","author":[{"given":"Haiou","family":"JIANG","sequence":"first","affiliation":[{"name":"Beijing University of Posts and Telecommunications"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haihong","family":"E","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meina","family":"SONG","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"532","reference":[{"key":"1","doi-asserted-by":"crossref","unstructured":"[1] F. Fakhfakh, H.H. Kacem, and A.H. Kacem, \u201cWorkflow scheduling in coud computing: a survey,\u201d IEEE 18th International Enterprise Distributed Object Computing Conference Workshops and Demonstrations, pp.372-378, 2014.","DOI":"10.1109\/EDOCW.2014.61"},{"key":"2","doi-asserted-by":"crossref","unstructured":"[2] E.N. Alkhanaka, S.P. Leea, R. Rezaeia, and R.M. Parizi, \u201cCost optimization approaches for scientific workflow scheduling in cloud and Grid computing: a review, classifications, and open issues,\u201d The Journal of Systems and Software vol.113, pp.1-26, 2016","DOI":"10.1016\/j.jss.2015.11.023"},{"key":"3","doi-asserted-by":"crossref","unstructured":"[3] J. Liu, E. Pacitti, P. Valduriez, and M. Mattoso, \u201cA survey of data-intensive scientific workflow management,\u201d Journal of Grid Computing, vol.13, no.4, pp.457-493, 2015.","DOI":"10.1007\/s10723-015-9329-8"},{"key":"4","doi-asserted-by":"crossref","unstructured":"[4] D.I.G. Amalarethinam and A.M. Josphin, \u201cDynamic task scheduling methods in heterogeneous systems: a survey,\u201d International Journal of Computer Applications, vol.110, no.6, pp.12-18, 2015.","DOI":"10.5120\/19318-0859"},{"key":"5","doi-asserted-by":"crossref","unstructured":"[5] G.P.J. Dejun, and C.H. Chi, EC<sub>2<\/sub>: performance analysis for resource provisioning of service-oriented applications, Workshop on Service Oriented Computing (ICSOC\/ServiceWave), pp.197-207, 2009.","DOI":"10.1007\/978-3-642-16132-2_19"},{"key":"6","doi-asserted-by":"crossref","unstructured":"[6] H. Topcuoglu, S. Hariri, and M.-Y. Wu, \u201cPerformance-effective and low-complexity task scheduling for heterogeneous computing,\u201d IEEE Transactions on Parallel and Distributed Systems, vol.13, no.3, pp.260-274, 2002.","DOI":"10.1109\/71.993206"},{"key":"7","doi-asserted-by":"crossref","unstructured":"[7] E. Ilavarasan and P. Thambidurai, \u201cLow complexity performance effective task scheduling algorithm for heterogeneous computing environments,\u201d Journal of Computer Sciences, vol.3, no.2, pp.94-103, 2007.","DOI":"10.3844\/jcssp.2007.94.103"},{"key":"8","doi-asserted-by":"crossref","unstructured":"[8] T. Hagras and J. Janecet, \u201cA simple scheduling heuristic for heterogeneous computing environments,\u201d Second International Symposium on Parallel and Distributed Computing, pp.104-110, 2003.","DOI":"10.1109\/ISPDC.2003.1267650"},{"key":"9","doi-asserted-by":"crossref","unstructured":"[9] E. Ilavarasan, P. Thambidurai, and R. Mahilmannan, \u201cHigh performance task scheduling algorithm for heterogeneous computing system,\u201d Distributed and Parallel Computing, vol.3719, pp.193-203, 2005.","DOI":"10.1007\/11564621_22"},{"key":"10","doi-asserted-by":"crossref","unstructured":"[10] L.F. Bittencourt, R. Sakellariou, and E.R.M. Madeira, \u201cDAG scheduling using a lookahead variant of the heterogeneous earliest finish time algorithm,\u201d 18th Euromicro Conference on Parallel, Distributed and Network-based Processing, pp.27-34, 2010.","DOI":"10.1109\/PDP.2010.56"},{"key":"11","doi-asserted-by":"crossref","unstructured":"[11] E.U. Munir, S. Mohsin, A. Hussain, M.W. Nisar, and S. Ali, \u201cSDBATS: a novel algorithm for task scheduling in heterogeneous computing systems,\u201d IEEE 27th International Symposium on Parallel and Distributed Processing Workshops and PhD Forum, pp.43-53, 2013.","DOI":"10.1109\/IPDPSW.2013.259"},{"key":"12","doi-asserted-by":"crossref","unstructured":"[12] H. Arabnejad and J.G. Barbosa, \u201cList scheduling algorithm for heterogeneous systems by an optimistic cost table,\u201d IEEE Transactions on Parallel and Distributed Systems, vol.25, no.3, pp.682-694, 2014.","DOI":"10.1109\/TPDS.2013.57"},{"key":"13","doi-asserted-by":"crossref","unstructured":"[13] M.A. Rodriguez and R. Buyya, \u201cDeadline based resource provisioning and scheduling algorithm for scientific workflows on clouds,\u201d IEEE Transactions on Cloud Computing, vol.2, no.2, pp.222-235, 2014.","DOI":"10.1109\/TCC.2014.2314655"},{"key":"14","doi-asserted-by":"crossref","unstructured":"[14] X. Tang, K. Li, G. Liao, K. Fang, and F. Wu, \u201cA stochastic scheduling algorithm for precedence constrained tasks on Grid,\u201d Future Generation of Computing System, vol.27, no.8, pp.1083-1091, 2011.","DOI":"10.1016\/j.future.2011.04.007"},{"key":"15","doi-asserted-by":"crossref","unstructured":"[15] D. Poola, S.K. Garg, R. Buyya, Y. Yang, and K. Ramamohanarao, \u201cRobust scheduling of scientific workflows with deadline and budget constraints in clouds,\u201d IEEE 28th International Conference on Advanced Information Networking and Applications (AINA), pp.858-865, 2014.","DOI":"10.1109\/AINA.2014.105"},{"key":"16","doi-asserted-by":"crossref","unstructured":"[16] W. Zheng and R. Sakellariou, \u201cA Monte-Carlo approach for full-ahead stochastic DAG scheduling,\u201d Proceedings of the 21st Heterogeneous Computing Workshop, pp.99-112, 2012.","DOI":"10.1109\/IPDPSW.2012.8"},{"key":"17","doi-asserted-by":"crossref","unstructured":"[17] W. Zheng and R. Sakellariou, \u201cStochastic DAG scheduling using a Monte Carlo approach,\u201d Journal of Parallel and Distributed Computing, vol.73, no.12, pp.1673-1689, 2013.","DOI":"10.1016\/j.jpdc.2013.07.019"},{"key":"18","doi-asserted-by":"crossref","unstructured":"[18] Q. Zheng, \u201cDynamic adaptation of DAGs with uncertain execution times in heterogeneous computing systems,\u201d IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW), pp.1-8, 2010.","DOI":"10.1109\/IPDPSW.2010.5470873"},{"key":"19","doi-asserted-by":"crossref","unstructured":"[19] J.G. Barbosa and B. Moreira, \u201cDynamic scheduling of a batch of parallel task jobs on heterogeneous clusters,\u201d Parallel Computing, vol.37, no.8, pp.428-438, 2011.","DOI":"10.1016\/j.parco.2010.12.004"},{"key":"20","doi-asserted-by":"crossref","unstructured":"[20] M. Rahman, R. Hassan, R. Ranjan, and R. Buyya, \u201cAdaptive workflow scheduling for dynamic Grid and cloud computing environment,\u201d Concurrency and Computation: Practice and Experience, vol.25, no.13, pp.1816-1842, 2013.","DOI":"10.1002\/cpe.3003"},{"key":"21","doi-asserted-by":"crossref","unstructured":"[21] L. B\u00f6l\u00f6ni and D.C. Marinescu, \u201cRobust scheduling of meta-programs,\u201d Journal of Scheduling, vol.5, no.5, pp.395-412, 2002.","DOI":"10.1002\/jos.115"},{"key":"22","doi-asserted-by":"crossref","unstructured":"[22] Z. Shi, E. Jeannot, and J. Dongarra, \u201cRobust task scheduling in non-deterministic heterogeneous computing systems,\u201d Cluster Computing, pp.1-10, 2006.","DOI":"10.1109\/CLUSTR.2006.311868"},{"key":"23","doi-asserted-by":"crossref","unstructured":"[23] L.-C. Canon and E. Jeannot, \u201cEvaluation and optimization of the robustness of DAG schedules in heterogeneous environments,\u201d IEEE Transactions on Parallel and Distributed Systems, vol.21, no.4, pp.532-546, 2010.","DOI":"10.1109\/TPDS.2009.84"},{"key":"24","doi-asserted-by":"crossref","unstructured":"[24] V. Shestak, J. Smith, H.J. Siegel, and A.A. Maciejewski, \u201cA stochastic approach to measuring the robustness of resource allocations in distributed systems,\u201d International Conference of Parallel Processing (ICPP), pp.459-470, 2006.","DOI":"10.1109\/ICPP.2006.14"},{"key":"25","doi-asserted-by":"crossref","unstructured":"[25] M. Bux and U. Leser, \u201cDynamicCloudSim: simulating heterogeneity in computational clouds,\u201d Future Generation Computer Systems, vol.46, pp.85-99, 2015.","DOI":"10.1016\/j.future.2014.09.007"},{"key":"26","doi-asserted-by":"crossref","unstructured":"[26] R.N. Calheiros, R. Ranjan, A. Beloglazov, C.A.F.D. Rose, and R. Buyya, \u201cCloudsim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms,\u201d SoftwarePractice and Experience vol.41, no.1, pp.23-50, 2011.","DOI":"10.1002\/spe.995"},{"key":"27","unstructured":"[27] Pegasus, WorkflowGenerator, https:\/\/confluence.pegasus.isi.edu\/display\/pegasus\/WorkflowGenerator, Accessed on 27th Oct. 2016."}],"container-title":["IEICE Transactions on Information and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E100.D\/4\/E100.D_2016EDP7346\/_pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,20]],"date-time":"2019-09-20T13:50:44Z","timestamp":1568987444000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E100.D\/4\/E100.D_2016EDP7346\/_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"references-count":27,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2017]]}},"URL":"https:\/\/doi.org\/10.1587\/transinf.2016edp7346","relation":{},"ISSN":["0916-8532","1745-1361"],"issn-type":[{"value":"0916-8532","type":"print"},{"value":"1745-1361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017]]}}}