{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T10:10:38Z","timestamp":1777889438613,"version":"3.51.4"},"reference-count":32,"publisher":"SAGE Publications","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["KES"],"published-print":{"date-parts":[[2021,4,9]]},"abstract":"<jats:p>One of the familiar distributed technologies for sharing computing resources through internet is a cloud computing technology. One need not setup all computing resources on their own to design their applications. They can own as much they want by requesting computing resources through net. These resources are shared between users upon request by properly scheduling tasks in cloud. The process of scheduling tasks is to be optimized to share the resources very fast. The paper proposes a cluster medoid based task scheduling technique KMPS (K-medoid particle swarm approach) for minimizing the makespan. KMPS uses the merits of both Particle Swarm Optimization (PSO) and k-medoid approaches with added weights concept. Experimental results have shown that KMPS has optimized the results of make span and it is most suitable one for cloud computing.<\/jats:p>","DOI":"10.3233\/kes-210053","type":"journal-article","created":{"date-parts":[[2021,4,9]],"date-time":"2021-04-09T12:17:35Z","timestamp":1617970655000},"page":"65-73","source":"Crossref","is-referenced-by-count":2,"title":["A cluster medoid approach for cloud task scheduling"],"prefix":"10.1177","volume":"25","author":[{"given":"Y. Home Prasanna","family":"Raju","sequence":"first","affiliation":[{"name":"Department of CSE, Acharya Nagarjuna University, Guntur, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nagaraju","family":"Devarakonda","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, VIT-AP University, Amaravati, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"key":"10.3233\/KES-210053_ref1","first-page":"457","article-title":"Pso-based task scheduling algorithm using adaptive load balancing approach for cloud computing environment","author":"Ahmad","year":"2019","journal-title":"International Journal of Scientific and Technology Research"},{"key":"10.3233\/KES-210053_ref2","doi-asserted-by":"crossref","unstructured":"P. Akilandeswari and H. Srimathi, Survey and analysis on task scheduling in cloud environment, Indian Journal of Science and Technology (2016).","DOI":"10.17485\/ijst\/2016\/v9i37\/102058"},{"key":"10.3233\/KES-210053_ref3","doi-asserted-by":"crossref","first-page":"245","DOI":"10.14257\/ijgdc.2015.8.5.24","article-title":"Task scheduling using PSO algorithm in cloud computing environments","author":"Al-maamari","year":"2015","journal-title":"International Journal of Grid and Distributed Computing"},{"key":"10.3233\/KES-210053_ref4","first-page":"77","article-title":"Task scheduling in cloud computing using lion optimization algorithm","author":"Almezeini","year":"2017","journal-title":"International Journal of Advanced Computer Science and Applications"},{"key":"10.3233\/KES-210053_ref5","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1016\/j.protcy.2013.12.525","article-title":"Advantages and challenges of adopting cloud computing from an enterprise perspective","author":"Avram","year":"2014","journal-title":"Procedia Technology"},{"key":"10.3233\/KES-210053_ref6","doi-asserted-by":"crossref","first-page":"920","DOI":"10.1016\/j.procs.2015.09.064","article-title":"Enhanced particle swarm optimization for task scheduling in cloud computing environments","author":"Awad","year":"2015","journal-title":"Procedia Computer Science"},{"key":"10.3233\/KES-210053_ref7","doi-asserted-by":"crossref","first-page":"713","DOI":"10.1007\/s12243-010-0194-y","article-title":"Network virtualization for cloud computing","author":"Baroncelli","year":"2010","journal-title":"Annales des Telecommunications\/Annals of Telecommunications"},{"key":"10.3233\/KES-210053_ref8","unstructured":"Z. Chenhong et al., Independent tasks scheduling based on genetic algorithm in cloud computing, 5th International Conference on Wireless Communications, Networking and Mobile Computing, IEEE (2009)."},{"key":"10.3233\/KES-210053_ref9","first-page":"27","article-title":"Cloud computing: Issues and challenges","author":"Dillon","year":"2010","journal-title":"International Conference on Advanced Information Networking and Applications"},{"key":"10.3233\/KES-210053_ref10","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/j.icte.2017.08.001","article-title":"A hybrid particle swarm optimization and hill climbing algorithm for task scheduling in the cloud environments","author":"Dordaie","year":"2018","journal-title":"ICT Express"},{"key":"10.3233\/KES-210053_ref11","doi-asserted-by":"crossref","first-page":"1626","DOI":"10.1631\/jzus.2006.A1626","article-title":"An efficient enhanced k-means clustering algorithm","author":"Fahim","year":"2006","journal-title":"Journal of Zhejiang University-SCIENCE A"},{"key":"10.3233\/KES-210053_ref12","first-page":"60","article-title":"Genetic simulated annealing algorithm for task scheduling based on cloud computing environment","author":"Gan","year":"2010","journal-title":"International Conference on Intelligent Computing and Integrated Systems"},{"key":"10.3233\/KES-210053_ref13","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1109\/CCGrid.2013.89","article-title":"Energy efficient VM scheduling for cloud data centers: Exact allocation and migration algorithms","author":"Ghribi","year":"2013","journal-title":"13th IEEE\/ACM International Symposium on Cluster, Cloud, and Grid Computing"},{"key":"10.3233\/KES-210053_ref14","first-page":"1","article-title":"Multi-objective task assignment in cloud coputing by particle swarm optimizatoin","author":"Guo","year":"2012","journal-title":"International Conference on Wireless Communications, Networking and Mobile Computing"},{"key":"10.3233\/KES-210053_ref15","doi-asserted-by":"crossref","first-page":"1345","DOI":"10.1109\/GLOCOMW.2010.5700157","article-title":"Taxonomy of cloud computing services","author":"Hoefer","year":"2010","journal-title":"IEEE Globecom Workshops"},{"key":"10.3233\/KES-210053_ref16","first-page":"238","article-title":"Cloud load balancing techniques: A step towards green computing","author":"Kansal","year":"2012","journal-title":"IJCSI International Journal of Computer Science Issues"},{"key":"10.3233\/KES-210053_ref17","first-page":"265","article-title":"Using simulated annealing for task scheduling in distributed systems","author":"Kashani","year":"2009","journal-title":"1st International Conference on Computational Intelligence, Modelling, and Simulation"},{"key":"10.3233\/KES-210053_ref18","first-page":"405","article-title":"Clustering by means of medoids","author":"Kaufman","year":"1987","journal-title":"Statistical Data Analysis Based on the L 1-Norm and Related Methods"},{"key":"10.3233\/KES-210053_ref19","doi-asserted-by":"crossref","first-page":"7444","DOI":"10.1016\/j.eswa.2013.07.002","article-title":"Cluster center initialization algorithm for K-modes clustering","author":"Khan","year":"2013","journal-title":"Expert Systems with Applications"},{"key":"10.3233\/KES-210053_ref20","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1109\/CyberC.2011.79","article-title":"Load-balancing tactics in cloud","author":"Lee","year":"2011","journal-title":"International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery"},{"key":"10.3233\/KES-210053_ref21","first-page":"3","article-title":"Cloud task scheduling based on load balancing ant colony optimization","author":"Li","year":"2011","journal-title":"6th Annual China Grid Conference"},{"key":"10.3233\/KES-210053_ref22","first-page":"296","article-title":"A load-adapative cloud resource scheduling model based on ant colony algorithm","author":"Lu","year":"2011","journal-title":"International Conference on Cloud Computing and Intelligence Systems"},{"key":"10.3233\/KES-210053_ref23","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1007\/s10922-016-9385-9","article-title":"A survey of PSO-based scheduling algorithms in cloud computing","author":"Masdari","year":"2017","journal-title":"Journal of Network and Systems Management"},{"key":"10.3233\/KES-210053_ref24","unstructured":"P.N. Babu, M.C. Kumari and S.V. Mohan, A literature survey on cloud computing (2018), 44\u201349."},{"key":"10.3233\/KES-210053_ref25","first-page":"400","article-title":"A particle swarm optimization-based heuristic for scheduling workflow applications in cloud computing environments","author":"Pandey","year":"2010","journal-title":"International Conference on Advanced Information Networking and Applications"},{"key":"10.3233\/KES-210053_ref26","doi-asserted-by":"crossref","first-page":"3336","DOI":"10.1016\/j.eswa.2008.01.039","article-title":"A simple and fast algorithm for K-medoids clustering","author":"Park","year":"2009","journal-title":"Expert Systems with Applications"},{"key":"10.3233\/KES-210053_ref27","first-page":"425","article-title":"Cluster based hybrid approach to task scheduling in cloud environment","author":"Raju","year":"2019","journal-title":"International Journal of Advanced Computer Science and Applications"},{"key":"10.3233\/KES-210053_ref28","doi-asserted-by":"crossref","first-page":"739","DOI":"10.1007\/s10766-013-0275-4","article-title":"Task-based system load balancing in cloud computing using particle swarm optimization","author":"Ramezani","year":"2014","journal-title":"International Journal of Parallel Programming"},{"key":"10.3233\/KES-210053_ref29","doi-asserted-by":"crossref","first-page":"5412","DOI":"10.1109\/ACCESS.2018.2890067","article-title":"IPSO task scheduling algorithm for large scale data in cloud computing environment","author":"Saleh","year":"2019","journal-title":"IEEE Access"},{"key":"10.3233\/KES-210053_ref30","unstructured":"E. Schubert and P.J. Rousseeuw, Faster k-medoids clustering: Improving the PAM, CLARA, and CLARANS algorithms (2018)."},{"key":"10.3233\/KES-210053_ref31","doi-asserted-by":"crossref","first-page":"390","DOI":"10.7763\/IJCTE.2017.V9.1172","article-title":"Load management model for cloud computing using cloudsim","author":"Srivastava","year":"2017","journal-title":"International Journal of Computer Theory and Engineering"},{"key":"10.3233\/KES-210053_ref32","first-page":"332","article-title":"Dynamic PSO for task scheduling optimization in cloud computing","author":"Sudheer","year":"2019","journal-title":"International Journal of Recent Technology and Engineering"}],"container-title":["International Journal of Knowledge-based and Intelligent Engineering Systems"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/KES-210053","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T05:13:39Z","timestamp":1777612419000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/KES-210053"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,9]]},"references-count":32,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.3233\/kes-210053","relation":{},"ISSN":["1327-2314","1875-8827"],"issn-type":[{"value":"1327-2314","type":"print"},{"value":"1875-8827","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,4,9]]}}}