{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T02:13:12Z","timestamp":1775182392466,"version":"3.50.1"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2021,6,14]],"date-time":"2021-06-14T00:00:00Z","timestamp":1623628800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,6,14]],"date-time":"2021-06-14T00:00:00Z","timestamp":1623628800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Computing"],"published-print":{"date-parts":[[2021,10]]},"DOI":"10.1007\/s00607-021-00967-1","type":"journal-article","created":{"date-parts":[[2021,6,14]],"date-time":"2021-06-14T17:02:32Z","timestamp":1623690152000},"page":"2339-2360","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Prediction of resource contention in cloud using second order Markov model"],"prefix":"10.1007","volume":"103","author":[{"given":"K","family":"Surya","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4733-8191","authenticated-orcid":false,"given":"V. Mary Anita","family":"Rajam","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,6,14]]},"reference":[{"key":"967_CR1","volume-title":"Next generation and advanced network reliability analysis: using Markov models and software reliability engineering","author":"SR Ali","year":"2018","unstructured":"Ali SR (2018) Next generation and advanced network reliability analysis: using Markov models and software reliability engineering. Springer, Berlin"},{"key":"967_CR2","doi-asserted-by":"crossref","unstructured":"Anand A, Lakshmi J, Nandy S (2013) Virtual machine placement optimization supporting performance slas. In: Cloud Computing Technology and Science (CloudCom). In: 2013 IEEE 5th International conference on, IEEE, vol\u00a01, pp. 298\u2013305","DOI":"10.1109\/CloudCom.2013.46"},{"key":"967_CR3","doi-asserted-by":"publisher","first-page":"107340","DOI":"10.1016\/j.comnet.2020.107340","volume":"179","author":"A Asghari","year":"2020","unstructured":"Asghari A, Sohrabi MK, Yaghmaee F (2020) A cloud resource management framework for multiple online scientific workflows using cooperative reinforcement learning agents. Computer Netw 179:107340","journal-title":"Computer Netw"},{"issue":"1","key":"967_CR4","first-page":"23","volume":"41","author":"RN Calheiros","year":"2011","unstructured":"Calheiros RN, Ranjan R, Beloglazov A, De Rose CA, Buyya R (2011) Cloudsim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Softw: Pract Exp 41(1):23\u201350","journal-title":"Softw: Pract Exp"},{"key":"967_CR5","doi-asserted-by":"crossref","unstructured":"Chen L, Shen H, Platt S (2016) Cache contention aware virtual machine placement and migration in cloud datacenters. In: 2016 IEEE 24th International conference on network protocols (ICNP), IEEE, pp. 1\u201310","DOI":"10.1109\/ICNP.2016.7784447"},{"key":"967_CR6","doi-asserted-by":"publisher","first-page":"1016","DOI":"10.1016\/j.future.2016.11.022","volume":"105","author":"Y Cheng","year":"2020","unstructured":"Cheng Y, Chen W, Wang Z, Tang Z, Xiang Y (2020) Smart vm co-scheduling with the precise prediction of performance characteristics. Future Gener Computer Syst 105:1016\u20131027","journal-title":"Future Gener Computer Syst"},{"key":"967_CR7","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1007\/978-981-15-0751-9_28","volume-title":"Soft computing: theories and applications","author":"K Dubey","year":"2020","unstructured":"Dubey K, Nasr AA, Sharma S, El-Bahnasawy N, Attiya G, El-Sayed A (2020) Efficient vm placement policy for data centre in cloud environment. In: Pant M, Sharma T, Verma O, Singla R, Sikander A (eds) Soft computing: theories and applications. Springer, Berlin, pp 301\u2013309"},{"key":"967_CR8","doi-asserted-by":"crossref","unstructured":"Fox A, Turner A, Kim HS (2012) (2012) Resource contention-aware virtual machine management for enterprise applications. In: Global communications conference (GLOBECOM). IEEE, IEEE, pp. 1641\u20131646","DOI":"10.1109\/GLOCOM.2012.6503349"},{"issue":"2","key":"967_CR9","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1109\/TSUSC.2017.2723954","volume":"3","author":"K Gai","year":"2018","unstructured":"Gai K, Qiu M, Zhao H, Sun X (2018) Resource management in sustainable cyber-physical systems using heterogeneous cloud computing. IEEE Trans Sustain Comput 3(2):60\u201372","journal-title":"IEEE Trans Sustain Comput"},{"key":"967_CR10","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-020-05559-2","author":"M Ghetas","year":"2021","unstructured":"Ghetas M (2021) A multi-objective monarch butterfly algorithm for virtual machine placement in cloud computing. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-020-05559-2","journal-title":"Neural Comput Appl"},{"key":"967_CR11","doi-asserted-by":"publisher","first-page":"437","DOI":"10.1007\/978-981-15-5341-7_35","volume-title":"Advances in communication and computational technology","author":"BN Gohil","year":"2021","unstructured":"Gohil BN, Gamit S, Patel DR (2021) Fair fit\u2013a load balance aware vm placement algorithm in cloud data centers. In: Hura G, Singh A, Siong Hoe L (eds) Advances in communication and computational technology. Springer, Singapore, pp 437\u2013451"},{"issue":"4","key":"967_CR12","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1002\/for.2441","volume":"36","author":"HL Hammer","year":"2017","unstructured":"Hammer HL, Yazidi A, Begnum K (2017) An inhomogeneous hidden markov model for efficient virtual machine placement in cloud computing environments. J Forecast 36(4):407\u2013420","journal-title":"J Forecast"},{"key":"967_CR13","doi-asserted-by":"crossref","unstructured":"Han X, Schooley R, Mackenzie D, David O, Lloyd WJ (2020) Characterizing public cloud resource contention to support virtual machine co-residency prediction. In: 2020 IEEE International conference on cloud engineering (IC2E), IEEE, pp. 162\u2013172","DOI":"10.1109\/IC2E48712.2020.00024"},{"key":"967_CR14","doi-asserted-by":"crossref","unstructured":"Kandoussi EM, El Mir I, Hanini M, Haqiq A (2019) Modeling virtual machine migration as a security mechanism by using continuous-time markov chain model. In: 2019 4th World conference on complex systems (WCCS), IEEE, pp. 1\u20136","DOI":"10.1109\/ICoCS.2019.8930781"},{"issue":"3","key":"967_CR15","first-page":"1","volume":"57","author":"DX Ky","year":"2018","unstructured":"Ky DX, Tuyen LT (2018) A higher order Markov model for time series forecasting. Int J Appl Math Stat TM 57(3):1\u201318","journal-title":"Int J Appl Math Stat TM"},{"issue":"3","key":"967_CR16","doi-asserted-by":"publisher","first-page":"37","DOI":"10.3390\/fi9030037","volume":"9","author":"Z Lei","year":"2017","unstructured":"Lei Z, Sun E, Chen S, Wu J, Shen W (2017) A novel hybrid-copy algorithm for live migration of virtual machine. Future Internet 9(3):37","journal-title":"Future Internet"},{"key":"967_CR17","doi-asserted-by":"crossref","unstructured":"Liu D, Cai Z, Li X (2017) Hidden markov model based spot price prediction for cloud computing. In: 2017 IEEE International symposium on parallel and distributed processing with applications and 2017 IEEE international conference on ubiquitous computing and communications (ISPA\/IUCC), pp. 996\u20131003","DOI":"10.1109\/ISPA\/IUCC.2017.00152"},{"key":"967_CR18","doi-asserted-by":"crossref","unstructured":"Lloyd W, Pallickara S, David O, Arabi M, Rojas K (2017) Mitigating resource contention and heterogeneity in public clouds for scientific modeling services. In: 2017 IEEE International conference on cloud engineering (IC2E), IEEE, pp. 159\u2013166","DOI":"10.1109\/IC2E.2017.29"},{"key":"967_CR19","doi-asserted-by":"crossref","unstructured":"Mars J, Vachharajani N, Hundt R, Soffa ML (2010) Contention aware execution: online contention detection and response. In: Proceedings of the 8th annual IEEE\/ACM international symposium on Code generation and optimization, ACM, pp. 257\u2013265","DOI":"10.1145\/1772954.1772991"},{"key":"967_CR20","doi-asserted-by":"publisher","first-page":"7190","DOI":"10.1109\/ACCESS.2017.2785280","volume":"6","author":"SB Melhem","year":"2018","unstructured":"Melhem SB, Agarwal A, Goel N, Zaman M (2018) Markov prediction model for host load detection and vm placement in live migration. IEEE Access 6:7190\u20137205","journal-title":"IEEE Access"},{"key":"967_CR21","doi-asserted-by":"crossref","unstructured":"Moradi H, Wang W, Fernandez A, Zhu D (2019) upredict: A user-level profiler-based predictive framework for single vm applications in multi-tenant clouds. arXiv preprint arXiv:1908.04491","DOI":"10.1109\/IC2E48712.2020.00015"},{"issue":"2","key":"967_CR22","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1109\/TNSM.2015.2407273","volume":"12","author":"J Mukherjee","year":"2015","unstructured":"Mukherjee J, Krishnamurthy D, Rolia J (2015) Resource contention detection in virtualized environments. IEEE Trans Netw Serv Manag 12(2):217\u2013231","journal-title":"IEEE Trans Netw Serv Manag"},{"issue":"1","key":"967_CR23","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1145\/1113361.1113374","volume":"40","author":"K Park","year":"2006","unstructured":"Park K, Pai VS (2006) Comon: a mostly-scalable monitoring system for planetlab. ACM SIGOPS Op Syst Rev 40(1):65\u201374","journal-title":"ACM SIGOPS Op Syst Rev"},{"key":"967_CR24","doi-asserted-by":"crossref","unstructured":"Perez D, Hung LH, Xu S, Yeung KY, Lloyd W (2020) An investigation on public cloud performance variation for an rna sequencing workflow. In: Proceedings of the 11th ACM international conference on bioinformatics, computational biology and health informatics, pp. 1\u20137","DOI":"10.1145\/3388440.3414859"},{"key":"967_CR25","doi-asserted-by":"publisher","first-page":"114558","DOI":"10.1016\/j.eswa.2020.114558","volume":"171","author":"PF Popiolek","year":"2021","unstructured":"Popiolek PF, dos Santos Machado K, Mendizabal OM (2021) Low overhead performance monitoring for shared infrastructures. Expert Syst Appl 171:114558","journal-title":"Expert Syst Appl"},{"key":"967_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11227-020-03169-2","volume":"76","author":"M Rajabzadeh","year":"2020","unstructured":"Rajabzadeh M, Haghighat AT, Rahmani AM (2020) New comprehensive model based on virtual clusters and absorbing markov chains for energy-efficient virtual machine management in cloud computing. J Supercomput 76:1\u201320","journal-title":"J Supercomput"},{"key":"967_CR27","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s00607-021-00915-z","volume":"103","author":"R Regaieg","year":"2021","unstructured":"Regaieg R, Koub\u00e0a M, Ales Z, Aguili T (2021) Multi-objective optimization for vm placement in homogeneous and heterogeneous cloud service provider data centers. Computing 103:1\u201325","journal-title":"Computing"},{"issue":"2","key":"967_CR28","first-page":"161","volume":"45","author":"M Sheikhalishahi","year":"2015","unstructured":"Sheikhalishahi M, Grandinetti L, Wallace RM, Vazquez-Poletti JL (2015) Autonomic resource contention-aware scheduling. Softw: Pr Exp 45(2):161\u2013175","journal-title":"Softw: Pr Exp"},{"key":"967_CR29","unstructured":"Somani G, Khandelwal P, Phatnani K (2012) Vupic: Virtual machine usage based placement in iaas cloud. arXiv preprint arXiv:1212.0085"},{"issue":"2","key":"967_CR30","doi-asserted-by":"publisher","first-page":"837","DOI":"10.1007\/s10586-019-02954-w","volume":"23","author":"H Talebian","year":"2020","unstructured":"Talebian H, Gani A, Sookhak M, Abdelatif AA, Yousafzai A, Vasilakos AV, Yu FR (2020) Optimizing virtual machine placement in iaas data centers: taxonomy, review and open issues. Clust Comput 23(2):837\u2013878","journal-title":"Clust Comput"},{"key":"967_CR31","unstructured":"Vallone J, Birke R, Chen L (2017) Making neighbors quiet: An approach to detect virtual resource contention. In: IEEE Transactions on services computing"},{"key":"967_CR32","doi-asserted-by":"crossref","unstructured":"Van\u00a0Beek V, Oikonomou G, Iosup A (2019) A cpu contention predictor for business-critical workloads in cloud datacenters. In: 2019 IEEE 4th International workshops on foundations and applications of self* systems (FAS* W), IEEE, pp. 56\u201361","DOI":"10.1109\/FAS-W.2019.00027"},{"key":"967_CR33","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2020.3046673","author":"Q Wu","year":"2021","unstructured":"Wu Q, Zhou M, Wen J (2021) Endpoint communication contention-aware cloud workflow scheduling. IEEE Trans Autom Sci Eng. https:\/\/doi.org\/10.1109\/TASE.2020.3046673","journal-title":"IEEE Trans Autom Sci Eng"},{"issue":"2","key":"967_CR34","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1023\/A:1011408729750","volume":"4","author":"D Xu","year":"2001","unstructured":"Xu D, Nahrstedt K, Wichadakul D (2001) Qos and contention-aware multi-resource reservation. Clust Comput 4(2):95\u2013107","journal-title":"Clust Comput"},{"key":"967_CR35","doi-asserted-by":"publisher","unstructured":"Zhao H, Wang Q, Wang J, Wan B, Li S (2020) Vm performance maximization and pm load balancing virtual machine placement in cloud. In: 2020 20th IEEE\/ACM International symposium on cluster, cloud and internet computing (CCGRID), pp. 857\u2013864, https:\/\/doi.org\/10.1109\/CCGrid49817.2020.00011","DOI":"10.1109\/CCGrid49817.2020.00011"}],"container-title":["Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00607-021-00967-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00607-021-00967-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00607-021-00967-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,4]],"date-time":"2023-11-04T21:53:45Z","timestamp":1699134825000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00607-021-00967-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,14]]},"references-count":35,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2021,10]]}},"alternative-id":["967"],"URL":"https:\/\/doi.org\/10.1007\/s00607-021-00967-1","relation":{},"ISSN":["0010-485X","1436-5057"],"issn-type":[{"value":"0010-485X","type":"print"},{"value":"1436-5057","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,6,14]]},"assertion":[{"value":"23 January 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 June 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 June 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}