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Although the current static allocation method can make applications get corresponding resources, there still exist some shortcomings such as resource surpluses or shortages. This kind of problem is more crucial in real-time requirements of mobile cloud computing service. Therefore, it is necessary to establish a forecasting model to predict the future resource demands, and then perform on-demand distribution, which can effectively reduce the unnecessary daily network management fees and address the issues mentioned above. This paper focuses on CPU resource forecasting, establishing three forecasting models including Markov chain, weighted Markov chain and stacking weighted Markov chain. By comparing and analyzing the experiment results, the most reasonable forecasting model is found and explained.<\/jats:p>","DOI":"10.3233\/jifs-169675","type":"journal-article","created":{"date-parts":[[2018,6,19]],"date-time":"2018-06-19T15:00:05Z","timestamp":1529420405000},"page":"1315-1324","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":3,"title":["Research on the resource allocation algorithm based on forecasting in mobile cloud computing"],"prefix":"10.1177","volume":"35","author":[{"given":"Peicong","family":"Luo","sequence":"first","affiliation":[{"name":"Department of Computer Technology and Applications, State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining, China"}]},{"given":"Xiaoying","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Computer Technology and Applications, State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining, China"}]}],"member":"179","published-online":{"date-parts":[[2018,6,18]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/TC.2013.106"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2011.04.017"},{"key":"e_1_3_2_4_2","first-page":"364","article-title":"Efficient resource management for cloud computing environments[C]","volume":"357","author":"Younge A.J.","year":"2010","unstructured":"YoungeA.J., Von LaszewskiG., WangL., et al, Efficient resource management for cloud computing environments[C], Green Computing Conference357 (2010), 364.","journal-title":"Green Computing Conference"},{"key":"e_1_3_2_5_2","first-page":"99","article-title":"Adaptive management of virtualized resources in cloud computing using feedback control[C]","author":"Li Q.","year":"2009","unstructured":"LiQ.et al, Adaptive management of virtualized resources in cloud computing using feedback control[C], 1st International Conference on Information Science and Engineering (ICISE), (2009), 99\u2013102.","journal-title":"1st International Conference on Information Science and Engineering (ICISE)"},{"key":"e_1_3_2_6_2","first-page":"11","article-title":"Adaptive resource management in PaaS platform using feedback control LRU algorithm[C]","author":"Hu R.","year":"2011","unstructured":"HuR., LiY. and ZhangY., Adaptive resource management in PaaS platform using feedback control LRU algorithm[C], International Conference on Cloud and Service Computing (CSC), IEEE (2011), 11\u201318.","journal-title":"International Conference on Cloud and Service Computing (CSC), IEEE"},{"key":"e_1_3_2_7_2","first-page":"303","article-title":"Design of an adaptive framework for utility-based optimization of scientific applications in the cloud[C]","author":"Koehler M.","year":"2012","unstructured":"KoehlerM. and BenknerS., Design of an adaptive framework for utility-based optimization of scientific applications in the cloud[C], (UCC)2012, pp. 303\u2013308.","journal-title":"(UCC)"},{"key":"e_1_3_2_8_2","first-page":"1","article-title":"GPSO: An improved search algorithm for resource allocation in cloud databases[C]","author":"Sahal R.","year":"2013","unstructured":"SahalR., KhattabS.M. and OmaraF.A., GPSO: An improved search algorithm for resource allocation in cloud databases[C], ACS International Conference on Computer Systems and Applications. 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