{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T18:15:46Z","timestamp":1754158546457,"version":"3.41.2"},"reference-count":27,"publisher":"Emerald","issue":"4","license":[{"start":{"date-parts":[[2020,8,11]],"date-time":"2020-08-11T00:00:00Z","timestamp":1597104000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["EL"],"published-print":{"date-parts":[[2020,8,11]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>As the storage and processing requirement of digital information is increasing on the cloud, it is very difficult for the single cloud provider (CP) to meet the resource requirement. Multiple providers form a federation for the execution of users\u2019 requests. For the federated cloud, this paper aims to address the issue distribution of users\u2019 request for resources and revenue among the providers by offering fair and stable distribution models for the federated cloud.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>This paper uses cooperative game (CG)-theoretical models, i.e. Shapley\u2013Shubik power index (SSPI) and Banzhaf power index (BPI) for distribution. Performance is analysed using variance and monotonicity using a case study.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>Numerical analysis is done using two scenarios. Monotonicity is evaluated. Results show that SSPI performs better as compared to BPI in terms of fairness accuracy and the framework provide the fair distribution of revenue among providers in the federated cloud.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Research limitations\/implications<\/jats:title>\n<jats:p>The proposed framework works efficiently under the specific defined conditions.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Social implications<\/jats:title>\n<jats:p>Paper provides the fair distribution. It assist the centralised cloud exchange in managing the users\u2019 request in such a way every CPs, in the federated cloud will get an equal chance of serving the users\u2019 request. The framework also provides the stable federation. Proposed work provides less rejection rate of users\u2019 request. Finally, it assists the providers in increasing their profits in the federation.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>This paper presents a CG theoretic-based framework for the distribution of resources required and revenue. The framework analysed the performance of distribution models by considering the variance and monotonicity for multiple users\u2019 requests.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/el-01-2019-0005","type":"journal-article","created":{"date-parts":[[2020,8,11]],"date-time":"2020-08-11T05:09:50Z","timestamp":1597122590000},"page":"745-767","source":"Crossref","is-referenced-by-count":3,"title":["A request allocation model for processing data in federated cloud computing"],"prefix":"10.1108","volume":"38","author":[{"given":"Sahil","family":"Kansal","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Harish","family":"Kumar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sakshi","family":"Kaushal","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"key2020111311425214600_ref001","unstructured":"Amazon (2016), 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