{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T01:10:09Z","timestamp":1772759409214,"version":"3.50.1"},"reference-count":41,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2017,2,7]],"date-time":"2017-02-07T00:00:00Z","timestamp":1486425600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"National 973 Basic Research Program","award":["2014CB347800"],"award-info":[{"award-number":["2014CB347800"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61520106005"],"award-info":[{"award-number":["61520106005"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program","doi-asserted-by":"crossref","award":["2016YFB1000501"],"award-info":[{"award-number":["2016YFB1000501"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Model. Perform. Eval. Comput. Syst."],"published-print":{"date-parts":[[2017,6,30]]},"abstract":"<jats:p>\n            Although the Infrastructure-as-a-Service (IaaS) cloud offers diverse instance types to users, a significant portion of cloud users, especially those with small and short demands, cannot find an instance type that exactly fits their needs or fully utilize purchased instance-hours. In the meantime, cloud service providers are also faced with the challenge to consolidate small, short jobs, which exhibit strong dynamics, to effectively improve resource utilization. To handle such inefficiencies and improve cloud resource utilization, we propose\n            <jats:italic>Cocoa (COmputing in COntAiners)<\/jats:italic>\n            , a novel group buying mechanism that organizes jobs with complementary resource demands into groups and allocates them to group buying deals predefined by cloud providers. Each group buying deal offers a resource pool for all the jobs in the deal, which can be implemented as either a virtual machine or a physical server. By running each user job on a virtualized container, our mechanism allows flexible resource sharing among different users in the same group buying deal, while improving resource utilization for cloud providers. To organize jobs with varied resource demands and durations into groups, we model the initial static group organization as a variable-sized vector bin packing problem, and the subsequent dynamic group organization problem as an online multidimensional knapsack problem. Through extensive simulations driven by a large amount of real usage traces from a Google cluster, we evaluate the potential cost reduction achieved by\n            <jats:italic>Cocoa<\/jats:italic>\n            . We show that through the effective combination and interaction of the proposed static and dynamic group organization strategies,\n            <jats:italic>Cocoa<\/jats:italic>\n            greatly outperforms the existing cloud workload consolidation mechanism, substantiating the feasibility of group buying in cloud computing.\n          <\/jats:p>","DOI":"10.1145\/3022876","type":"journal-article","created":{"date-parts":[[2017,2,10]],"date-time":"2017-02-10T13:28:54Z","timestamp":1486733334000},"page":"1-31","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":14,"title":["Cocoa"],"prefix":"10.1145","volume":"2","author":[{"given":"Xiaomeng","family":"Yi","sequence":"first","affiliation":[{"name":"Key Laboratory of Services Computing Technology and System, Ministry of Education, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China"}]},{"given":"Fangming","family":"Liu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Services Computing Technology and System, Ministry of Education, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China"}]},{"given":"Di","family":"Niu","sequence":"additional","affiliation":[{"name":"University of Alberta, Alberta, Canada"}]},{"given":"Hai","family":"Jin","sequence":"additional","affiliation":[{"name":"Key Laboratory of Services Computing Technology and System, Ministry of Education, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China"}]},{"given":"John C. S.","family":"Lui","sequence":"additional","affiliation":[{"name":"The Chinese University of Hong Kong, N.T, Hong Kong"}]}],"member":"320","published-online":{"date-parts":[[2017,2,7]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Amazon. 2014. EC2 Spot Instance Pricing. Retrieved from http:\/\/aws.amazon.com\/ec2\/spot\/pricing\/.  Amazon. 2014. EC2 Spot Instance Pricing. Retrieved from http:\/\/aws.amazon.com\/ec2\/spot\/pricing\/."},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1287\/opre.46.3.316"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/cpe.1867"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2012.240"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2523616.2523637"},{"key":"e_1_2_1_6_1","unstructured":"J. Wilkes C. Reiss and J. Hellerstein. 2011. Google Cluster-Usage Traces. Retrieved from http:\/\/code.google.com\/p\/googleclusterdata\/.  J. Wilkes C. Reiss and J. Hellerstein. 2011. 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