{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T20:30:50Z","timestamp":1761597050249,"version":"3.38.0"},"reference-count":24,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2007,11,1]],"date-time":"2007-11-01T00:00:00Z","timestamp":1193875200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["The International Journal of High Performance Computing Applications"],"published-print":{"date-parts":[[2007,11]]},"abstract":"<jats:p> Users perceive varying levels of utility for each different job completed by the cluster. Therefore, there is a need for existing cluster resource management systems (RMS) to provide a means for the user to express its perceived utility during job submission. The cluster RMS can then obtain and consider these user-centric needs such as Quality-of-Service requirements in order to achieve utility-driven resource management and allocation. We advocate the use of computational economy for this purpose. In this paper, we describe an architectural framework for a utility-driven cluster RMS. We present a user-level job submission specification for soliciting user-centric information that is used by the cluster RMS for making better resource allocation decisions. In addition, we propose a dynamic pricing function that the cluster owner can use to determine the level of sharing within a cluster. Finally, we define two user-centric performance evaluation metrics: Job QoS Satisfaction and Cluster Profitability for measuring the effectiveness of the proposed pricing function in realizing utility-driven resource management and allocation. <\/jats:p>","DOI":"10.1177\/1094342007083776","type":"journal-article","created":{"date-parts":[[2007,10,29]],"date-time":"2007-10-29T14:19:04Z","timestamp":1193667544000},"page":"405-418","source":"Crossref","is-referenced-by-count":54,"title":["Pricing for Utility-Driven Resource Management and Allocation in Clusters"],"prefix":"10.1177","volume":"21","author":[{"given":"Chee","family":"Shin Yeo","sequence":"first","affiliation":[{"name":"GRID COMPUTING AND DISTRIBUTED SYSTEMS LABORATORY, DEPARTMENT OF COMPUTER\r                        SCIENCE AND SOFTWARE ENGINEERING, THE UNIVERSITY OF MELBOURNE, VIC 3010, AUSTRALIA"}]},{"given":"Rajkumar","family":"Buyya","sequence":"additional","affiliation":[{"name":"GRID COMPUTING AND DISTRIBUTED SYSTEMS LABORATORY, DEPARTMENT OF COMPUTER\r                        SCIENCE AND SOFTWARE ENGINEERING, THE UNIVERSITY OF MELBOURNE, VIC 3010,\r                        AUSTRALIA,"}]}],"member":"179","published-online":{"date-parts":[[2007,11,1]]},"reference":[{"key":"atypb1","first-page":"3","volume":"2","author":"Altair Grid","year":"2000","journal-title":"Release"},{"volume-title":"High Performance Cluster Computing: Architectures and Systems","year":"1999","author":"Buyya, R.","key":"atypb2"},{"volume-title":"Proc. of International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA 2000)","author":"Buyya, R.","key":"atypb3"},{"volume-title":"Proc. of 10th International Heterogeneous Computing Workshop (HCW 2001)","author":"Buyya, R.","key":"atypb4"},{"key":"atypb5","doi-asserted-by":"publisher","DOI":"10.1177\/109434200101500205"},{"key":"atypb6","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4419-8648-1_19"},{"volume-title":"Proc. of International 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