{"title":"Notice of Violation of IEEE Publication PrinciplesResource management and knapsack formulation in distributed multimedia networks","authors":"A. E. Lawabni, A. Tewfik","doi":"10.1109/GLOCOM.2005.1577660","DOIUrl":null,"url":null,"abstract":"In this paper, the problem of allocating multiple finite resources to satisfy the quality of service (QoS) needs of multiple applications along multiple QoS dimensions is presented. A mathematical model that captures the dynamics of such adaptive problem is presented. This model formulates the problem as a multiple-choice multidimensional 0-1 knapsack problem (MMKP), an NP-hard optimization problem. A heuristic algorithm is then proposed to solve the MMKP. Experimental results demonstrate that our proposed algorithm finds 96% optimal solutions on average, and outperforms other heuristic algorithms for MMKP. Furthermore, the time required is on average 50% to 70% less than that required by other benchmark heuristics. These two properties make this heuristic a strong candidate for use in real-time multimedia applications","PeriodicalId":319736,"journal":{"name":"GLOBECOM '05. IEEE Global Telecommunications Conference, 2005.","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"GLOBECOM '05. IEEE Global Telecommunications Conference, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GLOCOM.2005.1577660","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper, the problem of allocating multiple finite resources to satisfy the quality of service (QoS) needs of multiple applications along multiple QoS dimensions is presented. A mathematical model that captures the dynamics of such adaptive problem is presented. This model formulates the problem as a multiple-choice multidimensional 0-1 knapsack problem (MMKP), an NP-hard optimization problem. A heuristic algorithm is then proposed to solve the MMKP. Experimental results demonstrate that our proposed algorithm finds 96% optimal solutions on average, and outperforms other heuristic algorithms for MMKP. Furthermore, the time required is on average 50% to 70% less than that required by other benchmark heuristics. These two properties make this heuristic a strong candidate for use in real-time multimedia applications
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