A goal programming based energy efficient resource allocation in data centers
Tóm tắt
Từ khóa
Tài liệu tham khảo
Symantec corporation. Symantec state of the data center report, available online at: http://www.symantec.com/content/en/us/about/media/SOTDC_report_2007.pdf
United States air force satellite control network data, available online at: http://www.cs.colostate.edu/sched/index.html
Abdelzaher TF, Lu C (2001) Schedulability analysis and utilization bounds for highly scalable real-time services. In: 7th real-time technology and applications symposium, p 15
Bansal N, Kimbrel T, Pruhs K (2004) Dynamic speed scaling to manage energy and temperature. In: 45th annual IEEE symposium on foundations of computer science, pp 520–529
Bianchini R, Rajamony R (2004) Power and energy management for server systems. IEEE Comput 37(11):68–74
Bunde DP (2006) Power-aware scheduling for makespan and flow. In: 8th ACM symposium on parallelism in algorithms and architectures, pp 190–196
Chen J, Dubois M, Stenström P (2007) Simwattch: Integrating complete-system and user-level performance and power simulators. IEEE MICRO 27(4):34–48
Chung E-Y, Benini L, Bogiolo A, De Micheli G (1999) Dynamic power management for non-stationary service requests. In: Conference on design, automation and test in Europe, p 18
Dyer JS (1972) Interactive goal programming. Oper Res 19:62–70
Guzek M, Pecero JE, Dorronsoro B, Bouvry P, Khan SU (2010) A cellular genetic algorithm for scheduling applications and energy-aware communication optimization. In: International conference on high performance computing & simulation HPCS, pp 241–248
Heath T, Diniz B, Carrera EV, Meira W Jr, Bianchini R (2005) Energy conservation in heterogeneous server clusters. In: 10th ACM SIGPLAN symposium on principles and practice of parallel programming, pp 186–195
Hwang CL, Masud ASM (1979) Multiple objective decision making—methods and applications: A state-pf-the-art survey. Springer, Berlin
Irani S, Gupta R, Shukla S (2002) Competitive analysis of dynamic power management strategies for systems with multiple power savings states. In: Conference on design, automation and test in Europe, p 117
Khan SU (2009) A game theoretical energy efficient resource allocation technique for large distributed computing systems. In: International conference on parallel and distributed processing techniques and applications (PDPTA), pp 48–54
Khan SU (2009) A multi-objective programming approach for resource allocation in data centers. In: International conference on parallel and distributed processing techniques and applications (PDPTA), pp 152–158
Khan SU, Ahmad I (2009) A cooperative game theoretical technique for joint optimization of energy consumption and response time in computational grids. IEEE Trans Parallel Distrib Syst 20(3):346–360
Kliazovich D, Bouvry P, Khan SU (2010) DENS: Data center energy-efficient network-aware scheduling. In: ACM/IEEE international conference on green computing and communications (GreenCom), pp 69–75
Li L, Lai KK (2000) A fuzzy approach to the multiobjective transportation problem. Comput Oper Res 27(1):43–57
Liang T-F (2008) Fuzzy multi-objective production/distribution planning decisions with multi-product and multi-time period in a supply chain. Comput Ind Eng 55(3):676–694
Lorch JR, Smith AJ (2001) Improving dynamic voltage scaling algorithms with pace. In: 2001 ACM SIGMETRICS international conference on measurement and modeling of computer systems, pp 50–61
Luenberger D (1984) Linear and nonlinear programming. Addison-Wesley, Reading
Mejia-Alvarez P, Levner E, Mossé D (2004) Adaptive scheduling server for power-aware real-time tasks. ACM Trans Embed Comput Syst 3(2):284–306
Nathuji R, Isci C, Gorbatov E (2007) Exploiting platform heterogeneity for power efficient data centers. In: 4th international conference on autonomic computing, p 5
Pinel F, Pecero J, Bouvry P, Khan SU (2010) Memory-aware green scheduling on multi-core processors. In: 39th IEEE international conference on parallel processing (ICPP), pp 485–488
Pinheiro E, Bianchini R, Carrera EV, Heath T (2001) Load balancing and unbalancing for power and performance in cluster-based systems. In: Workshop on compilers and operating systems for low power
Rusu C, Ferreira A, Scordino C, Watson A (2006) Energy-efficient real-time heterogeneous server clusters. In: 12th IEEE real-time and embedded technology and applications symposium, pp 418–428
Schrage L (1986) Linear, integer, and quadratic programming with LINDO. Scientific Press, South San Francisco
Stefanescu A, Stefanescu M (1984) The arbitrated solution for multi-objective convex programming. Rev Roum Math Pures Appl 29:593–598
Subrata R, Zomaya AY, Landfeldt B (2010) Cooperative power-aware scheduling in grid computing environments. J Parallel Distrib Comput 70(2):84–91
Wallenius J (1975) Comparative evaluation of some interactive approaches to multicriterion optimization. Manag Sci 21:1387–1396
Weiser M, Welch B, Demers A, Shenker S (1994) Scheduling for reduced cpu energy. In: 1st USENIX conference on operating systems design and implementation, p 2
Yu Y, Prasanna VK (2002) Power-aware resource allocation for independent tasks in heterogeneous real-time systems. In: 9th international conference on parallel and distributed systems, p 341