چكيده به لاتين
Abstract Many centralized data services are highly dependent on cloud data centers to reduce operating costs and resource sharing . In cloud data centers , a large number of virtual machines are assigned to physical servers to provide intensive data services by ensuring service quality . hence , the energy consumption in cloud data centers is increasing internationally with a very large scale . This is why there is a fundamental need to improve energy efficiency in such data centers using the integration of servers that aim at minimising the active physical machines at a data center . This reduces the energy consumption and thus reduce the consumption of carbon dioxide and prolong the network lifetime . however , some of the tasks have been done in the allocation of virtual machines to the physical machines , but these assignments have some challenges , such as taking advantage of the user 's benefit alongside the benefit of the suppliers . in this thesis , a method for positioning virtual machines on physical machines has been proposed to optimize energy consumption while observing the service quality parameters , and to consider the users and suppliers . for this purpose , we model the resource allocation problem using linear programming and to evaluate our proposed resource allocation method , we implemented the proposed model into CPLEX software and results show that the proposed model has improved about 50 % of energy consumption in terms of service availability conditions , which improves about 40 % of the delay in time of service delivery. keywords: cloud data centers , virtual machine placement , energy consumption , quality of Service , delay
