A Novel Approach to Reducing Energy Consumption, Economic Savings, Service Quality Enhancement, and Resource Utilization in Cloud Data Centers

Cloud data centers often provide the infrastructure for millions of virtual machines in dynamic environments. Virtual machine deployment is a process where it is determined which virtual machines should be executed on which physical machines within the virtualized infrastructure. Given the randomness of customer requests, the virtual machine deployment issue must be formulated as a dynamic optimization problem. On the other hand, providers must be able to respond to virtual resource requests in complex dynamic cloud computing environments, considering service elasticity and overbooking physical resources. In this work, five experiments were designed and conducted for the two-stage optimization of such issues. In these experiments, after evaluating online heuristic algorithms, various overbooking protection coefficients, and different scaling methods, a non-deterministic formulation was considered for optimizing four objective functions (energy consumption, economic savings, service quality, and resource utilization). The experimental results, considering ۹۶ different scenarios, show that two of the online phase heuristic algorithms, taking into account a memetic algorithm for the offline phase, setting the overbooking protection coefficient to ۰.۷۵, and scaling the four objective functions based on the shortest Euclidean distance to the origin, yield the best performance.

کلیدواژه ها:

Virtual Machine Deployment ، optimization ، virtualization ، energy consumption ، Service Quality ، Data Centers ، Virtual Resources ، cloud computing