Optimized Scheduling for Cost and Energy Consumption Minimization in Cloud Computing Networks based on Fuzzy- Particle Swarm Optimization Algorithm

This paper first examines the existing approaches to task planning and resources allocation in the cloud infrastructure and evaluates their advantages and disadvantages. Subsequently, a hybrid algorithm (Fuzzy-PSO) is presented to allocate tasks to resources and reduce runtime. In this research, the optimal particle swarm algorithm for scheduling tasks between data centers is used which has shown great success in solving continuous optimization problems. Fuzzy logic is also used to determine the competence of nodes in this algorithm. This algorithm assigns tasks to processing resources in a way that the workload is distributed evenly over the processing resources to maximize the efficiency of available processing resources and minimize runtime and total cost.

کلیدواژه ها:

Cloud Computing Network ، Resource Scheduling ، Load Balance ، Fuzzy Logic ، Particle Swarm Optimization Algorithm