Scheduling tasks in the cloud computing environment using the combination of metal melting algorithm and fuzzy theory

Resource scheduling is one of the most important tasks that is performed in distributed systems such as the cloud environment. On this basis, adopting a suitable method in scheduling can be considered an important matter. The dynamism and heterogeneity of resources in distributed systems causes the complexity of task scheduling. Reducing execution time and execution cost is one of the criteria that is always taken into consideration in all proposed methods for cloud scheduling. Recently, the use of intelligent methods, including the fuzzy system, in the scheduling of tasks in cloud computing has received a lot of attention. Uncertainty and prioritization of input parameters of fuzzy system are important features of fuzzy theory. In this article, a new hybrid scheduling method is presented based on the fuzzy system and the metal melting method, which assigns the requests sent by users to the most suitable source, taking into account criteria such as execution cost, execution time, and imbalance coefficient. The main purpose of the proposed plan is to assign the sent requests to the resources, taking into account the computing power of the resources, the bandwidth of the virtual machines, the delay of the lines between the resources and also the length of the requested work. These parameters are the inputs of the fuzzy system and resources are assigned to requests based on the output of the fuzzy system. The proposed method has been evaluated with CloudSim simulator and the results have been compared with other cloud scheduling methods under the same conditions. The results show that the proposed method improves the efficiency of resource scheduling in terms of total execution time, execution cost and imbalance coefficient.