LAUSR

Cloud computing is a popular and powerful paradigm for leasing IT services over the Internet. It allows sharing the resources among a large number of consumers. This requires allocating and releasing resources dynamically over time. Since resources are paid as are used, ensuring a better level of service is a challenge for cloud providers. They must provide enough resources to meet user needs with maintaining the quality of service. Therefore, QoS is a serious problem that arises during the dynamic management of heterogeneous resources. This type of problem can be resolved by minimizing execution time and resource reservation prices. It is necessary to integrate a new method well enough to improve the performance of the cloud, in this area. This article presents a dynamic resource allocation model for the cloud computing environment. In addition, we propose a meta-heuristic approach named Multi-Objectives Symbiotic Organism Search algorithm (MOSOS) for resource allocation. We specifically designed MOSOS to minimize both the makespan and cost. Simulation results revealed that MOSOS gave a better result compared to other methods. It shown significant adaptation with the dynamic change of the cloud, as well as minimizing the execution time. Hence, improving the QoS given to cloud users.