Fog computing is known as a new computing technology where it covers cloud computing shortcomings in term of delay. This is a potential for running IoT applications containing multiple services taking benefit of closeness to fog nodes near to devices where the data are sensed. This article formulates service placement issue into an optimization problem with total power consumption minimization inclination. It considers resource utilization and traffic transmission between different services as two prominent factors of power consumption, once they are placed on different fog nodes. On the other hand, placing all of the services on the single fog node owing to power reduction reduces system reliability because of one point of failure phenomenon. In the proposed optimization model, reliability limitations are considered as constraints of stated problem. To solve this combinatorial problem, an energy-aware reliable service placement algorithm based on whale optimization algorithm (ER-SPA-WOA) is proposed. The suggested algorithm was validated in different circumstances. The results reported from simulations prove the dominance of proposed algorithm in comparison with counterpart state-of-the-arts. پرونده مقاله

Cloud computing is a distributed environment for providing services over the Internet. Load balancing of computing resources has emerged as a crucial element in this industry as a result of the expanding use of cloud computing and the expectations of customers to receive more services and better outcomes. The workload and system behavior of cloud computing are quite dynamic. And this can cause the resources in the data center to be overloaded. Ultimately, a load imbalance in some data center resources could result in increased energy use, decreased performance, and resource waste. Response time, expense, throughput, performance, and resource usage are among the quality of service indicators that load balancing can enhance. In this article, we analyze and evaluate scheduling and resource allocation methods with a view to load balancing, review the most recent approaches, and give a classification of these algorithms. Also, several significant problems and difficulties with cloud load balancing will be discussed in an upcoming study to create new algorithms. پرونده مقاله