An Efficient Approach to Reduce Energy Consumption in a Fog Computing Environment Using a Moth Flame Optimization Algorithm

After decades of growth in the computer computing field, cyber-physical systems (CPS), a combination of physical and tangible hardware and virtual and supernatural tools and concepts, distributed. Today, fog and cloud computing are the most complex cyber-physical systems available. Theretofore, the cloud data centers developed to provide the resources needed by users, home, and industrial businesses. Cloud computing has provided the possibility of providing services near the occurrence of requests with processing in proximity (PP). However, edge or fog computing will supply a possible solution to improve the quality of service delivery compared to using cloud computing. Applications in cyber-physical fog systems utilize different services provided by diverse resources in fog colonies based on criteria and restriction rules. Since internet of things (IoT) applications executed in real-time and sensitive to time, the problem of delay in providing service to application requests in cloud computing distributed resources is very challenging. Fog computing supply an ideal platform for CPSs with fully geographically distributed features. At first, by placing services on resources are located in the edge layer, the cloud decrease the volume of requests sent to the cloud. Moreover, the response and the average delay time be solved in the proposed method. As a result, it makes the problem of placing services in cloud computing more complicated than in other areas like cloud computing and standard distributed systems. In addition, to balance the load and ensure the quality of services, requested services in the fog system can be freely processed by any of the resources (nodes) available in the fog computing. According to the characteristics of the geographic distribution of fog nodes, the complexity of placing services to provide services to reduce energy consumption will be very high. In this study, we offer a solution based on the meta-heuristic algorithm of moth flame optimization (MFO) to place efficient energy and efficient delay of IoT services. The simulation results with iFogSim have revealed that the performance of the suggested solution has enhanced by 21% compared to the basic solutions in terms of energy consumption and service delivery delay by 15%.