ROGI: Partial Computation Offloading and Resource Allocation in the Fog-Based IoT Network Towards Optimizing Latency and Power Consumption

Fog computing has risen into a popular topic in recent years with the idea of deploying computation and communication closer to end-users. The capability of the fog model to face serious challenges like high latency and power consumption is of paramount research significance, notably in the context of the Internet of Things (IoT), given the volume and requirements of IoT applications. Accordingly, issues such as using the capacity of the fog layer maximally, minimizing latency while maintaining reliability, and efficiently distributing the workload across the network can be well explored. This motivated us to propose a scheme for pa r tial computation offloading and res o urce allocation in the fo g -based IoT network with the goal of opt i mizing latency and power consumption (ROGI). In this research, the nodes in all network layers are involved in processing the workload. Also, the power consumption in the end-users layer is reduced. Additionally, the fog nodes collaborate to improve system reliability and provide more resources for handling users’ requests. Furthermore, the concept of partial offloading is adopted, which would potentially lead to higher flexibility in resource management and provide the opportunity to leverage more resources in each layer of IoT architecture. Moreover, the whole model is decomposed into three problems, each of which is solved via optimization techniques. Extensive simulations are carried out to show the performance of the proposed scheme.