An Optimized Method for Outsourcing and Computational Offloading in Resources Allocation to IoT Users in Fog computing

Fog computing is a method for improving cloud computations performance attempts to expand the internet of things processes and distribute cloud services in the network edge. this paper proposes a real-time outsourcing and offloading mechanism to optimize the cache and cpu consumption in resource allocation to iot users in a fog-based processing environment. based on this mechanism, the computations that require heavy processing are moved to the network edge, and computations with lower processing needs are processed inside user devices. according to the simulation results, the average users' average service latency in the proposed method spa-(offloading) for 200 users has been improved in the range of 0.8 to 0.6. in addition, the profits of cloud and fog service providers for 220 users are higher than other methods. also, the average system cost performance is evaluated, which is better than the other methods. the results show that this mechanism improves cache consumption, processing time, and optimal resource allocation to iot users.