Hybrid traffic Offloading method for distributed edge computing in 6G networks

Nowadays, modern information technologies develop very fast. Thousands of new devices are added to the network daily, and along with that, network load and the quantity of handled information increase correspondingly. In this paper, we address the issue of High INC in MEC network task offloading and further propose a three-layer network structure of task offloading: the network consists not just of subscriber terminals, edge servers, and cloud storage but also network devices such as routers and switches. The systemic latency and hence energy consumption are what we are trying to minimize. This optimization problem can then be posed as a minimization problem of latency according to some criterion. One possible promising answer to such a question is the hybridization of the two approaches, namely, INC and MEC. This work intends to find out on which type of tasks MEC will execute locally and for which kind of tasks INC will be utilized. In this scenario, a dynamic threshold has been set multi-factor and all-around. Therefore, from the obtained simulation results, it is self-evident that the proposed INC-and MEC-supported task offloading scheme can guarantee a high convergence rate and behave the best among other benchmark approaches for the case of minimized system latency and EC