Energy-saving and security-enhanced task offloading strategies in D2D-integrated MEC networks

With the rapid development of the Internet of Things, the demand for low latency and efficient computation has increased significantly. Mobile edge computing (MEC) has become a key technology for improving the performance of Internet of Things (IoT) systems. In cellular networks, computation offloading through D2D communication between edge devices can effectively reduce task latency and improve energy efficiency. However, most of the existing works focus on energy efficiency and delay optimization and often ignores security issues. Hence, we study the D2D offloading problem of edge devices under centralized scheduling of MEC servers, and propose a risk assessment criterion based on security level to jointly optimize energy consumption and security. To solve the problem, it was first modeled as a Mixed-Integer Nonlinear Programming (MINLP) problem. By optimizing the constraints, the problem was transformed into an Integer Linear Programming (ILP) problem and the theoretical optimal solution was obtained. Considering the requirements of practical engineering applications, a low-complexity heuristic algorithm is designed. The proposed strategies can be widely used in D2D-Integrated MEC Networks to improve system energy efficiency and security.