Abstract
To provide users with on-demand computing and network resources while ensuring service quality, the concept of a computational power network has emerged. However, efficiently allocating these resources to achieve an optimal balance between system energy consumption and latency, as well as ensuring the security of the resource allocation process, remain significant challenges. To solve these challenges, this paper proposes a secure edge offloading optimization framework. Within this framework, we incorporate blockchain technology to record critical network information in blocks within the blockchain, thereby ensuring the security of resource allocation. Subsequently, we formulate a joint optimization problem aimed at optimizing network bandwidth, computational resources, and blockchain maintenance resources simultaneously to achieve the best possible balance between system latency and energy consumption. Given the complexity of the original problem, we decompose it into two subproblems and solve each using the Lagrange multiplier iterative algorithm. To validate the effectiveness of our proposed solution, we compare it with several baseline approaches, including those based on Particle Swarm Optimization (PSO) and reinforcement learning methods such as Proximal Policy Optimization (PPO). Simulation results demonstrate that our proposed scheme performs notably better in achieving an optimal balance between system energy consumption and latency.