Resource allocation algorithm for MEC systems with joint network slicing

A resource allocation algorithm for a mobile edge computing system utilizing joint network slicing is proposed to address issues related to energy consumption and delay within the mobile edge computing system. First, a mobile edge computing system model with joint network slicing is established, considering delay and energy consumption as the primary optimization objectives, while also taking into account system resource utilization comprehensively. Second, a resource allocation algorithm based on deep deterministic policy gradient is proposed, which jointly optimizes the computation offloading decision, CPU working frequency, and power allocation. It dynamically adjusts the offloading strategy of computation tasks and the allocation of device resources according to real-time environment information and user demand, in order to minimize system latency and energy consumption, achieving a balance between energy consumption and latency in the mobile edge computing system. The performance of the proposed algorithm has been verified, demonstrating that it balances system delay and energy consumption more effectively compared to traditional algorithms.