Network Resource Allocation Algorithm Using Reinforcement Learning Policy-Based Network in a Smart Grid Scenario

• DOI: 10.3390/electronics12153330
• Publication Date: 2023-08-03T15:13:06Z
• Authors: Zhe Zheng; Yu Han; Yingying Chi; Fusheng Yuan; Wenpeng Cui; Hailong Zhu; Yi Zhang; Peiying Zhang
• Keywords: Virtual network

The exponential growth in user numbers has resulted an overwhelming surge data that the smart grid must process. To tackle this challenge, edge computing emerges as a vital solution. However, current heuristic resource scheduling approaches often suffer from fragmentation and consequently get stuck local optimum solutions. This paper introduces novel network allocation method for multi-domain virtual networks with support of computing. approach entails modeling model formulating constraints specific to network. Secondly, policy is constructed reinforcement learning (RL) optimal strategy obtained under premise ensuring requirements. In experimental section, our algorithm compared three other algorithms. results show average increase 5.30%, 8.85%, 15.47% 22.67% long-term revenue–cost ratio, request acceptance revenue CPU utilization, respectively.