Efficient Orchestration of Virtualization Resource in RAN Based on Chemical Reaction Optimization and Q-Learning
| Autor: | Wenyong Wang, Yu Liang Tang, Wei Ni, Lei Wang, Sai Zou |
|---|---|
| Rok vydání: | 2022 |
| Předmět: |
Radio access network
Computer Networks and Communications Computer science Heuristic (computer science) Distributed computing Access method Q-learning Particle swarm optimization Virtualization computer.software_genre Computer Science Applications Hardware and Architecture Signal Processing Genetic algorithm Orchestration (computing) computer Information Systems |
| Zdroj: | IEEE Internet of Things Journal. 9:3383-3396 |
| ISSN: | 2372-2541 |
| Popis: | Virtualized network function (VNF) orchestration dynamically deploys network slices, which provides an effective means of customized service provision. To achieve a realistic and comprehensive perspective of the decision process for customized service provision, we propose a virtualized resource orchestration strategy in radio access network (RAN) of Internet of things (Iots) based on chemical reaction optimization (CRO). Specifically, we apply particle swarm optimization (PSO), a Gaussian process, random walk model, and Q-learning to enhance the CRO algorithm to quickly obtain the approximate optimal solution for the proposed CRO-based resource orchestration strategy (CROROS). Simulation results show that, compared with existing access methods, CROROS can reduce the service rejection rate of a virtualized radio access network and improve the utilization rate of network system resources. Compared with other heuristic algorithms (e.g., PSO, genetic algorithm (GA), and CRO), CROROS can accelerate the global approximate optimal solution and improve the approximate fitness of the approximate optimal solution within a specified time. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|