软件导刊2025，Vol.24Issue(6)：10-17,8.DOI:10.11907/rjdk.241389
面向车联网场景的网络切片效用最大化资源分配方案
A Network Slicing Utility Maximization Resource Allocation Scheme for Internet of Vehicles Scenarios
摘要
Abstract
5G network slicing technology is an important choice to meet the low latency and high reliability requirements of vehicle networking services.To meet the differentiated and diversified service needs of the Internet of Vehicles(IoV)business,design a resource allocation scheme for IoV network slicing based on maximizing network utility.This scheme defines a network utility function that considers the impact of vehicle mobility on network utility while balancing transmission rate and latency,and proposes a dual Sigmoid particle swarm algorithm based on dynamic memory.Among them,the dynamic memory bank increases population diversity by maintaining a dynamically updated memory bank,effectively avoiding the algorithm from falling into local optima too early;The dual Sigmoid function updates the inertia weight factor to solve problems such as uneven transitions before and after the algorithm.The simulation experiment results show that the proposed algorithm decreased the running time by 5.5%compared to the suboptimal algorithm,increases the fairness coefficient of resource allocation in the same scenario of vehicle networking network slicing by 9.62%,and improves network utility by 7.86%,providing a reference for improving the qual-ity of vehicle networking services.关键词
网络切片/车联网/粒子群算法/罚函数法/网络效用Key words
network slicing/Internet of Vehicles/particle swarm algorithms/penalty function method/network utility分类
信息技术与安全科学引用本文复制引用
鲍禹丞,窦海娥,姚继明,王磊..面向车联网场景的网络切片效用最大化资源分配方案[J].软件导刊,2025,24(6):10-17,8.基金项目
国家自然科学基金项目(62071255) （62071255）
江苏省重点研发计划项目(BE2023087) （BE2023087）
江苏省高等学校自然科学研究重大项目(20KJA510009) （20KJA510009）
