| 面向多租户网络资源分配的博弈优化策略 |
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| 引用本文： | 郑振康,周金和. 面向多租户网络资源分配的博弈优化策略[J]. 计算机工程, 2022, 48(5): 170-177. DOI: 10.19678/j.issn.1000-3428.0061889 |
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| 作者姓名： | 郑振康 周金和 |
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| 作者单位： | 北京信息科技大学 信息与通信工程学院, 北京 100101 |
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| 基金项目： | 国家自然科学基金“5G超密集接入网智能动态资源分配及其优化方法研究”（61872044）； |
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| 摘 要： | 为了应对5G及未来网络中用户间差异化的服务需求，改善多租户网络切片资源利用率低和部署成本高的问题，提出一种基于多租户网络资源分配的博弈优化策略。在多租户网络中，网络切片租户（NSTs）租用基础设施提供商基站的无线频谱资源，将接入服务切片构建为网络切片即服务，为用户提供网络接入服务。将NSTs和用户的关系建模为一个多主多从的Stackelberg博弈，引入切片流行度和服务命中率指标，建立博弈双方的策略空间和收益函数，并证明NSTs的切片订购策略存在唯一的纳什均衡。通过逆向归纳法分析博弈模型，提出一种分布式迭代算法求得用户的最优吞吐量需求以及NSTs的最优切片定价。仿真结果表明，与传统考虑切片资源分配的优化策略对比，基于多租户网络资源分配的博弈优化策略能够有效提高资源利用率和用户满意度，并降低切片部署能耗，较好地实现频谱带宽资源的合理分配。
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| 关 键 词： | 多租户网络 网络切片 资源分配 接入服务 Stackelberg博弈 纳什均衡 |
| 收稿时间： | 2021-06-09 |
| 修稿时间： | 2021-07-08 |
Game Optimization Strategy for Multi-tenant Network Resource Allocation |
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| ZHENG Zhenkang,ZHOU Jinhe. Game Optimization Strategy for Multi-tenant Network Resource Allocation[J]. Computer Engineering, 2022, 48(5): 170-177. DOI: 10.19678/j.issn.1000-3428.0061889 |
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| Authors: | ZHENG Zhenkang ZHOU Jinhe |
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| Affiliation: | School of Information and Communication Engineering, Beijing Information Science and Technology University, Beijing 100101, China |
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| Abstract: | To cope with the differentiated service requirements among users in 5G and future networks and to ameliorate the problems of low resource utilization and high deployment costs for multi-tenant network slicing, we propose a game optimization strategy for multi-tenant network resource allocation.In a multi-tenant network, Network Slice Tenants(NSTs) lease the wireless spectrum resources of the base stations of an infrastructure provider and construct access service slices as network slices to provide users with network access services.First, this study modeled the relationship between NSTs and users as a multi-master multi-slave Stackelberg game.We introduced slice popularity and service hit rate metrics, constructed a strategy space and profit function for both players, and proved that there is a unique Nash equilibrium between users after NSTs have made strategic decisions.Finally, this study analyzed the proposed game model through reverse induction.We propose a distributed iterative algorithm to obtain the optimal throughput demand of users and optimal slice pricing for NSTs.Simulation results demonstrate that compared to the traditional optimization strategy considering slice resource allocation, our strategy can effectively improve resource utilization and user satisfaction while reducing the energy consumption of slice deployment.Therefore, it can better realize the reasonable allocation of spectrum-bandwidth resources. |
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| Keywords: | multi-tenant network network slice resource allocation access services Stackelberg game Nash equilibrium |
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