Network slicing resource allocation strategy based on joint optimization

Zaijian WANG; Huimin GU

doi:10.11959/j.issn.1000-436x.2023089

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Network slicing resource allocation strategy based on joint optimization

Correspondences | 更新时间：2024-06-06

- Network slicing resource allocation strategy based on joint optimization
- Journal on Communications Vol. 44, Issue 5, Pages: 234-245(2023)
- 作者机构：
  
  1. 安徽师范大学物理与电子信息学院，安徽芜湖 241002
  2. 安徽省智能机器人信息融合与控制工程实验室，安徽芜湖 241002
- 作者简介：
- 基金信息：
  
  The Natural Science Foundation of Anhui Province(2008085MF222)
- DOI：10.11959/j.issn.1000-436x.2023089
  CLC： TN929.5
- Online First：2023-05，
  
  Published：25 May 2023
- 稿件说明：
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Zaijian WANG, Huimin GU. Network slicing resource allocation strategy based on joint optimization[J]. Journal on Communications, 2023, 44(5): 234-245.
DOI：

Zaijian WANG, Huimin GU. Network slicing resource allocation strategy based on joint optimization[J]. Journal on Communications, 2023, 44(5): 234-245. DOI： 10.11959/j.issn.1000-436x.2023089.

摘要

为解决5G网络中各类应用差异性大对通信需求侧重点不同造成的网络资源利用率低的问题，提出一种基于联合优化的网络切片资源分配策略，旨在通过综合考虑切片间资源分配和切片内资源调度问题，最大化网络资源利用率和网络收益。首先，在切片间资源分配问题中定义一个切片用户平均满意度函数，基于切片用户数量、切片调度时延以及切片优先级等约束，提出基于用户服务质量（QoS）的比例公平资源分配算法，以权衡各切片之间的公平性和用户需求。其次，在切片内资源调度问题中引入服务降级和资源迁移函数，针对拥塞和非拥塞2 种情况为内部接入用户和外部接入用户分别建立价格模型。基于所提价格模型建立基站与用户之间的Stackelberg博弈，并采用一种低复杂度的全局搜索算法求解该博弈的最佳响应，使基站效用和用户效用最优。仿真结果表明，所提策略能够有效提高资源利用率和网络收益，并降低网络拥塞，较好地实现资源分配的公平性。

Abstract

To improve network resource utilization that was decreased by different applications with different requirements in 5G networks

a network slicing resource allocation strategy based on joint optimization was proposed

which was utilized to maximize both network resource utilization and network revenue by comprehensively considering in tra-slice and inter-slice resource schedule.Firstly

the user’s average satisfaction function was defined in the inter-slicing resource allocation problem.Furthermore

in terms of the number of users

slicing schedule delay and priority

a proportional fair resource allocation algorithm based on quality of service (QoS) was proposed

which was employed to achieve the best tradeoff between fairness and the users’ requirements among slices.Secondly

after two functions (service degradation and resource migration) were introduced in the inter-slice resource schedule problem

two price models were established for internal access users and external access users respectively

where congestion and non-congestion conditions were analyzed.According to the proposed price models

a Stackelberg game between the base station and users was constructed

and a global search algorithm with low complexity was leveraged to obtain the best response of the game

where the best tradeoff between the base station revenue and user utility was obtained.Simulation results show that the proposed strategy can effectively improve resource utilization and network revenue while reducing network congestion.Therefore

it can better realize fairness in resource allocation.

关键词

Keywords

references

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