Dynamic resource scheduling strategy for 5G network slicing based on improved greedy algorithm

Qiang CHEN; Caixia LIU; Lingshu LI

doi:10.11959/j.issn.2096-109x.2018057

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Dynamic resource scheduling strategy for 5G network slicing based on improved greedy algorithm

Papers | 更新时间：2024-06-03

- Dynamic resource scheduling strategy for 5G network slicing based on improved greedy algorithm
- Chinese Journal of Network and Information Security Vol. 4, Issue 7, Pages: 60-68(2018)
- 作者机构：
  
  1. 国家数字交换系统工程技术研究中心，河南郑州450002
  2. 移动互联网安全技术国家工程实验室，北京100876
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-109x.2018057
  CLC： TN929.5
- Online First：2018-07，
  
  Published：15 July 2018
- 稿件说明：
移动端阅览
Qiang CHEN, Caixia LIU, Lingshu LI. Dynamic resource scheduling strategy for 5G network slicing based on improved greedy algorithm[J]. Chinese Journal of Network and Information Security, 2018, 4(7): 60-68.
DOI：

Qiang CHEN, Caixia LIU, Lingshu LI. Dynamic resource scheduling strategy for 5G network slicing based on improved greedy algorithm[J]. Chinese Journal of Network and Information Security, 2018, 4(7): 60-68. DOI： 10.11959/j.issn.2096-109x.2018057.

摘要

为了解决移动通信网络中资源利用率和用户体验质量的瓶颈问题，5G 引入网络切片来应对用户的巨大资源需求。提出了一种基于改进式贪婪算法的网络切片动态资源调度策略，在切片调度和用户调度阶段，设计了一种两层模型，即切片−用户模型，并且结合改进式贪婪算法，使服务权重值最大的切片和优先级最高的用户组合，完成相应的服务。该方法是将全局资源最优问题简化为规模更小的子问题，通过每一次切片和用户的最佳组合，从而使整个系统的资源和用户的体验质量达到最优。Matlab的仿真结果表明，基于改进式贪婪算法的网络切片动态资源调度策略在系统剩余资源利用率、系统达到平均的QoE水平、系统吞吐量等方面都显优于现行的资源调度策略，能够更好地满足用户的需求。

Abstract

Dealing with the problem of network resource utilization and the user experience

the network slicing as a novel technology is adopted in 5G.A dynamic resource scheduling strategy for 5G network slicing based on improved greedy algorithm was proposed.In the process of slice scheduling and user scheduling

a two layer slice-user model combined with the improved greedy algorithm was proposed

which ensured the slices with maximum service weight and the highest priority users combined together to complete corresponding services.The global resource optimal problem was transformed into a smaller sub problem by means of the optimal combination of each slice and every user

which improved the network resource utilization and the user experience in the meantime.The Matlab simulation results show that compared with existing algorithms

the proposed method could effective improve the system remaining resource utilization

system average QoE level and system throughput.

关键词

Keywords

references

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