网络与信息安全学报 ›› 2018, Vol. 4 ›› Issue (7): 60-68.doi: 10.11959/j.issn.2096-109x.2018057

• 论文 • 上一篇    下一篇

基于改进式贪婪算法的5G网络切片动态资源调度策略

陈强1,2,刘彩霞1,2,李凌书1,2   

  1. 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
  • 修回日期:2018-06-28 出版日期:2018-07-01 发布日期:2018-09-10
  • 作者简介:陈强(1993-),男,辽宁本溪人,国家数字交换系统工程技术研究中心硕士生,主要研究方向为新一代移动通信。|刘彩霞(1974-),女,山东烟台人,国家数字交换系统工程技术研究中心副教授,主要研究方向为移动通信网络、新型网络体系结构。|李凌书(1992-),男,湖北恩施人,国家数字交换系统工程技术研究中心博士生,主要研究方向为新型网络体系结构、网络空间安全。
  • 基金资助:
    国家高技术研究发展计划(“863”计划)基金资助项目(2014AA01A701);国家自然科学基金资助项目(61521003);科技部支撑计划基金资助项目(2014BAH30B01)

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

Qiang CHEN1,2,Caixia LIU1,2,Lingshu LI1,2   

  1. 1 National Digital Switching System Engineering and Technological R&D Center,Zhengzhou 450002,China
    2 National Engineering Laboratory for Mobile Network Security,Beijing 100876,China
  • Revised:2018-06-28 Online:2018-07-01 Published:2018-09-10
  • Supported by:
    The National High Technology Research and Development Program of China (863 Program)(2014AA01A701);The National Natural Science Foundation of China(61521003);Ministry of Science and Technology Support Plan(2014BAH30B01)

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。

关键词: 网络切片, 切片权重值, 用户优先级, 动态资源调度, 改进式贪婪算法

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.

Key words: network slicing, slicing weight value, user priority, dynamic resource scheduling, improved greedy algorithm

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