计算机科学

计算机科学 ›› 2021, Vol. 48 ›› Issue (6A): 383-386.doi: 10.11896/jsjkx.200900212

• 网络&通信 • 上一篇    下一篇

高速公路中的移动边缘计算研究

宋海宁1, 焦健1, 刘永2   

  1. 1 北京信息科技大学计算机学院 北京100101
    2 百融云创科技股份有限公司 北京100102
  • 出版日期:2021-06-10 发布日期:2021-06-17
  • 通讯作者: 焦健(jiaojian@bistu.edu.cn)
  • 作者简介:songhaining1997@sina.com
  • 基金资助:
    国家自然科学基金(61872044)

Research on Mobile Edge Computing in Expressway

SONG Hai-ning1, JIAO Jian1, LIU Yong2   

  1. 1 School of Computer Science,Beijing Information Science &Technology University,Beijing 100101,China
    2 Bai Rong Yun Chuang Technology Company Limited,Beijing 100102,China
  • Online:2021-06-10 Published:2021-06-17
  • About author:SONG Hai-ning,born in 1997,postgra-duate,is a member of China Computer Federation.Her main research interests include edge computing and network security.
    JIAO Jian,born in 1978,Ph.D,assistantprofessor,postgraduate supervisor,is a member of China Computer Federation.His main research interests include edge computing and network security.
  • Supported by:
    National Natural Science Foundation of China(61872044).

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摘要： 中国高速公路的建设使得目前在公路侧出现了大量计算设备,为在高速公路场景中使用移动边缘计算技术提供了可能。移动边缘计算能够在高速为车辆提供低延时、高带宽和可靠的计算服务,是实现交通智能化的重要手段。考虑到高速公路的特殊环境,文中研究了任务卸载和资源调度等关键技术并结合5G,建立了面向高速公路行车任务的移动边缘计算模型。针对不同种类的计算任务,设计了有效的任务卸载策略,提出一种动态融合的调度策略以实现高效的合理的资源调度,该策略结合了遗传算法和蚁群算法。为验证该模型的有效性,使用负载均衡度作为性能指标对其进行仿真实验。实验结果表明,该算法与同类算法相比能够有效减小负载差异,降低计算成本。

关键词: 负载均衡, 高速公路, 任务卸载, 移动边缘计算, 资源调度

Abstract: With the improvement of expressway construction,a large number of computing devices appear on both sides of the expressway.Based on this,mobile edge computing technology can be used in expressway scenarios.Mobile edge computing can provide vehicles with low latency,high bandwidth and reliable computing services on highways.It is also an important means to rea-lize intelligent transportation system.Considering the special environment of expressway,this paper focuses on the problems of task offloading and resource allocation.Combined with 5G mobile network,a mobile edge computing model for expresswaydri-ving task is established.An efficient and reasonable resource scheduling strategy for different kinds of computing tasksis designed.And a dynamic scheduling strategy is put forward,which combines genetic algorithm and ant colony algorithm.To verify the effectiveness of this model,load balancing is used as the performance index for the simulation experiment.The experimental results show that the proposed algorithm can effectively reduce the load gaps and the computing cost compared with similar algorithms

Key words: Expressway, Load balancing, Mobile edge computing, Resource allocation, Task offloading

中图分类号: 

  • TN929.5
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