计算机科学 ›› 2020, Vol. 47 ›› Issue (7): 236-242.doi: 10.11896/jsjkx.190600022

• 计算机网络 • 上一篇    下一篇

拓扑综合评估与权值自适应的虚拟网络映射算法

史朝卫1, 孟相如2, 马志强2, 韩晓阳1   

  1. 1 空军工程大学研究生院 西安710051
    2 空军工程大学信息与导航学院 西安710077
  • 收稿日期:2019-06-05 出版日期:2020-07-15 发布日期:2020-07-16
  • 通讯作者: 孟相如(xrmeng@126.com)
  • 作者简介:cwshi0839@163.com
  • 基金资助:
    国家自然科学基金(61873277)

Virtual Network Embedding Algorithm Based on Topology Comprehensive Evaluation and Weight Adaptation

SHI Chao-wei1, MENG Xiang-ru2, MA Zhi-qiang2, HAN Xiao-yang1   

  1. 1 Schoolof Graduate,Air Force Engineering University,Xi’an 710051,China
    2 School of Information and Navigation,Air Force Engineering University,Xi’an 710077,China
  • Received:2019-06-05 Online:2020-07-15 Published:2020-07-16
  • About author:SHI Chao-wei,born in 1996,postgra-duate.His main research interests include network virtualization and so on.
    MENG Xiang-ru,born in 1963,Ph.D,professor,Ph.D supervisor.His main research interests include next generation internet and cyber security.
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (61873277)

摘要: 针对现有虚拟网络映射算法对节点拓扑特征考虑得不够全面、节点评价方式较为单一且指标权值不能根据网络环境自适应调整等问题,提出一种拓扑综合评估与权值自适应的虚拟网络映射算法。文中在节点映射阶段综合考虑节点中心度、就近度与邻近聚集度等拓扑属性,结合节点CPU与邻接带宽和等资源属性对节点进行多指标重要度排序,根据网络环境的变化利用熵权法自适应调整指标权值。仿真结果表明,相较于最新的和经典的虚拟网络映射算法,所提算法的映射成功率提高了2%~23%,长期平均收益开销比提升了3%~17%,且该算法对不同资源需求类型的虚拟网络请求都能保持良好性能。

关键词: 邻近聚集, 权值自适应, 熵权法, 拓扑综合评估, 虚拟网络映射

Abstract: The existing virtual network embedding algorithms do not consider the topological features of nodes comprehensively,the evaluation method of nodes is relative simple and the weights cannot be adaptively adjusted according to the network.To solve these problems,a virtual network embedding algorithm based on topology comprehensive evaluation and weight adaptation is proposed.In the node embedding stage,by considering the centrality,proximity and adjacent aggregation of nodes,this paper establishes a node multi-metric evaluation model combined with the node resource properties such as the node CPU and the sum of adjacent bandwidth.The weights are adjusted adaptively according to the change of network environment by using the entropy weight method.Simulation results show that compared with the latest and classical virtual network embedding algorithms,the acceptance ratio of the proposed algorithm is improved by 2%~23%,and the long-term average revenue-to-cost ratio is increased by 3%~17%.Moreover,the proposed algorithm can maintain good performance for different types of virtual network requests with different resource requirements.

Key words: Entropy weight method, Regional aggregation, Topology comprehensive evaluation, Virtual network embedding, Weight adaptation

中图分类号: 

  • TP393
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