J4 ›› 2015, Vol. 42 ›› Issue (1): 16-22.doi: 10.3969/j.issn.1001-2400.2015.01.003

• 研究论文 • 上一篇    下一篇

一种粒子群优化的用户优先级虚拟网络映射算法

常磊1;顾华玺1;张之义2;余晓杉1;赵彦1   

  1. (1. 西安电子科技大学 综合业务网理论及关键技术国家重点实验室,陕西 西安  710071;
    2. 中国电子科技集团公司第五十四研究所,河北 石家庄  050000)
  • 收稿日期:2013-09-11 出版日期:2015-02-20 发布日期:2015-04-14
  • 通讯作者: 常磊
  • 作者简介:常磊(1987-),男,西安电子科技大学硕士研究生,E-mail:07818654@163.com.
  • 基金资助:

    国家自然科学基金资助项目(61472300);中央高校基本业务费资助项目(JB142001-5);高等学校学科创新引智计划资助项目(B08038)

Particle swarm optimization user-priority virtual network embedding algorithm

CHANG Lei1;GU Huaxi1;ZHANG Zhiyi2;YU Xiaoshan1;ZHAO Yan1   

  1. (1. State Key Lab. of Integrated Service Networks, Xidian Univ., Xi'an  710071, China;
    2. The 54th Research Institute of China Electronics Technology Group Corporation, Shijiazhuang  050000, China)
  • Received:2013-09-11 Online:2015-02-20 Published:2015-04-14
  • Contact: CHANG Lei

摘要:

以底层网络资源利用率最大化为目标,对控制转发分离网络建立基于“资源抢占+重映射”的用户优先级虚拟网络映射整数线性规划模型,并提出了一种改进离散粒子群算法来解决虚拟网络映射问题.该算法的粒子进化更具方向性,同时引进不同粒子位置互斥因子,解决粒子群算法易早熟陷入局部最优解的缺陷.最后通过仿真实验从节点资源利用率、链路资源利用率、一般虚拟网络接受率、平均跳数和长期运营收益成本比等方面,将改进离散粒子群算法与贪婪算法和二进制离散粒子群算法对比,验证了改进离散粒子群算法的高性能.

关键词: 控制转发分离网络构架, 虚拟网络映射, 离散粒子群算法, 用户优先级

Abstract:

In the forwarding and control separation network, we model the user-priority virtual network embedding problem as an integer linear programming, which is achieved with resource grabbing and re-mapping aiming at maximizing the resource utilization of the substrate physical network. And we propose a modified discrete particle swarm optimization algorithm (M_DPSO) for short to solve the VN embedding problem. In the M_DPSO, the particle evolves more directionally, and the mutually exclusive factor of different particle positions is introduced to resolve the problem of premature and easily becoming local optimal solution. Finally, the performance parameters, including node resource utilization, link resource utilization, the VN accept rate, the average jump number and the long-term operators benefit cost ratio, are evaluated by emulation experiments. In contrast to the greedy algorithm and binary particle swarm optimization algorithm, the M_DPSO is verified to be of high performance.

Key words: forwarding and control separation network, virtual network embedding, discrete particle swarm optimization, user-priority

中图分类号: 

  • TP393
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