西安电子科技大学学报

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一种改进的网络鲁棒性与有效性增强方法

慕彩红1,2;柴文壹1,2;刘逸1;刘敬3   

  1. (1. 西安电子科技大学 电子工程学院,陕西 西安 710071;
    2. 西安电子科技大学 智能感知与图像理解教育部重点实验室,陕西 西安 710071;
    3. 西安邮电大学 电子工程学院,陕西 西安 710121)
  • 收稿日期:2017-07-19 出版日期:2018-08-20 发布日期:2018-09-25
  • 作者简介:慕彩红(1978-), 女, 副教授, E-mail: caihongm@mail.xidian.edu.cn
  • 基金资助:

    中央高校基本科研业务费专项资金资助项目(JB170204);国家自然科学基金资助项目(61672405, U1701267, 61573015, 61473215, 61773304);国家留学基金资助项目(201706965003, 201606965051)

Improved approach to enhancing the robustness and effectiveness of networks

MU Caihong1,2;CHAI Wenyi1,2;LIU Yi1;LIU Jing3   

  1. (1. School of Electronic Engineering, Xidian Univ., Xian 710071, China;
    2. Ministry of Education Key Lab. of Intelligent Perception and Image Understanding, Xidian Univ., Xian 710071, China;
    3. School of Electronic Engineering, Xian Univ. of Posts & Telecommunications, Xian 710121, China)
  • Received:2017-07-19 Online:2018-08-20 Published:2018-09-25

摘要:

针对无标度网络面临恶意攻击时的脆弱性问题,提出了一种改进的网络鲁棒性与有效性增强算法.首先,在已有鲁棒性指标和有效性指标的基础上,将两者合理地融合在一起构造了新的目标函数; 然后,利用高鲁棒性网络的类洋葱结构信息,构造了高效的启发式混合搜索算子,结合模拟退火算法并采用一种基于变化率的评价模型来迭代优化网络的结构,实现了对网络鲁棒性和有效性的同时优化.实验结果表明,该方法能够较好地同时提高网络的鲁棒性与有效性.

关键词: 鲁棒性, 有效性, 无标度网络, 模拟退火, 启发式方法

Abstract:

Focusing on the problem of the vulnerability for scale-free networks under malicious attacks, an improved approach is proposed to enhance the robustness and effectiveness of the networks. Based on the existing robustness index and effectiveness index, this paper presents a new object function by combining these two indexes together reasonably. Then taking the onion-like structure as the heuristic information, a heuristic mixed searching operator is constructed. By adopting the simulated annealing algorithm combined with the heuristic mixed searching operator and a novel evaluation model based on the rate of change, the network structure is optimized iteratively, resulting in a network with higher robustness and effectiveness. Experimental results show that this new approach can improve the robustness and effectiveness of the initial network simultaneously.

Key words: robustness, effectiveness, scale-free networks, simulated annealing, heuristic methods