✦ LIBER ✦

Random walk immunization strategy on scale-free networks

✍ Scribed by Weidong Pei; Zengqiang Chen; Zhuzhi Yuan

Book ID: 107504704
Publisher: South China University of Technology and Academy of Mathematics and Systems Science, CAS
Year: 2009
Tongue: English
Weight: 228 KB
Volume: 7
Category: Article
ISSN: 1672-6340
DOI: 10.1007/s11768-009-6187-6

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Random walks and diameter of finite scal

Random walks and diameter of finite scale-free networks

✍ Sungmin Lee; Soon-Hyung Yook; Yup Kim 📂 Article 📅 2008 🏛 Elsevier Science 🌐 English ⚖ 498 KB

Imperfect targeted immunization in scale

Imperfect targeted immunization in scale-free networks

✍ Yubo Wang; Gaoxi Xiao; Jie Hu; Tee Hiang Cheng; Limsoon Wang 📂 Article 📅 2009 🏛 Elsevier Science 🌐 English ⚖ 987 KB

Scale-free networks are prone to epidemic spreading. To provide cost-effective protection for such networks, targeted immunization was proposed to selectively immunize the hub nodes. In many real-life applications, however, the targeted immunization may not be perfect, either because some hub nodes

Immunization of susceptible–infected mod

Immunization of susceptible–infected model on scale-free networks

✍ Wen-Jie Bai; Tao Zhou; Bing-Hong Wang 📂 Article 📅 2007 🏛 Elsevier Science 🌐 English ⚖ 340 KB

A highly clustered scale-free network ev

A highly clustered scale-free network evolved by random walking

✍ Qinghua Chen; Shenghui Chen 📂 Article 📅 2007 🏛 Elsevier Science 🌐 English ⚖ 369 KB

Random models of scale-free networks

✍ Xianmin Geng; Qiang Li 📂 Article 📅 2005 🏛 Elsevier Science 🌐 English ⚖ 203 KB

A packet routing strategy using neural n

A packet routing strategy using neural networks on scale-free networks

✍ Yuki Naganuma; Akito Igarashi 📂 Article 📅 2010 🏛 Elsevier Science 🌐 English ⚖ 379 KB

We propose a dynamic packet routing strategy by using neural networks on scale-free networks. In this strategy, in order to determine the nodes to which the packets should be transmitted, we use path lengths to the destinations of the packets, and adjust the connection weights of the neural networks