Your browser doesn't support javascript.
loading
High-Speed Path Probing Method for Large-Scale Network.
Luo, Zhihao; Liu, Jingju; Yang, Guozheng; Zhang, Yongheng; Hang, Zijun.
Afiliação
  • Luo Z; College of Electronic Engineering, National University of Defense Technology, Hefei 230037, China.
  • Liu J; Cyberspace Security Situation Awareness and Evaluation Key Laboratory of Anhui Province, Hefei 230037, China.
  • Yang G; College of Electronic Engineering, National University of Defense Technology, Hefei 230037, China.
  • Zhang Y; Cyberspace Security Situation Awareness and Evaluation Key Laboratory of Anhui Province, Hefei 230037, China.
  • Hang Z; College of Electronic Engineering, National University of Defense Technology, Hefei 230037, China.
Sensors (Basel) ; 22(15)2022 Jul 28.
Article em En | MEDLINE | ID: mdl-35957205
In large-scale network topology discovery, due to the complex network structure and dynamic change characteristics, it is always the focus of network topology measurement to obtain as many network paths as possible in a short time. In this paper, we propose a large-scale network path probing approach in order to solve the problems of low probing efficiency and high probing redundancy commonly found in current research. By improving the packet delivery order and the update strategy of time-to-live field values, we redesigned and implemented an efficient large-scale network path probing tool. The experimental results show that the method-derived tool can complete path probing for a sample of 12 million/24 network address segments worldwide within 1 hour, which greatly improves the efficiency of network path probing. Meanwhile, compared to existing methods, the proposed method can reduce the number of packets sent by about 10% with the same number of network addresses found, which effectively reduces probing redundancy and alleviates the network load.
Assuntos
Palavras-chave

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Algoritmos Idioma: En Revista: Sensors (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Algoritmos Idioma: En Revista: Sensors (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China