Computational Verification of Network Programs for Several OpenFlow Switches in Coq

被引:0
|
作者
Date, Hiroaki [1 ]
Yoshiura, Noriaki [1 ]
机构
[1] Saitama Univ, Dept Informat & Comp Sci, Sakura Ku, 255 Shimo Ookubo, Saitama, Japan
关键词
D O I
10.1007/978-3-319-42108-7_17
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
OpenFlow is a network technology that enables to control network equipment centrally, to realize complicated forwarding of packets and to change network topologies flexibly. In OpenFlow networks, network equipment is separated into OpenFlow switches and OpenFlow controllers. OpenFlow switches do not have controllers that usual network equipment has. OpenFlow controllers control OpenFlow switches. OpenFlow controllers are configured by programs. Therefore, network configurations are realized by software. This kind of software can be created by several kinds of programming languages. NetCore is one of them. The verification method of NetCore programs has been introduced. This method uses Coq, which is a formal proof management system. This method, however, deals with only networks that consist of one OpenFlow switch. This paper proposes a methodology that verifies networks that consist of several OpenFlow switches.
引用
收藏
页码:223 / 238
页数:16
相关论文
共 31 条
  • [21] Effects of initial settings on computational protein-ligand docking accuracies for several docking programs
    Oda, Akifumi
    Yamaotsu, Noriyuki
    Hirono, Shuichi
    Watanabe, Yurie
    Fukuyoshi, Shuichi
    Takahashi, Ohgi
    MOLECULAR SIMULATION, 2015, 41 (10-12) : 1027 - 1034
  • [22] Compatibility among Electrical Network Component Models of Computational Power System Analysis Programs
    Varricchio, S.
    Campello, T.
    IEEE LATIN AMERICA TRANSACTIONS, 2019, 17 (05) : 833 - 842
  • [23] Hybrid neural-network/computational programs to the analysis of elastic-plastic structures
    Waszczyszyn, Z
    Pabisek, E
    Mucha, G
    IUTAM SYMPOSIUM ON DISCRETIZATION METHODS IN STRUCTURAL MECHANICS, 1999, 68 : 189 - 198
  • [24] A Comparison of Verification Methods for Neural-Network Controllers Using Mixed-Integer Programs
    Dubach, Marcel
    Ducard, Guillaume J. J.
    2022 7TH INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION ENGINEERING, ICRAE, 2022, : 43 - 48
  • [25] SINGLE-EXCEPTION SORTING NETWORKS AND THE COMPUTATIONAL-COMPLEXITY OF OPTIMAL SORTING NETWORK VERIFICATION
    PARBERRY, I
    MATHEMATICAL SYSTEMS THEORY, 1990, 23 (02): : 81 - 93
  • [26] Verification of path computational performance in functionally distributed transport networking on next-generation network
    Ogawa, Entaro
    Aoki, Michihiro
    Chaki, Shinichiro
    2008 7TH ASIA-PACIFIC SYMPOSIUM ON INFORMATION AND TELECOMMUNICATION TECHNOLOGIES, 2008, : 81 - +
  • [27] Analysis of effective thermal conductivity of pebble bed by artificial neural network and its computational and experimental verification
    Sedani, Chirag
    Panchal, Maulik
    Tanna, Vipul
    Chaudhuri, Paritosh
    Gupta, Manoj Kumar
    CASE STUDIES IN THERMAL ENGINEERING, 2022, 40
  • [28] Neural transition system abstraction for neural network dynamical system models and its application to Computational Tree Logic verification
    Yang, Yejiang
    Wang, Tao
    Xiang, Weiming
    NEURAL NETWORKS, 2025, 186
  • [29] Exploring the Molecular Mechanism of Niuxi-Mugua Formula in Treating Coronavirus Disease 2019 via Network Pharmacology, Computational Biology, and Surface Plasmon Resonance Verification
    Wang, Wei
    Cao, Xu
    Cao, Yi-nan
    Liu, Lian-lian
    Zhang, Shu-ling
    Qi, Wen-ying
    Zhang, Jia-xin
    Yang, Xian-zhao
    Li, Xiao-ke
    Zao, Xiao-bin
    Ye, Yong-an
    CURRENT COMPUTER-AIDED DRUG DESIGN, 2024, 20 (07) : 1113 - 1129
  • [30] Computational exploration of cis-regulatory modules in rhythmic expression data using the "Exploration of Distinctive CREs and CRMs" (EDCC) and "CRM Network Generator" (CNG) programs
    Bekiaris, Pavlos Stephanos
    Tekath, Tobias
    Staiger, Dorothee
    Danisman, Selahattin
    PLOS ONE, 2018, 13 (01):