带内网络遥测的非重叠网络图覆盖算法

发布时间：2021-08-07 12:31

　　随着各种云服务的部署增加,今天的数据中心网络变得越来越大。随着网络规模的不断扩大,细粒度网络监控成为了网络可靠性和闭环流量控制的先决条件。然而,由于控制平面和数据平面之间的连续交互以及有限的CPU能力,这种监视机制是粗粒度的,并且导致在具有高密度数据中心网络的现代网络中无法很好地随剧烈变化的通信动态扩展。为了增加可扩展性,P4语言联盟（P4.org）提出了带内网络遥测（INT）机制,其提供实时数据平面监视网络。在本文中,我们提出了带内网络遥测的概念,并提出使用路由路径生成策略来解决问题。在WINT系统中,我们可以精确地控制每个探测路径,从而可以为非重叠INT路径生成一个多样的INT路径规划算法来覆盖整个网络拓扑图并确保路径数最小,并对算法运行是的复杂度进行详尽分析。在这里,我们首先提出一种基于深度优先搜索（DFS）的简单算法,该算法简单且省时。其次,我们提出了基于欧拉路径的算法来最优地生成具有最小路径数的非重叠INT路径。为了实现更好的负载平衡,经典数据中心中网络拓扑是兼容的,并且存在多种多路径拓扑模式。因此INNT路径非常适合在数据中心网络中部署。另外,仿真结果表明欧拉算法的执行时间... 

【文章来源】：北京邮电大学北京市 211工程院校 教育部直属院校

【文章页数】：60 页

【学位级别】：硕士

【文章目录】：
ABSTRACT
摘要
Chapter 1: Introduction
    1.1 Research Background
    1.2 Traditional networking
    1.3 Software-Defined Network(SDN)
        1.3.1 Control plane:
        1.3.2 Data plane:
    1.4 Active network
    1.5 OpenFlow
    1.6 Data plane programmability
    1.7 Contribution
    1.8 Summary
    1.9 Thesis Organization
Chapter 2: Software-defined networking for computer networking
    2.1 Overview of Software-Define Networking
        2.1.1 Intelligence and speed
        2.1.2 Easy network management:
        2.1.3 Multi-tenancy:
        2.1.4 Network Security
    2.2 Traditional vs Software Define Networking
    2.3 Software-Defined Networking Architecture
        2.3.1 Data layer/Infrastructure layer
        2.3.2 Control layer
        2.3.3 Application Layer
    2.4 Feature of SDN
    2.5 Open Flow
    2.6 Programmable Data plane
        2.6.1 Protocol Oblivious Forwarding
        2.6.2 P4 (Programming Protocol-Independent Packet Processing)
    2.7 Network wide telemetry in Data center network
        2.7.1 Tree based topologies
            Basic tree
            FatTree network topology
            Leaf-Spine network topology
    Summary
Chapter 3: Algorithm Design
    3.1 System Background:
    3.2 Challenging issue:
        3.2.1 Telemetry overhead
        3.2.2 Synchronized multi-path monitoring
    3.3 Problem statement:
    3.4 The Proposed Algorithms
    3.5 Depth-First Search algorithm
    3.6 Euler Trail based algorithm
        3.6.1 Algorithm Description
        3.6.2 Case study
        3.6.3 Run-time complexity analysis:
        3.6.4 Heuristic method for balanced path generation
    Summary
Chapter 4: Evaluation
    2.1 Experimental setting
    2.2 Experimental Results
        2.2.1 Number of generated INT path:
        2.2.2 Balanced and Unbalanced Path Generation:
        2.2.3 Telemetry Overhead:
        2.2.4 Execution time of path planning algorithms
    2.3 Network-wide telemetry in Data Center (DC) Network
Chapter 5: Conclusion
ACKNOWLEDGEMENT
REFERENCES



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