Network survivability modeling
Network survivability modeling
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DOI：
10.1016/j.comnet.2009.02.014
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发表时间：
2009-06
期刊：
影响因子：
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通讯作者：
P. Heegaard;Kishor S. Trivedi
中科院分区：
文献类型：
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作者：
P. Heegaard;Kishor S. Trivedi
电信网络中的关键服务应该连续提供，即使发生破坏、自然灾害或网络故障等不良事件。必须在对等节点之间提供具有一定性能保证的虚拟连接，例如最小吞吐量、最大延迟或丢失。虚拟连接、网络基础设施和业务平台的设计、建设和管理就是为了满足这些需求。在本文中，我们认为网络的生存能力，在网络基础设施和服务平台，可能是外部或内部的不良事件所造成的重大和轻微的故障。生存意味着提供的服务在出现故障时也符合要求。ANSI T1A1.2委员会定义了网络生存性，即从不良事件发生的瞬间到达到可接受性能水平的稳定状态的瞬态性能。本文讨论了在链路或节点失效情况下虚连接网络的生存性评估问题。我们开发了模拟和分析模型来交叉验证我们的假设。为了避免状态空间爆炸，同时解决大型网络，我们分解我们的模型首先在空间上独立研究节点，然后在时间上解耦我们的分析性能和恢复模型，这给了我们一个封闭的形式的解决方案。建模方法适用于小型和实际规模的网络的例子。定义了三种不同的场景，包括单链路故障、飓风灾害和系统大块的不稳定性（瞬时常见故障）。结果表明，在我们的模拟和解析近似的瞬态损耗和延迟性能之间有很好的对应关系。
Critical services in a telecommunication network should be continuously provided even when undesirable events like sabotage, natural disasters, or network failures happen. It is essential to provide virtual connections between peering nodes with certain performance guarantees such as minimum throughput, maximum delay or loss. The design, construction and management of virtual connections, network infrastructures and service platforms aim at meeting such requirements. In this paper we consider the network’s ability to survive major and minor failures in network infrastructure and service platforms that are caused by undesired events that might be external or internal. Survive means that the services provided comply with the requirement also in presence of failures. The network survivability is quantified as defined by the ANSI T1A1.2 committee which is the transient performance from the instant an undesirable event occurs until steady state with an acceptable performance level is attained. The assessment of the survivability of a network with virtual connections exposed to link or node failures is addressed in this paper. We have developed both simulation and analytic models to cross-validate our assumptions. In order to avoid state space explosion while addressing large networks we decompose our models first in space by studying the nodes independently and then in time by decoupling our analytic performance and recovery models which gives us a closed form solution. The modeling approaches are applied to both small and real-sized network examples. Three different scenarios have been defined, including single link failure, hurricane disaster, and instabilities in a large block of the system (transient common failure). The results show very good correspondence between the transient loss and delay performance in our simulations and in the analytic approximations.