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Minimizing protection switching time in transport networks with shared mesh protection
International Journal of Network Management ( IF 1.5 ) Pub Date : 2020-08-20 , DOI: 10.1002/nem.2136
Choong‐hee Cho 1 , Jeong‐dong Ryoo 1
Affiliation  

Shared mesh protection (SMP) protects service traffic on a working path and requires coordinated use of the shared resources on a protection path when the traffic is routed through the protection path. If there are many intermediate nodes on the protection path, the delay caused by the coordination at each node increases the protection switching time, resulting in losing more traffic. Considering the capacity of a link and the bandwidth required by the protection paths using that link, it appears that coordination is necessary. However, looking closely at the relationships with other links and their protection paths, there exist resources that may require no coordination at all. This observation leads to the fact that protection switching time can decrease when bypassing some intermediate nodes for coordination. This fact introduces an optimization problem, in which the objective is to exclude these resources as much as possible from the set of resources for which coordination is required. A sub-problem is finding these excludable candidate resources. For both the main problem and the sub-problem, which are NP-hard, we propose a greedy algorithm and a branch-and-bound algorithm, respectively. The simulations show that the results using the proposed algorithms are near-optimal. Furthermore, in an actual topology configured with the SMP environment, the protection switching time is improved by excluding resources for which coordination is not required, compared to the existing Optical Transport Network (OTN) SMP mechanism.

中文翻译:

使用共享网状保护最大限度地缩短传输网络中的保护切换时间

共享网状保护 (SMP) 保护工作路径上的服务流量,并且当流量通过保护路径路由时,需要协调使用保护路径上的共享资源。如果保护路径上的中间节点较多,各节点协调造成的延迟会增加保护倒换时间,从而导致更多的流量丢失。考虑到链路的容量和使用该链路的保护路径所需的带宽,协调似乎是必要的。然而,仔细观察与其他链路及其保护路径的关系,存在可能根本不需要协调的资源。这一观察导致这样一个事实,即当绕过一些中间节点进行协调时,保护切换时间可以减少。这一事实引入了一个优化问题,其目标是从需要协调的资源集中尽可能多地排除这些资源。一个子问题是找到这些可排他的候选资源。对于NP-hard的主问题和子问题,我们分别提出了贪心算法和分支定界算法。仿真表明,使用所提出的算法的结果接近最优。此外,在配置了SMP环境的实际拓扑中,与现有的OTN SMP机制相比,通过排除不需要协调的资源来提高保护倒换时间。其目标是将这些资源尽可能多地排除在需要协调的资源集中。一个子问题是找到这些可排他的候选资源。对于NP-hard的主问题和子问题,我们分别提出了贪心算法和分支定界算法。仿真表明,使用所提出的算法的结果接近最优。此外,在配置了SMP环境的实际拓扑中,与现有的OTN SMP机制相比,通过排除不需要协调的资源来提高保护倒换时间。其目标是将这些资源尽可能多地排除在需要协调的资源集中。一个子问题是找到这些可排他的候选资源。对于NP-hard的主问题和子问题,我们分别提出了贪心算法和分支定界算法。仿真表明,使用所提出的算法的结果接近最优。此外,在配置了SMP环境的实际拓扑中,与现有的OTN SMP机制相比,通过排除不需要协调的资源来提高保护倒换时间。我们分别提出了贪心算法和分支定界算法。仿真表明,使用所提出的算法的结果接近最优。此外,在配置了SMP环境的实际拓扑中,与现有的OTN SMP机制相比,通过排除不需要协调的资源来提高保护倒换时间。我们分别提出了贪心算法和分支定界算法。仿真表明,使用所提出的算法的结果接近最优。此外,在配置了SMP环境的实际拓扑中,与现有的OTN SMP机制相比,通过排除不需要协调的资源来提高保护倒换时间。
更新日期:2020-08-20
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