SDSFLF: fault localization framework for optical communication using software digital switching network

C. Raju, S. Rajagopal, Kanagaraj Venusamy, K. Suriyan, Manjunathan Alagarsamy
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引用次数: 4

Abstract

Optical network is an emerging technology for data communication inworldwide. The information is transmitted from the source to destination through the fiber optics. All optical network (AON) provides good transmission transparency, good expandability, large bandwidth, lower bit error rate (BER), and high processing speed. Link failure and node failure haveconsistently occurred in the traditional methods. In order to overcome the above mentioned issues, this paper proposes a robust software defined switching enabled fault localization framework (SDSFLF) to monitor the node and link failure in an AON. In this work, a novel faulty node localization (FNL) algorithm is exploited to locate the faulty node. Then, the software defined faulty link detection (SDFLD) algorithm that addresses the problem of link failure. The failures are localized in multi traffic stream (MTS) and multi agent system (MAS). Thus, the throughput is improved in SDSFLF compared than other existing methods like traditional routing and wavelength assignment (RWA), simulated annealing (SA) algorithm, attackaware RWA (A-RWA) convex, longest path first (LPF) ordering, and biggest source-destination node degree (BND) ordering. The performance of the proposed algorithm is evaluated in terms of network load, wavelength utilization, packet loss rate, and burst loss rate. Hence, proposed SDSFLF assures that high performance is achieved than other traditional techniques.
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SDSFLF:基于软件数字交换网络的光通信故障定位框架
光网络是一种新兴的数据通信技术。信息通过光纤从源传输到目标。全光网络具有传输透明性好、可扩展性好、带宽大、误码率低、处理速度快等特点。在传统的方法中,链路故障和节点故障一直存在。为了克服上述问题,本文提出了一种鲁棒的软件定义交换使能故障定位框架(SDSFLF)来监测AON中的节点和链路故障。本文提出了一种新的故障节点定位(FNL)算法来定位故障节点。然后,软件定义了故障链路检测(SDFLD)算法来解决链路故障问题。故障主要集中在多流量流(MTS)和多智能体系统(MAS)中。因此,与传统的路由和波长分配(RWA)、模拟退火(SA)算法、攻击感知的RWA (A-RWA)凸、最长路径优先(LPF)排序和最大源-目的节点度(BND)排序等现有方法相比,SDSFLF的吞吐量得到了提高。从网络负载、波长利用率、丢包率和突发损失率等方面对该算法的性能进行了评价。因此,建议的SDSFLF确保实现比其他传统技术更高的性能。
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