基于SNMP协议的可扩展在线多级分布式网络故障检测/监测系统

Ming-Shan Su, K. Thulasiraman, Anindya Das
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引用次数: 22

摘要

传统的集中式网络管理解决方案不能扩展到当今的大规模计算机/通信网络。去中心化/分布式解决方案可以解决其中的一些问题(Goldszmidt, G.和Yemini, Y., 1995),因此对分布式/去中心化网络管理应用程序有相当大的兴趣。我们提出了一个基于snmp的分布式网络故障检测/监控系统的设计和评估。我们在SNMP框架中集成了ML-ADSD算法(Su, m - s。et al., Proc. 39 Annual Allerton conf on common。,控制与计算机,2001;苏,“基于SNMP协议的多层分布式诊断与分布式网络故障检测系统设计”,博士论文,美国俄克拉何马大学计算机科学学院,2002),用于分布式处理器系统故障诊断。该算法使用多层范式,只需要微小的修改就可以扩展到不同规模的网络。该系统是容错的,允许处理器故障和/或恢复在诊断过程中。我们在32台机器的以太网网络上实现了该系统。我们的结果表明,诊断延迟(或终止时间)比以前的解决方案好得多。同时,该系统的带宽利用率不高,证明了其在实际网络中部署的实用性。成功融合了网络管理、分布式计算、系统级诊断三大现代学科。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A scalable on-line multilevel distributed network fault detection/monitoring system based on the SNMP protocol
Traditional centralized network management solutions do not scale to present-day large-scale computer/communication networks. Decentralization/distributed solutions can solve some of these problems (Goldszmidt, G. and Yemini, Y., 1995), and thus there is considerable interest in distributed/decentralized network management applications. We present the design and evaluation of an SNMP-based distributed network fault detection/monitoring system. We integrate into the SNMP framework our ML-ADSD algorithm (Su, M.-S. et al., Proc. 39th Annual Allerton Conf. on Commun., Control, and Computers, 2001; Su, "Multilevel distributed diagnosis and the design of a distributed network fault detection system based on the SNMP protocol", Ph.D. Thesis, School of Computer Science, University of Oklahoma, 2002) for fault diagnosis in a distributed processor system. The algorithm uses the multilevel paradigm and requires only minor modifications to be scalable to networks of varying sizes. The system is fault tolerant, allowing processor failure and/or recovery during the diagnosis process. We have implemented the system on an Ethernet network of 32 machines. Our results show that the diagnosis latency (or time to termination) is much better than that of earlier solutions. Also, the system's bandwidth utilization is insignificant, demonstrating the practicality of its deployment in a real network. We have successfully integrated three modern disciplines: network management, distributed computing and system level diagnosis.
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