• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文学位 >Probabilistic inference for diagnosing service failures in communication systems.
【24h】

Probabilistic inference for diagnosing service failures in communication systems.

机译：诊断通信系统中服务故障的概率推断。

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Fault localization is a process of deducing the exact source of a failure (a root cause) from a set of observed failure indications. Today's communication systems require techniques capable of: multi-layer integrated diagnosis, diagnosis of performance problems, dealing with uncertainty within the knowledge of the system structure and state, ability to isolate multiple simultaneous faults, event-driven and incremental diagnosis, high accuracy, and low complexity.; This dissertation addresses these challenges in designing a fault propagation model and algorithms for probabilistic fault localization. The proposed fault propagation model is a probabilistic multi-layer dependency-graph that incorporates both availability and performance problems, and allows arbitrary relationships among system components to be represented. For the purpose of fault diagnosis, the dissertation adopts two Bayesian inference algorithms that calculate belief-updating and most-probable-explanation queries in singly-connected belief networks to perform fault localization in belief networks with loops. The dissertation also proposes a novel fault localization algorithm based on incremental hypothesis updating to perform diagnosis with bipartite fault propagation models. These fault localization techniques are extended to incorporate reasoning with positive symptoms and be resilient to noise in the alarm data. The algorithms are evaluated using the problem of end-to-end service failure diagnosis as a case study. The dissertation defines this problem as the task of isolating host-to-host service failures responsible for failures of end-to-end services.; Although the algorithms based on iterative belief updating and incremental hypothesis updating introduced in this dissertation are efficient in the diagnosis of multi-fault end-to-end-failure scenarios in networks composed of tens of nodes, they do not scale well to networks composed of hundreds or thousands of nodes. To address this scalability problem, the dissertation introduces a multi-domain fault localization approach to end-to-end service failure diagnosis in hierarchically routed networks. The multi-domain approach divides the computational effort and system knowledge involved in end-to-end service-failure diagnosis among multiple hierarchically organized managers. The dissertation first proposes an algorithmic framework for the design of probabilistic techniques of multi-domain fault localization. Then, it introduces two specific techniques that expand on the centralized algorithms introduced in the dissertation: iterative belief updating and incremental hypothesis updating.
机译：故障定位是从一组观察到的故障指示中推导出故障确切原因（根本原因）的过程。当今的通信系统需要以下技术：多层集成诊断，性能问题诊断，系统结构和状态知识中的不确定性处理，隔离多个同时故障的能力，事件驱动和增量诊断，高精度以及低复杂度。本文针对概率故障定位设计故障传播模型和算法，解决了这些挑战。提出的故障传播模型是一个概率多层依赖图，它包含了可用性和性能问题，并允许表示系统组件之间的任意关系。出于故障诊断的目的，本文采用两种贝叶斯推理算法，分别在单连接信念网络中计算信念更新和最有可能解释的查询，以对带有回路的信念网络进行故障定位。本文还提出了一种新的基于增量假设更新的故障定位算法，利用二分故障传播模型进行诊断。这些故障定位技术已扩展为包含具有积极症状的推理功能，并且对警报数据中的噪声具有弹性。以端到端服务故障诊断问题为例对算法进行评估。本文将这个问题定义为隔离负责端到端服务故障的主机到主机服务故障的任务。尽管本文介绍的基于迭代信念更新和增量假设更新的算法在由数十个节点组成的网络中的多故障端到端故障场景的诊断中是有效的，但它们并不能很好地扩展到由以下节点组成的网络中数百或数千个节点。为了解决这一可扩展性问题，本文引入了一种多域故障定位方法，用于分层路由网络中的端到端服务故障诊断。多域方法将端到端服务故障诊断中涉及的计算工作量和系统知识划分为多个层次结构的管理器。本文首先提出了一种用于多域故障定位概率技术设计的算法框架。然后，介绍了在本文引入的集中式算法的基础上扩展的两种特定技术：迭代信念更新和增量假设更新。

著录项

  • 作者

    Steinder, Malgorzata.;

  • 作者单位

    University of Delaware.;

  • 授予单位 University of Delaware.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2003
  • 页码 210 p.
  • 总页数 210
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化技术、计算机技术;
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号