View in EDS

Network fault detection with Wiener filter-based agent

Saved in:
Bibliographic Details
Title: Network fault detection with Wiener filter-based agent
Authors: Al-Kasassbeh, Mouhammd mouhammd.al-kasassbeh@port.ac.uk, Adda, Mo1 mo.adda@port.ac.uk
Source: Journal of Network & Computer Applications. Jul2009, Vol. 32 Issue 4, p824-833. 10p.
Subjects: Management information systems, Mobile communication systems, Systems design, Intelligent agents
Abstract: Abstract: Over the last few decades, network domains have become more and more advanced in terms of their size, complexity and level of heterogeneity. Existing centralized-based network management approaches suffer from problems such as insufficient scalability, availability and flexibility, as networks become more distributed. Mobile agents (MA), upgraded with intelligence, can present a reasonable new technology that will help to achieve distributed management. These agents migrate from one node to another, accessing an appropriate subset of Management Information Base (MIB) variables from each node analysing them locally and retaining the results of this analysis during their subsequent migration. One of the network fault management tasks is fault detection, and in this paper our purpose was to carry out a statistical method based on Wiener filter to capture the abnormal changes in the behaviour of the MIB variables. Our algorithm was implemented on data obtained from two different scenarios in the laboratory, with four different fault case studies. The purpose of this is to provide the manager node with a high level of information, such as a set of conclusions or recommendations, rather than large volumes of data relating to each management task. The filtering process is carried out concurrently by each agent responsible for a particular domain and device, proving to be more scalable and efficient. [Copyright &y& Elsevier]
Copyright of Journal of Network & Computer Applications is the property of Academic Press Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 38800175
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Network fault detection with Wiener filter-based agent
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Al-Kasassbeh%2C+Mouhammd%22">Al-Kasassbeh, Mouhammd</searchLink><i> mouhammd.al-kasassbeh@port.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Adda%2C+Mo%22">Adda, Mo</searchLink><relatesTo>1</relatesTo><i> mo.adda@port.ac.uk</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Journal+of+Network+%26+Computer+Applications%22">Journal of Network & Computer Applications</searchLink>. Jul2009, Vol. 32 Issue 4, p824-833. 10p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Management+information+systems%22">Management information systems</searchLink><br /><searchLink fieldCode="DE" term="%22Mobile+communication+systems%22">Mobile communication systems</searchLink><br /><searchLink fieldCode="DE" term="%22Systems+design%22">Systems design</searchLink><br /><searchLink fieldCode="DE" term="%22Intelligent+agents%22">Intelligent agents</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Abstract: Over the last few decades, network domains have become more and more advanced in terms of their size, complexity and level of heterogeneity. Existing centralized-based network management approaches suffer from problems such as insufficient scalability, availability and flexibility, as networks become more distributed. Mobile agents (MA), upgraded with intelligence, can present a reasonable new technology that will help to achieve distributed management. These agents migrate from one node to another, accessing an appropriate subset of Management Information Base (MIB) variables from each node analysing them locally and retaining the results of this analysis during their subsequent migration. One of the network fault management tasks is fault detection, and in this paper our purpose was to carry out a statistical method based on Wiener filter to capture the abnormal changes in the behaviour of the MIB variables. Our algorithm was implemented on data obtained from two different scenarios in the laboratory, with four different fault case studies. The purpose of this is to provide the manager node with a high level of information, such as a set of conclusions or recommendations, rather than large volumes of data relating to each management task. The filtering process is carried out concurrently by each agent responsible for a particular domain and device, proving to be more scalable and efficient. [Copyright &y& Elsevier]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Network & Computer Applications is the property of Academic Press Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=38800175
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.jnca.2009.02.001
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 10
        StartPage: 824
    Subjects:
      – SubjectFull: Management information systems
        Type: general
      – SubjectFull: Mobile communication systems
        Type: general
      – SubjectFull: Systems design
        Type: general
      – SubjectFull: Intelligent agents
        Type: general
    Titles:
      – TitleFull: Network fault detection with Wiener filter-based agent
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Al-Kasassbeh, Mouhammd
      – PersonEntity:
          Name:
            NameFull: Adda, Mo
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 07
              Text: Jul2009
              Type: published
              Y: 2009
          Identifiers:
            – Type: issn-print
              Value: 10848045
          Numbering:
            – Type: volume
              Value: 32
            – Type: issue
              Value: 4
          Titles:
            – TitleFull: Journal of Network & Computer Applications
              Type: main
ResultId 1