Detecting and classifying delay Data Exceptions on communication networks using rule based algorithms

被引:5
|
作者
Benmusa, T [1 ]
Parish, DJ [1 ]
Sandford, M [1 ]
机构
[1] Loughborough Univ Technol, Dept Elect Engn, Loughborough LE11 3TU, Leics, England
关键词
Data Exceptions; communication network measurement; communication network performance; changes in network performance; rule based detection;
D O I
10.1002/dac.694
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Network performance monitoring is essential for managing a network efficiently and for ensuring reliable operation of the network. Monitored network performance changes reflect events in the network, such as faults, significant changes in usage patterns or planned alterations. Network managers are interested in how and when the performance of a network changes; however it is inefficient to analyse all the data resulting from the monitoring operation manually. In this paper a rule based algorithm to automate detection of the changes in one of the network performance parameters, namely delay, is presented and described in detail. The nature of the delay pattern in a commercial communication network was the key issue in developing this algorithm. The approach was tested with monitored delay data generated from three different networks and showed good results. Also, the algorithm was tested with sets of delay data which have been already input to a previously developed detector based on a different approach, and the results between the two detectors are compared. In addition to a noticeable improvement in detection performance, the new approach provides more generality and independency of the source of the delay data, making the approach generally applicable to other networks. Copyright (C) 2004 John Wiley Sons, Ltd.
引用
收藏
页码:159 / 177
页数:19
相关论文
共 50 条
  • [1] FALCoN: Detecting and classifying abusive language in social networks using context features and unlabeled data
    Tuarob, Suppawong
    Satravisut, Manisa
    Sangtunchai, Pochara
    Nunthavanich, Sakunrat
    Noraset, Thanapon
    INFORMATION PROCESSING & MANAGEMENT, 2023, 60 (04)
  • [2] Detecting coherent structures in a turbulent wake by using delay based networks
    Peña, FL
    Duro, RJ
    Simón, MS
    COMPUTER STANDARDS & INTERFACES, 2002, 24 (02) : 171 - 184
  • [3] Rule-Based Data Communication Optimization Using Quantitative Communication Profiling
    Cuong Pham Quoc
    Al-Ars, Zaid
    Bertels, Koen
    2012 INTERNATIONAL CONFERENCE ON FIELD-PROGRAMMABLE TECHNOLOGY (FPT'12), 2012, : 104 - 108
  • [4] An overview of queuing delay and various delay based algorithms in networks
    Roy, Arnab
    Pachuau, Joseph Lalnunfela
    Saha, Anish Kumar
    COMPUTING, 2021, 103 (10) : 2361 - 2399
  • [5] An overview of queuing delay and various delay based algorithms in networks
    Arnab Roy
    Joseph Lalnunfela Pachuau
    Anish Kumar Saha
    Computing, 2021, 103 : 2361 - 2399
  • [6] Models and algorithms for classifying big data based on distributed data streams
    Mao G.-J.
    Hu D.-J.
    Xie S.-Y.
    1600, Science Press (40): : 161 - 175
  • [7] Communication-Aware Flight Algorithms for UAV-Based Delay-Tolerant Networks
    Asano, Hiroyuki
    Okada, Hiraku
    Ben Naila, Chedlia
    Katayama, Masaaki
    IEICE TRANSACTIONS ON COMMUNICATIONS, 2023, E106B (11) : 1122 - 1132
  • [8] Modern Approaches to Detecting and Classifying Toxic Comments Using Neural Networks
    S. V. Morzhov
    Automatic Control and Computer Sciences, 2021, 55 : 607 - 616
  • [9] Modern Approaches to Detecting and Classifying Toxic Comments Using Neural Networks
    Morzhov, S. V.
    AUTOMATIC CONTROL AND COMPUTER SCIENCES, 2021, 55 (07) : 607 - 616
  • [10] Classifying Modulations in Communication Intelligence Using Deep Learning Networks
    Yahya BENREMDANE
    Said JAMAL
    Oumaima TAHERI
    Jawad LAKZIZ
    Said OUASKIT
    JournalofSystemsScienceandInformation, 2024, 12 (03) : 379 - 392