Network traffic engineering using linear regression approach / Vathsala Devi Kunalan

Vathsala Devi, Kunalan (2006) Network traffic engineering using linear regression approach / Vathsala Devi Kunalan. Masters thesis, University of Malaya.

PDF (Thesis M.A)
Download (1078Kb) | Preview


    Quality of Service (QoS) routing is becoming a very important criteria in Internet for supporting the ever-increasing diverse multimedia applications that demand very high level quality of service from the underlying network. To achieve this, QoS-enabled routers need to maintain accurate view of the network resource availability by exchanging state information among themselves at appropriate intervals. Frequent dissemination of global network state information introduces two major problems: increased computational costs and higher protocol overheads. In this thesis, a new mechanism that disseminates link state updates based on the bandwidth utilization trend of a link, called TE-LR (Traffic Engineering using Linear Regression), is proposed. The main idea of the mechanism is to sample the bandwidth utilization ratio of a link at regular intervals and use these sampled data to construct linear regression line equations. The tangent value obtained from the equation is used to decide when to send link state updates. Simulation results showed that the proposed mechanism had been successful in reducing the update message overheads by almost 78% with minimal impact to other parameters such as packet loss ratio, , average link utilization and average end-to-end delay.

    Item Type: Thesis (Masters)
    Additional Information: Dissertation (M.A.) – Faculty of Computer Science & Information Technology, University of Malaya, 2006.
    Uncontrolled Keywords: Quality of Service (QoS); linear regression approach; global network; packet commit ratio; link utilization
    Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
    Divisions: Faculty of Computer Science & Information Technology
    Depositing User: Mr Mohd Safri Tahir
    Date Deposited: 23 Dec 2019 03:55
    Last Modified: 17 Aug 2020 08:14

    Actions (For repository staff only : Login required)

    View Item