![Open Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextgreen.png)
![Restricted Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextred.png)
![Open Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextgreen.png)
![Open Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltext_open_medium.gif)
![Restricted Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextred.png)
![Restricted Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltext_restricted_medium.gif)
Modeling RTT Using Box-Jenkins Model
Subscribe/Renew Journal
The Round Trip Time (RTT) is composition of propagation delay, transmission delay, queuing delay, router processing overhead and random delay due to medium access contention. The transmission delay, router processing overhead and propagation delay are deterministic component. The queuing delay and random delay are random noise component. The sudden and sharp increases of RTT caused by congestion, link failure and changes in routing configuration arising from heavy data traffic are random and difficult to model. Many models have been proposed in the literature to forecast the RTT. In this paper, we propose AutoRegressive „Integrated‟ Moving Average model (ARIMA(p,d,q) where p, q, d are the order of autoregressive process, moving average process and order of difference respectively. This model was popularized by Box-Jenkins for time series analysis. The ARIMA(p,d,q) model is a low pass filter which preserves the slowly varying trend component of a time series and removes the rapidly fluctuating or high frequency component. We found that ARIMA (2,1,0) is suitable for modeling the RTT. Most of the time, the one step forecast of RTT is unbiased with actual RTT.
Keywords
RTT Modeling, Time Series Analysis, ARIMA, Box-Jenkins Model.
User
Subscription
Login to verify subscription
Font Size
Information
![](https://i-scholar.in/public/site/images/abstractview.png)
Abstract Views: 181
![](https://i-scholar.in/public/site/images/pdfview.png)
PDF Views: 4