Abstract
Round-trip time (RTT) is an important component for smooth end-to-end congestion control, seamless data flow and for bandwidth estimation in Internet. In transport layer, the performance of a TCP flow directly depends on its RTT value. RTT is the time elapsed for the instant a packet is released by the sender to the instant the corresponding acknowledgement is received by the sender. The study of RTT distribution throws light in understanding the data rate realized by an individual TCP flow in a shared link, queue length along the bottleneck link of a router and the dynamics of sender window. In this paper, a stochastic model defining RTT estimation is considered. The performance of the model is enhanced by applying one-dimensional Kalman filter. Kalman filter is used to eliminate the noise introduced into the signals during transmission of data from source to destination. The combination of the aggregated model with a bias term gives more accurate RTT value. The bias term in the model define Kalman filtering applied for noise elimination. The RTT values calculated using model is regarded as RTT estimation values, and RTT values captured using Wireshark tool are regarded as RTT measurement values. The enhancement of performance of RTT estimation model is demonstrated by inferring statistical data and graphs obtained using MATLAB programming.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
