Programs
- M. Tech. in Automotive Engineering -
- Clinical Fellowship in Laboratory Genetics & Genomics - Fellowship
Publication Type : Journal Article
Publisher : Ambient Intelligence and Humanized Computing,
Source : Ambient Intelligence and Humanized Computing, p.979–990 (2021)
Keywords : Congestion, error, Fairness, Non-real-time, Real-time, Satellite
Campus : Coimbatore
School : School of Engineering
Department : Computer Science
Year : 2021
Abstract : In current times, the intensity of Internet usage has been on a relentless rise, in pace with the release of numerous real-time applications like video transmission and non-real-time applications. Due to high error channels, the end-users will observe poor quality video over satellite network. The applications are competing themselves to inject their traffic into the network and hence end users get unfair shares of the bandwidth for the video transmissions. Also, the high transmission rate of video applications affects traditional Internet applications like e-mail. TCP-friendly rate control (TFRC), TFRC-satellite and mul-tiple TFRC streams (MulTFRC), which are intended to provide congestion control, error control and increase bandwidth (BW) utilization respectively, may fail over the satellite networks with high error rate and high congestion. Besides, these connection-oriented protocols increase the applications overhead. In this paper, we present a cooperative flow regulation protocol (CFR), which provides fair access to both real-time and non-real-time applications, over networks with high con-gestion and high error. Verification of the proffered approach, by simulations, show that theCFR protocol reduces the loss of video frames by 30–40%, compared to DCCP and MulTFRC, and 50–60% compared to user datagram protocol (UDP) traffic, without compromise of the video quality.
Cite this Research Publication : Govindarajan J. and Govardhanan, K., “Cooperative flow regulation protocol for real-time and non-real-time applications over satellite network”, Ambient Intelligence and Humanized Computing, pp. 979–990, 2021.