Study of a transport protocol employing bottleneck probing and token bucket flow control

<p>Quality of Service (QoS) is the collective effect of service performances, which determine the degree of satisfaction of a user of the service. In addition, QoS defined as the ability of a network to provide good service. QoS aims to provide different quality of services for various needs in the IP network. QoS parameters that can be used to analyze the data communication services are jitter, packet loss, throughput, and delay. The quality of QoS parameters in the network is affected by congestion. Congestion occurs because there is an excessive queue in the network. Congestion can be prevented by implementing flow control on network. Flow control is a method to control the data packet flow in a network. By controlling of the data packet flow, it can improve of QoS. This study intends to find out value of QoS on the internet network at Faculty Engineering, State University of Semarang by measuring network performance using QoS parameters. Then, in this research will be implemented the token bucket method as a flow control mechanism at the network to improve the QoS. After research and data analysis, internet network at Faculty Engineering State University of Semarang has QoS value was 3,5 with 87,5 % of percentage and classified in satisfying of category. When measuring the network performance, there are decreases of performance at access point that having data rates 150 Mbps with many users connected. It has 9,0 ms of delay value, 0.046 ms of jitter, 16,6% of packet loss and, 1293407 bps of throughput. After token bucket was applied as flow control mechanism that be simulated on Graphical Network Simulator 3, the internet network has QoS values 3,75 with 93,75 % of percentage and classified as “satisfying” category. Furthermore, the percentage of the throughput value obtained on network by implementing flow control is 62%, while on the existing network is 41%.</p>

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Simulation-Based Comparison of TCP and TCP-Friendly Protocols

Encyclopedia of Multimedia Technology and Networking, Second Edition ◽

10.4018/978-1-60566-014-1.ch176 ◽

2009 ◽

pp. 1307-1315

Author(s):

Gábor Hosszú

Keyword(s):

Flow Control ◽

Congestion Control ◽

Streaming Media ◽

Transport Protocol ◽

Receiver Side ◽

Tcp Friendly ◽

Congestion Collapse ◽

End To End ◽

Technical Simplicity ◽

Uniform Manner

Internet streaming media changed the Web from a static medium into a multimedia platform, which supports audio and video content delivery. In our days streaming media turns into the standard way of global media broadcasting and distribution. The low costs, worldwide accessibility, and technical simplicity of this telecommunication way make media streams very attractive for content providers. Streaming works by cutting the compressed media content into packets, which are sent to the receiver. Packets are reassembled and decompressed on the receiver side into a format that can be played by the user. To achieve smooth playback, packets are buffered on the receiver side. However, in case of a network congestion, the stream of packets slows down, and the player application runs out of data, which results in poor playback quality. This article presents the comparison of different transport level congestion control schemes, including variants of the TCP. The protocol mechanisms, implemented in various protocols, are hard to investigate in a uniform manner; therefore, the simulator SimCast (Simulator for multiCast) is developed for traffic analysis of the unicast and multicast streams. In this article the TCP and other transport protocol mechanisms will be compared using the SimCast simulator (Orosz & Tegze, 2001). The simulated results are presented through examples. Due to spreading of traffic lacking end-to-end congestion control, congestion collapse may arise in the Internet (Floyd & Fall, 1999). This form of congestion collapse is caused by congested links that are sending packets to be dropped only later in the network. The essential factor behind this form of congestion collapse is the absence of end-to-end feedback. On the one hand an unresponsive flow fails to reduce its offered load at a router in response to an increased packet drop rate, and on the other hand a disproportionate-bandwidth flow uses considerably more bandwidth than other flows in time of congestion. In order to achieve accurate multicast traffic simulation—being not so TCP-friendly yet—the effects of the flow control of the TCP protocol should be determined (Postel, 1981). However, there are many different kinds of TCP and other unicast transport protocol implementations with various flow control mechanisms, which make this investigation rather difficult (He, Vicat-Blanc Primet, & Welzl, 2005).

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