Dynamic behavior of slowly-responsive congestion control algorithms

Bansal, Deepak; Balakrishnan, Hari; Floyd, Sally; Shenker, Scott

doi:10.1145/383059.383080

Cited by 138 publications

(69 citation statements)

References 7 publications

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“…Moreover, it should be friendly toward Reno sources in order to fairly allocate bandwidth to flows carrying multimedia and bulk data [16]. In order to provide friendliness, many control algorithms with a slower responsive dynamics have been designed by trying to emulate the "long-term" behavior of the Reno algorithm [5]. The TEAR (TCP emulation at receivers) rate control algorithm computes the input rate at the receiver and then feeds it back to the sender [30].…”

Section: Related Workmentioning

confidence: 99%

“…This algorithm also does not implement the self-clocking mechanism. It has been shown that a simple AIMD rate control algorithm cannot guarantee friendliness toward Reno connections since an AIMD rate mechanism does not match an AIMD window mechanism [5,6].…”

Section: Related Workmentioning

confidence: 99%

“…In [5] the rate-based algorithms proposed in [12,29] and the window-based algorithms proposed in [2,4] have been tested in the presence of dynamic network conditions to show that algorithms that do not employ the self-clocking principle [12,29] may exhibit a huge settling time, that is, they may require many RTTs to adapt the input rate to the bandwidth available in the network. To overcome the disastrous effects due to the violation of the self-clocking principle, an enhanced version of the TFRC algorithm that emulates the self-clocking mechanism has been proposed in [5].…”

Section: Related Workmentioning

confidence: 99%

“…ARC has been tested over many scenarios and compared with the TCP-Friendly Rate Control (TFRC), which is currently considered by the IETF for applications such as video streaming or telephony where a relative smooth sending rate is of importance [5,12,16]. In particular, single-and multibottleneck scenarios with and without lossy links and in the presence of homogeneous and heterogeneous traffic sources have been considered.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive rate control for streaming flows over the Internet

Grieco

Mascolo

2004

Multimedia Systems

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The existing end-to-end TCP congestion control algorithm is well suited for applications that are not sensitive to delay jitter and abrupt changes of the transmission rate, such as FTP data transfer, but it is not recommended for delivering video data, whose perceived quality is sensitive to delay jitter and changes in the sending rate. In particular, the window-based control of Reno TCP congestion control causes burstiness in data transmission, which not only requires large buffers at the client side to provide a smooth playout but also may provoke bursts of lost packets difficult to recover via forward error correction techniques. This paper proposes an adaptive rate-based control (ARC) algorithm that striclty mimics the real-time dynamics of TCP and is based on an end-to-end mechanism to estimate the connection available bandwidth. Computer simulations using ns-2 have been developed to compare the ARC with the Reno TCP and with the TCP-Friendly Rate Control (TFRC) algorithm. Single-and multibottleneck scenarios in the presence of homogeneous and heterogeneous traffic sources have been considered. Simulations have shown that the ARC algorithm improves fairness and is friendly toward Reno. On the other hand, TFRC revealed itself not to be friendly toward Reno since it mimics only the long term behaviour of Reno TCP. Finally, simulations have shown that ARC remarkably improves the goodput with respect to TFRC and Reno in the presence of lossy links.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Adaptive rate control for streaming flows over the Internet

Grieco

Mascolo

2004

Multimedia Systems

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“…Floyd et al [7] introduce the TFRC algorithm that adjusts its sending rate as a function of the measured loss rate. Bansal et al [3] investigate the behavior of slowly responsive congestion control algorithms. However, for safe deployment in the Internet these algorithms must be stable and interact well with TCP.…”

Section: Introductionmentioning

confidence: 99%

Adaptive AIMD Congestion Control

Kesselman

Mansour

2005

Algorithmica

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The main objectives of a congestion control algorithm are high bandwidth utilization, fairness and responsiveness in a changing environment. However, these objectives are contradicting in particular situations since the algorithm constantly has to probe available bandwidth, which may affect its stability. This paper proposes a novel congestion control algorithm that achieves high bandwidth utilization providing fairness among competing connections and, on the other hand, is sufficiently responsive to changes of available bandwidth. The main idea of the algorithm is to use adaptive setting for the additive increase/multiplicative decrease (AIMD) congestion control scheme, where parameters may change dynamically, with respect to the current network conditions.

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References

2005

Scalable Video on Demand

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Dynamic behavior of slowly-responsive congestion control algorithms

Cited by 138 publications

References 7 publications

Adaptive rate control for streaming flows over the Internet

Adaptive rate control for streaming flows over the Internet

Adaptive AIMD Congestion Control

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