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Using Adaptive Rate Estimation to Provide Enhanced and Robust Transport over Heterogeneous Networks


The rapid advancement in wireless communication technology has spurred significant interest in the design and development of enhanced TCP protocols. Among them, TCP Westwood (TCPW) is a sender side only modification to improve TCP performance particularly over heterogeneous networks. The key idea of TCPW is to use rate estimation methods to set the congestion window and slow start threshold after a packet loss. When packet losses are not only due to buffer overflow, but random errors as well, TCPW estimation methods have been shown to provide significant performance improvement. The earliest estimation method, called Bandwidth Estimation (BE), however, may result in over-estimation under certain circumstances, and thus may be unfriendly toward non-TCPW traffic. TCPW CRB (Combined Rate and Bandwidth estimation) and TCPW ABSE (Adaptive Bandwidth Share Estimation), have been later introduced to address this concern. The schemes provide better control of the tradeoffs among efficiency, friendliness, and implementation complexity. CRB may slightly sacrifice the efficiency gain to ensure friendliness. ABSE adaptivity mechanisms are more sophisticated and provide both better efficiency and friendliness. In this paper, we summarize ABSE, which adapts to congestion level, as well as round drip time, and other network dynamics, thus providing enhanced and robust performance under various network conditions. Extensive experiments show that TCPW ABSE is able to enhance TCP performance significantly over ”large leaky pipes”, while maintaining friendliness toward TCP NewReno. In this paper we show that TCPW ABSE is robust to packet and ACK compression due to cross traffic on forward and backward paths. We also show that ABSE is robust to buffer size variations, which are inevitable in today’s networks. Keywords: TCP Westwood

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Information & Date

10th IEEE International Conference on Network Protocols, Paris, France, November. 2002


Ren Wang
Massimo Valla
M. Y. Sanadidi
Mario Gerla