The developed model allows to quantify the joint effect of many implementation-specific parameters on TCP performance over both correlated and non-correlated wireless channels. This distribution is used at the next step of the modeling, where we derive expressions for the TCP long-term steady-state throughput, the mean round-trip time, and the spurious timeout probability. At the first step, we consider the service process of the wireless channel and derive a probability distribution of the time required to successfully transmit an IP packet over the wireless channel.
Since backbone networks today are highly overprovisioned, we assume that the wireless channel is the only one bottleneck in the system which causes packets to be buffered at the wired/wireless interface and dropped as a result of buffer overflow. In this paper, we propose an analytical cross-layer model for a TCP connection running over a covariance-stationary wireless channel with a completely reliable Automatic Repeat reQuest (ARQ) scheme combined with Forward Error Correction (FEC) coding. The input parameters include the bit error rate, the value of the normalized autocorrelation function of bit error observations at lag 1, the strength of the FEC code, the persistency of ARQ, the size of protocol data units at different layers, the raw data rate of the wireless channel, and the bottleneck link buffer size. The model allows to evaluate the joint effect of stochastic properties of the wireless channel characteristics and various implementation-specific parameters on TCP performance, which makes it suitable for performance optimization studies. In this paper, we develop an analytical cross-layer model for a TCP connection running over a wireless channel with a semi-reliable ARQ scheme, where the amount of transmission attempts is limited by some number. Most analytical models that studied the effect of ARQ and FEC on TCP performance assumed that the ARQ scheme is perfectly persistent (i.e., completely reliable), thus a frame is always successfully transmitted irrespective of the number of transmission attempts it takes. Automatic Repeat reQuest (ARQ) and Forward Error Correction (FEC) try to improve communication reliability and reduce packet losses by detecting and recovering corrupted bits. Since TCP cannot distinguish packet losses due to bit corruption from those due to network congestion, any packet loss caused by wireless channel impairments leads to unnecessary execution of the TCP congestion control algorithms and, hence, sub-optimal performance. These errors result in loss of IP packets and, consequently, TCP segments encapsulated into these packets.
Providing reliable data communications over wireless channels is a challenging task because time-varying wireless channel characteristics often lead to bit errors. In this book, we made an effort towards a better understanding of various aspects of TCP performance under different conditions and in different environments. To be useful, these analytical models should be accurate and capture the most important TCP algorithms. Due to its widespread use, TCP performance has been extensively studied over the last decade, whereas analytical modeling has proven to be a powerful and cost-effective tool for examining the behavior of TCP. As a result, a large portion of Internet traffic is carried by TCP. Most popular applications and services, starting from FTP and Usenet before the World Wide Web was invented and up to YouTube and P2P these days, use TCP as the default transport layer protocol for providing reliable data delivery over best-effort IP networks.
From the early days of BSD Unix systems to desktop and server platforms of today, the TCP/IP protocol suite and, consequently, the Transmission Control Protocol (TCP) itself are an integral part of any operating system.
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