Rate adaptation is a crucial component that impacts the performance of IEEE 802.eleven wireless networks. In congested networks, traditional rate adaptation algorithms are shown to settle on lower data-rates for packet transmissions, resulting in reduced total network throughput and capacity. A primary reason for this behavior is the lack of real-time congestion measurement techniques that may assist in the identification of congestion-connected packet losses in an exceedingly wireless network. In this work, we first propose 2 real-time congestion measurement techniques, namely an active probe-primarily based technique referred to as Channel Access Delay, and a passive method known as Channel Busy Time. We have a tendency to evaluate the two techniques in a take a look at bed network and a massive WLAN connected to the Internet. We have a tendency to then present the design and analysis of Wireless congestion Optimized Fallback (WOOF), a rate adaptation theme that uses congestion measurement to identify congestion-connected packet losses. Through simulation and take a look at bed implementation we have a tendency to show that, compared to different well-known rate adaptation algorithms, WOOF achieves up to 300 percent throughput improvement in congested networks.
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