A rate-adaptive MAC protocol for multi-Hop wireless networks
Proceedings of the 7th annual international conference on Mobile computing and networking
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Wireless Communications: Principles and Practice
Opportunistic media access for multirate ad hoc networks
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Efficient channel-aware rate adaptation in dynamic environments
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NSDI'09 Proceedings of the 6th USENIX symposium on Networked systems design and implementation
Cross-layer wireless bit rate adaptation
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
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Proceedings of the 15th annual international conference on Mobile computing and networking
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Proceedings of the ACM SIGCOMM 2010 conference
AccuRate: constellation based rate estimation in wireless networks
NSDI'10 Proceedings of the 7th USENIX conference on Networked systems design and implementation
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Proceedings of the sixteenth annual international conference on Mobile computing and networking
Improving wireless network performance using sensor hints
Proceedings of the 8th USENIX conference on Networked systems design and implementation
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We present BlockRate, a wireless bitrate adaptation algorithm designed for blocks, or large contiguous units of transmitted data, as opposed to small packets. Our work is motivated by the observation that recent research results suggest significant overhead amortization benefits of blocks. Yet state-of-the-art bitrate algorithms are optimized for adaptation on a per-packet basis, so they can either have the amortization benefits of blocks or high responsiveness to underlying channel conditions of packets, but not both. To bridge this disparity, BlockRate employs multiple bitrates within a block that are predictive of future channel conditions. In each feedback round, BlockRate uses a history-based scheme to predict the SNR for packets within the next block. In slow-changing scenarios as under pedestrian mobility, BlockRate uses a simple linear regression model to predict the SNR trend over the next block. In fast-changing scenarios as under vehicular mobility, BlockRate uses a path loss model to capture more significant SNR variations within a block. We have implemented a prototype of BlockRate in a commodity 802.11 driver and evaluated it via deployment on an indoor mesh testbed as well as an outdoor vehicular testbed. Our evaluation shows that BlockRate achieves up to 1.4× and 2.8× improvement in goodput under indoor and outdoor mobility respectively.