Interference-aware fair rate control in wireless sensor networks

By Sumit Rangwala, Ramakrishna Gummadi, Ramesh Govindan, Konstantinos Psounis. Conference on Applications, Technologies, Architectures, and Protocols for Computer Communication, 2006

335 citations recorded by the source corpus.

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Data Collection and Wireless Communication in Internet of Things (IoT) Using Economic Analysis and Pricing Models: A Survey (2016, methodology): “The second method employs an Additive Increase Multiplicative Decrease (AIMD) [177] which takes into account the congestion level along the source’s flow to sink nodes.”
Collection tree protocol (2009, background): “A large body of sensor network protocol work examines how to mitigate congestion when traffic concentrates around one node [3,9,13,26,33,34].”
SOAR: Simple Opportunistic Adaptive Routing Protocol for Wireless Mesh Networks (2009, background): “neous flows, rate control is also useful to improve fairness and avoid starvation, as shown in [11], [27], [19].”
Information fusion for wireless sensor networks: Methods, models, and classifications (2007, methodology): “Another example is the use of EWMA .lters to detect incipient congestion [Rangwala et al. 2006] for fair and ef.cient rate control.”
Four-Bit Wireless Link Estimation (2007, methodology): “We compare our estimator with MultihopLQI, the current state of the art estimator used by many sensornet protocols and systems [18, 10, 16, 21, 2].”