TY - GEN
T1 - Estimating Link Packet Rates from Partial CSMA/CA Network Observations
AU - Cheng, Yirong
AU - Graves, Eric
AU - Swami, Ananthram
AU - Sabharwal, Ashutosh
N1 - Funding Information:
0Research was sponsored by the Army Research Office and was accomplished under Cooperative Agreement Number W911NF-19-2-0269. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Office or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein.
Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - We consider the problem of estimating link packet rates in CSMA/CA networks using only eavesdropped observations from a single observer. We assume that the observer does not know the network topology and hence the contention graph indicating the interference structure. Additionally, if the eavesdropped network permits spatial reuse, then there will be collisions at the eavesdropper, leading to partial measurements. We propose a link packet rate estimation algorithm that works under the challenges mentioned above, by leveraging time reversibility of the traffic on networks with single-hop flows. We demonstrate that the estimated values converge to the true values asymptotically in the duration of the observation window.
AB - We consider the problem of estimating link packet rates in CSMA/CA networks using only eavesdropped observations from a single observer. We assume that the observer does not know the network topology and hence the contention graph indicating the interference structure. Additionally, if the eavesdropped network permits spatial reuse, then there will be collisions at the eavesdropper, leading to partial measurements. We propose a link packet rate estimation algorithm that works under the challenges mentioned above, by leveraging time reversibility of the traffic on networks with single-hop flows. We demonstrate that the estimated values converge to the true values asymptotically in the duration of the observation window.
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U2 - 10.1109/IEEECONF53345.2021.9723259
DO - 10.1109/IEEECONF53345.2021.9723259
M3 - Conference contribution
AN - SCOPUS:85127065351
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 772
EP - 779
BT - 55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021
A2 - Matthews, Michael B.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021
Y2 - 31 October 2021 through 3 November 2021
ER -