Efficient Interference Graph Estimation via Concurrent Flooding
CoRR(2023)
摘要
Traditional wisdom for network management allocates network resources
separately for the measurement and data transmission tasks. Heavy measurement
tasks may take up resources for data transmission and significantly reduce
network performance. It is therefore challenging for interference graphs,
deemed as incurring heavy measurement overhead, to be used in practice in
wireless networks. To address this challenge in wireless sensor networks, we
propose to use power as a new dimension for interference graph estimation (IGE)
and integrate IGE with concurrent flooding such that IGE can be done
simultaneously with flooding using the same frequency-time resources. With
controlled and real-world experiments, we show that it is feasible to
efficiently achieve IGE via concurrent flooding on the commercial off-the-shelf
(COTS) devices by controlling the transmit powers of nodes. We believe that
efficient IGE would be a key enabler for the practical use of the existing
scheduling algorithms assuming known interference graphs.
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