Aperiodic data collection received little attention in wireless sensor networks, compared to its periodic counterpart. The recent Crystal system uses synchronous transmissions to support aperiodic traffic with near-perfect reliability, low latency, and ultra-low power consumption. However, its performance is known under mild interference—a concern, as Crystal relies heavily on the (noise-sensitive) capture effect and targets aperiodic traffic where “every packet counts”. We exploit a 49-node indoor testbed where, in contrast to existing evaluations using only naturally present interference to evaluate synchronous systems, we rely on JamLab to generate noise patterns that are not only more disruptive and extensive, but also reproducible. We show that a properly configured, unmodified Crystal yields perfect reliability (unlike Glossy) in several noise scenarios, but cannot sustain extreme ones (e.g., an emulated microwave oven near the sink) that instead are handled by routing-based approaches. We extend Crystal with techniques known to mitigate interference—channel hopping and noise detection—and demonstrate that these allow Crystal to achieve performance akin to the original even under multiple sources of strong interference

Interference-Resilient Ultra-Low Power Aperiodic Data Collection

Istomin, Timofei;Murphy, Amy Lynn;
2018-01-01

Abstract

Aperiodic data collection received little attention in wireless sensor networks, compared to its periodic counterpart. The recent Crystal system uses synchronous transmissions to support aperiodic traffic with near-perfect reliability, low latency, and ultra-low power consumption. However, its performance is known under mild interference—a concern, as Crystal relies heavily on the (noise-sensitive) capture effect and targets aperiodic traffic where “every packet counts”. We exploit a 49-node indoor testbed where, in contrast to existing evaluations using only naturally present interference to evaluate synchronous systems, we rely on JamLab to generate noise patterns that are not only more disruptive and extensive, but also reproducible. We show that a properly configured, unmodified Crystal yields perfect reliability (unlike Glossy) in several noise scenarios, but cannot sustain extreme ones (e.g., an emulated microwave oven near the sink) that instead are handled by routing-based approaches. We extend Crystal with techniques known to mitigate interference—channel hopping and noise detection—and demonstrate that these allow Crystal to achieve performance akin to the original even under multiple sources of strong interference
978-1-5386-5298-5
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/316130
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