Quick (and Dirty) Aggregate Queries on Low-Power WANs

Gadre, Akshay; Yi, Fan; Rowe, Anthony; Iannucci, Bob; Kumar, Swarun

doi:10.1109/ipsn48710.2020.00031

Cited by 28 publications

(13 citation statements)

References 21 publications

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“…Figure 13 depicts their energy consumption measured in the simulations. These results are fully compliant with the theoretical results given by Equation (25). For any spreading factor, the energy consumption curve consists of four steps corresponding to the four monitoring periods in the synchronization period.…”

Section: Energy Consumptionsupporting

confidence: 85%

“…Our paper aims at proposing solutions to avoid collisions, whereas others try to strongly limit them [ 23 ] or transform them into constructive collisions like Choir [ 24 ] or QuAiL [ 25 ] using the linear addition of powers of phase-asynchronous channels. Others take advantage of specific hardware to successfully decode weak transmissions at the GW, like Charm [ 26 ].…”

Section: Related Workmentioning

confidence: 99%

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Collision-Free Transmissions in an IoT Monitoring Application Based on LoRaWAN

Haiahem¹,

Minet

Boumerdassi

et al. 2020

Sensors

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With the Internet of Things (IoT), the number of monitoring applications deployed is considerably increasing, whatever the field considered: smart city, smart agriculture, environment monitoring, air pollution monitoring, to name a few. The LoRaWAN (Long Range Wide Area Network)architecture with its long range communication, its robustness to interference and its reduced energy consumption is an excellent candidate to support such applications. However, if the number of end devices is high, the reliability of LoRaWAN, measured by the Packet Delivery Ratio (PDR), becomes unacceptable due to an excessive number of collisions. In this paper, we propose two different families of solutions ensuring collision-free transmissions. The first family is TDMA (Time-Division Multiple Access)-based. All clusters transmit in sequence and up to six end devices with different spreading factors belonging to the same cluster are allowed to transmit in parallel. The second family is FDMA (Frequency Divsion Multiple Access)-based. All clusters transmit in parallel, each cluster on its own frequency. Within each cluster, all end devices transmit in sequence. Their performance are compared in terms of PDR, energy consumption by end device and maximum number of end devices supported. Simulation results corroborate the theoretical results and show the high efficiency of the solutions proposed.

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Section: Energy Consumptionsupporting

confidence: 85%

Section: Related Workmentioning

confidence: 99%

Collision-Free Transmissions in an IoT Monitoring Application Based on LoRaWAN

Haiahem¹,

Minet

Boumerdassi

et al. 2020

Sensors

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show abstract

“…Last few years have seen advances in LoRa technology such as performance optimization [Balanuta et al 2020;Demetri et al 2019;Dongare et al 2018;Gao et al 2020;Hessar et al 2020;Li et al 2021;Liu et al 2020b;Sangar and Krishnaswamy 2020;Yang et al 2020a], LoRa backscatter [Guo et al 2020;Katanbaf et al 2021;Peng et al 2018;Talla et al 2017], LoRa sensing [Chen et al 2019;Gadre et al 2020b;Lin et al 2021;Nandakumar et al 2018;Xie and Xiong 2020;, and LoRa security Hou et al 2021;Hou and Zheng 2020;], etc.…”

Section: Related Workmentioning

confidence: 99%

PCube: Scaling LoRa Concurrent Transmissions with Reception Diversities

Xia

Hou

Zheng

et al. 2022

ACM Trans. Sen. Netw.

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This paper presents the design and implementation of PCube, a phase-based parallel packet decoder for concurrent transmissions of LoRa nodes. The key enabling technology behind PCube is a novel air-channel phase measurement technique which is able to extract phase differences of air-channels between LoRa nodes and multiple antennas of a gateway. PCube leverages the reception diversities of multiple receiving antennas of a gateway and scales the concurrent transmissions of a large number of LoRa nodes, even exceeding the number of receiving antennas at a gateway. As a phase-based parallel decoder, PCube provides a new dimension to resolve collisions and supports more concurrent transmissions by complementing time and frequency based parallel decoders. PCube is implemented and evaluated with synchronized software defined radios and off-the-shelf LoRa nodes in both indoors and outdoors. Results demonstrate that PCube can substantially outperform state-of-the-art works in terms of aggregated throughput by 4.9 × and the number of concurrent nodes by up to 5 ×. More importantly, PCube scales well with the number of receiving antennas of a gateway, which is promising to break the barrier of concurrent transmissions.

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“…Low-Power IoT: There has been much work done in Low-Power Wide-Area Networks (LP-WANs) for synchronization [3,55], association [23,41], optimizing power [5,20], improving scalability [21,24,58], and client power adaptation [74]. Recent trends [31,37] demonstrate moving complex functions off the low-power client to the more powerful base stations.…”

Section: Related Workmentioning

confidence: 99%

Joltik

Yang

Zhang

Gadre

et al. 2020

Proceedings of the 26th Annual International Conference on Mobile Computing and Networking

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Wireless sensors have enabled a number of key applications. Due to their energy constraints, wireless sensors today communicate occasional short samples or predetermined summary statistics of the data they collect. This means that computing every additional statistic at high fidelity incurs additional communication and energy overhead. This paper presents Joltik, a framework enabling general, future-proof, and energy-efficient analytics for low power wireless sensors. Joltik is general in that it summarizes sensed data from low-power devices without making assumptions on which specific statistical metric(s) are desired at the cloud and is future-proof, meaning it supports new, unforeseen metrics. Joltik is built upon recent theoretical advances in universal sketching, which can enable a Joltik sensor node to report a compact summary of observed data to enable a large class of statistical summaries. We address key system design and implementation challenges with respect to communication, memory, and computation bottlenecks that arise in practically realizing the potential benefits of universal sketching in the low-power regime. We present a proof-of-concept testbed evaluation of Joltik in LoRaWAN NUCLEO-L476RG boards and sensors. Across a range of realistic datasets, Joltik provides up to a 24.6× reduction in energy cost compared to transmitting raw data and outperforms many natural alternatives (e.g., sub-sampling, custom sketches, compressed sensing, and lossy compression) in terms of energy-accuracy trade-offs. CCS Concepts • Networks → Network components; • Computer systems organization → Embedded and cyber-physical systems; • Hardware → Communication hardware, interfaces and storage.

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Quick (and Dirty) Aggregate Queries on Low-Power WANs

Cited by 28 publications

References 21 publications

Collision-Free Transmissions in an IoT Monitoring Application Based on LoRaWAN

Collision-Free Transmissions in an IoT Monitoring Application Based on LoRaWAN

PCube: Scaling LoRa Concurrent Transmissions with Reception Diversities

Joltik

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