TempLab: A testbed infrastructure to study the impact of temperature on wireless sensor networks

Boano, Carlo Alberto; Zúñiga, Marco; Brown, James; Roedig, Utz; Keppitiyagama, Chamath; Römer, Kay Uwe

doi:10.1109/ipsn.2014.6846744

Cited by 39 publications

(22 citation statements)

References 28 publications

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“…The authors have also shown how the impact of temperature cannot be neglected when designing duty-cycled medium access control protocols for low-power wireless radios [37,38]. To facilitate the study of how temperature affects the operation of low-power wireless protocols on a larger scale than in a temperature-controlled chamber, several low-cost testbed infrastructures have been proposed, the most popular being TempLab and HotBox [39,40].…”

Section: Environmental Effects On Low-power Radiosmentioning

confidence: 99%

“…We use the TempLab testbed [39] to expose a number of LoRa nodes to repeatable temperature variations as shown in Figure 8. The TempLab testbed available at Graz University of Technology has two different types of nodes [38]: LO nodes only heating the sensor nodes above room temperature and PE nodes having the capability to also cool down the node's temperature below zero degrees thanks to enclosures made of hard Polystyrene foam and ATA-050-24 Peltier air-to-air assembly modules (Custom Thermoelectric, Bishopville, MD, USA).…”

Section: Impact Of Temperature On Lora Transceiversmentioning

confidence: 99%

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An Experimental Evaluation of the Reliability of LoRa Long-Range Low-Power Wireless Communication

Cattani

Boano

Römer

2017

JSAN

186

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Recent technological innovations allow compact radios to transmit over long distances with minimal energy consumption and could drastically affect the way Internet of Things (IoT) technologies communicate in the near future. By extending the communication range of links, it is indeed possible to reduce the network diameter to a point that each node can communicate with almost every other node in the network directly. This drastically simplifies communication, removing the need of routing, and significantly reduces the overhead of data collection. Long-range low-power wireless technology, however, is still at its infancy, and it is yet unclear (i) whether it is sufficiently reliable to complement existing short-range and cellular technologies and (ii) which radio settings can sustain a high delivery rate while maximizing energy-efficiency. To shed light on this matter, this paper presents an extensive experimental study of the reliability of LoRa , one of the most promising long-range low-power wireless technologies to date. We focus our evaluation on the impact of physical layer settings on the effective data rate and energy efficiency of communications. Our results show that it is often not worth tuning parameters, thereby reducing the data rate in order to maximize the probability of successful reception, especially on links at the edge of their communication range. Furthermore, we study the impact of environmental factors on the performance of LoRa, and show that higher temperatures significantly decrease the received signal strength and may drastically affect packet reception.

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Section: Environmental Effects On Low-power Radiosmentioning

confidence: 99%

Section: Impact Of Temperature On Lora Transceiversmentioning

confidence: 99%

An Experimental Evaluation of the Reliability of LoRa Long-Range Low-Power Wireless Communication

Cattani

Boano

Römer

2017

JSAN

186

View full text Add to dashboard Cite

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“…It is important to realize that the CFO is not a constant value. Even minute variations of 0.1 degree in the temperature can cause CFO variations of a few hundred hertz [21], [22]. Similarly, noise in the supply voltage cause fast variations in the crystals frequency [22].…”

Section: Why Do Wireless Nodes Have Cfo?mentioning

confidence: 99%

AirShare: Distributed coherent transmission made seamless

Abari

Rahul

Katabi

et al. 2015

2015 IEEE Conference on Computer Communications (INFOCOM)

139

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Distributed coherent transmission is necessary for a variety of high-gain communication protocols such as distributed MIMO and creating codes over the air. Unfortunately, however, distributed coherent transmission is intrinsically difficult because different nodes are driven by independent clocks, which do not have the exact same frequency. This causes the nodes to have frequency offsets relative to each other, and hence their transmissions fail to combine coherently over the air.This paper presents AirShare, a primitive that makes distributed coherent transmission seamless. AirShare transmits a shared clock on the air and feeds it to the wireless nodes as a reference clock, hence eliminating the root cause for incoherent transmissions. The paper addresses the challenges in designing and delivering such a shared clock. It also implements AirShare in a network of USRP software radios, and demonstrates that it achieves tight phase coherence. Further, to illustrate AirShare's versatility, the paper uses it to deliver a coherent-radio abstraction on top of which it demonstrates two cooperative protocols: distributed MIMO, and distributed rate adaptation.

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“…To actually understand what is happening in a real and possibly large or dense wireless network, a number of recent scientific papers have urged to take a different ''data driven'' approach [4,11]. They utilize large datasets containing experimental data to better understand the behaviour of wireless systems.…”

Section: Introductionmentioning

confidence: 99%

Data Driven Wireless Network Design: A Multi-level Modeling Approach

Fortuna

Poorter

ŠKraba

et al. 2016

Wireless Pers Commun

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Wireless network technology keeps improving by solving problems detected in current systems and anticipating requirements for future systems. One of the possible approaches to help advancing wireless technology is to develop methods that help researchers understand the less desired behaviors that may occur in a real-world system. One such method is data driven multi-level analysis that uses the monitoring data collected from real-world networks to provide detailed insight, at several levels and/or scales, into the system behavior. This paper discusses data driven multi-level analysis, provides a proof of concept on how it can be applied and identifies challenges. The contributions of this paper are (1) the use of data driven multi-level analysis for understanding the behaviour of wireless networks and (2) the identification of open challenges and directions for future research.

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TempLab: A testbed infrastructure to study the impact of temperature on wireless sensor networks

Cited by 39 publications

References 28 publications

An Experimental Evaluation of the Reliability of LoRa Long-Range Low-Power Wireless Communication

An Experimental Evaluation of the Reliability of LoRa Long-Range Low-Power Wireless Communication

AirShare: Distributed coherent transmission made seamless

Data Driven Wireless Network Design: A Multi-level Modeling Approach

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