How Agile is the Adaptive Data Rate Mechanism of LoRaWAN?

Li, Shengyang; Raza, Usman; Khan, Aftab

doi:10.1109/glocom.2018.8647469

Cited by 101 publications

(86 citation statements)

References 8 publications

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“…The configuration of SFs and TPs has a significant impact on the delivery ratio of LoRa networks, as demonstrated by the results in the previous section. However, ADR requires a long time to determine the ideal set of parameters for large networks [64]. This results in a large number of dropped packets before the devices are configured with the ideal set of parameters.…”

Section: Network-aware Configurationmentioning

confidence: 99%

Efficient placement of edge computing devices for vehicular applications in smart cities

Premsankar

Ghaddar

Francesco

et al. 2018

NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium

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The author of this dissertation contributed to the development of the heuristic algorithms, the implementation of the simulator, the evaluation through simulation, the analysis of results, and writing the article.Publication IV empirically evaluates the impact of edge computing on emerging interactive applications and services. At the time of writing, there was no clear consensus on what specifically constitutes the edge of the network in edge computing. Thus, we first survey the state of the art in edge computing architectures and determine different deployment options for edge devices. Next, we experimentally evaluate edge computing when available at different physical locations and with different virtualization technologies. Specifically, we characterize the end-to-end latency (including

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Section: Network-aware Configurationmentioning

confidence: 99%

Efficient placement of edge computing devices for vehicular applications in smart cities

Premsankar

Ghaddar

Francesco

et al. 2018

NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium

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“…Reynders et al [5] propose a power and data rate (spreading factor, SF) allocation method based on clustering for the NS-3 simulator. Aligned to the problem we address, Abdelfadeel et al [6] assess the performance of Adaptive Data Rate (ADR)-enabled LoRaWAN, achieving results similar to our theoretical analysis, and Li et al [7] study ADR convergence, both through simulations.…”

mentioning

confidence: 76%

“…The main contributions in this letter are the performance analysis of ADR-enabled LoRaWAN and a simple closed expression for its outage probability in steady-state operation. We assume the network reaches steady-state when ADR converges for all nodes, and their SF and transmit power configuration remain unchanged, as defined in [7]. The performance analysis shows that ADR is an important feature of the technology and that it must be taken into account.…”

mentioning

confidence: 99%

“…The performance analysis shows that ADR is an important feature of the technology and that it must be taken into account. The closed-form expression assumes, as in [7], that a network with static nodes converges to RSSI-based SF and transmit power figures, implementing, in practice, a truncated channel inversion scheme [8]. Also, transient periods occur when channel or network conditions change, and the time to return to steady-state depends on application and deployment scenario [7].…”

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confidence: 99%

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Performance Analysis of Single-Cell Adaptive Data Rate-Enabled LoRaWAN

Hoeller

Souza

Montejo‐Sánchez

et al. 2020

IEEE Wireless Commun. Lett.

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LoRaWAN enables massive connectivity for Internet-of-Things applications. Many published works employ stochastic geometry to derive outage models of LoRaWAN over fading channels assuming fixed transmit power and distance-based spreading factor (SF) allocation. However, in practice, LoRaWAN employs the Adaptive Data Rate (ADR) mechanism, which dynamically adjusts SF and transmit power of nodes based on channel state. The community addressed the performance of ADR using simulations, but analytical models have not been introduced. In this letter, we seek to close this gap. We build over an analytical LoRaWAN model to consider the performance of steady-state ADR-enabled LoRaWAN. We derive outage expressions and an optimization procedure to maximize the number of users under reliability constraints. Results show that power allocation reduces interference and improves network capacity while reducing average power.

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“…Among other notable LoRaWAN features can be listed the Adaptive Data Rate (ADR) [16] mechanism. This mechanism enables the adaptation of the SF and the transmit power to the channel conditions experienced by each particular ED.…”

Section: A Lorawan Technologymentioning

confidence: 99%

Improving the Energy Efficiency of a LoRaWAN by a UAV-based Gateway

Tiurlikova

Stepanov

Mikhaylov

2019

2019 11th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)

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The Internet of Things (IoT) devices and applications are spreading all over around us to become the cardiovascular infrastructure for the data of the cyber-physical systems of the future. The implementation of a reliable collection of telemetry data within various application domains, including medicine, safety, and security, industry, smart cities, or environmental monitoring, to name just a few, is among the major challenges still to be solved. Importantly, many of the use cases imply a huge geographic area span or operation in remote areas with limited infrastructure availability and poor reachability. To address these scenarios in this paper, we propose a combination of the two technologies the Low Power Wide Area Network (LPWAN) and the Unmanned Aerial Vehicles (UAVs). Specifically, we study the energy utility and the communication performance of introducing a UAV-based GW into an LPWAN based on the LoRaWAN technology. The results of our simulations show that a UAVbased GW enables to reduce the mean energy consumption for communication in the network by up to 59%. Depending on the UAV speed, the communication performance in terms of the packet delivery ratio can either increase or decrease by several percentage points.

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How Agile is the Adaptive Data Rate Mechanism of LoRaWAN?

Cited by 101 publications

References 8 publications

Efficient placement of edge computing devices for vehicular applications in smart cities

Efficient placement of edge computing devices for vehicular applications in smart cities

Performance Analysis of Single-Cell Adaptive Data Rate-Enabled LoRaWAN

Improving the Energy Efficiency of a LoRaWAN by a UAV-based Gateway

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