Joint slice-based spreading factor and transmission power optimization in LoRa smart city networks

Dawaliby, Samir; Bradai, Abbas; Pousset, Yannis

doi:10.1016/j.iot.2019.100121

Cited by 19 publications

(14 citation statements)

References 30 publications

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“…In this paper, we performed a comprehensive analysis of solutions that have been developed to optimize ADR algorithms. The proposed optimization techniques address specific challenges such as scalability [ 28 , 30 , 31 , 32 , 33 , 34 , 35 , 36 ], throughput [ 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 ] and energy efficiency [ 20 , 46 , 47 , 48 , 49 , 50 , 51 ]. Our analysis distinguished the approaches used and highlighted the challenges and performance in the studies considered.…”

Section: Comparison and Discussionmentioning

confidence: 99%

“…Computational complexity refers to the amount of resources required to run the algorithm, particularly time and memory requirements expressed as a function

, where

is the size of the input and

is the worst-case complexity, or the average-case complexity. In [ 44 ] the adaptive slicing and SF-TP configuration algorithm has a constant complexity of

for the static algorithm owing to its simplicity. However, the overall complexity of the proposed dynamic adaptive slicing and SF-TP algorithm and TOPG algorithm is

.…”

Section: Comparison and Discussionmentioning

confidence: 99%

“…ADR schemes that maximize throughput maximizing solutions for the ADR scheme were discussed in [ 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 ]. The ordered waterfalling technique used in [ 37 ] for even distribution of channel load between the end nodes in the system by equally distributing SFs and then channel utilization.…”

Section: Comparison and Discussionmentioning

confidence: 99%

“…The drawback is that energy consumption in the adaptive dynamic network slicing algorithm is increased compared to the static and dynamic configuration. The authors extended this work in [ 44 ] by taking into consideration some smart city applications representative of different QoS classifications and used a slice-based SF and TP configuration optimization. They proposed a new slicing optimization method called TOPG that is formulated on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Geometric Mean Method (GMM).…”

Section: Review Of Adaptive Data Rate Algorithmsmentioning

confidence: 99%

See 3 more Smart Citations

A Survey on Adaptive Data Rate Optimization in LoRaWAN: Recent Solutions and Major Challenges

Kufakunesu

Hancke

Abu‐Mahfouz

2020

Sensors

120

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Long-Range Wide Area Network (LoRaWAN) is a fast-growing communication system for Low Power Wide Area Networks (LPWAN) in the Internet of Things (IoTs) deployments. LoRaWAN is built to optimize LPWANs for battery lifetime, capacity, range, and cost. LoRaWAN employs an Adaptive Data Rate (ADR) scheme that dynamically optimizes data rate, airtime, and energy consumption. The major challenge in LoRaWAN is that the LoRa specification does not state how the network server must command end nodes pertaining rate adaptation. As a result, numerous ADR schemes have been proposed to cater for the many applications of IoT technology, the quality of service requirements, different metrics, and radio frequency (RF) conditions. This offers a challenge for the reliability and suitability of these schemes. This paper presents a comprehensive review of the research on ADR algorithms for LoRaWAN technology. First, we provide an overview of LoRaWAN network performance that has been explored and documented in the literature and then focus on recent solutions for ADR as an optimization approach to improve throughput, energy efficiency and scalability. We then distinguish the approaches used, highlight their strengths and drawbacks, and provide a comparison of these approaches. Finally, we identify some research gaps and future directions.

show abstract

Section: Comparison and Discussionmentioning

confidence: 99%

“…Computational complexity refers to the amount of resources required to run the algorithm, particularly time and memory requirements expressed as a function

, where

is the size of the input and

is the worst-case complexity, or the average-case complexity. In [ 44 ] the adaptive slicing and SF-TP configuration algorithm has a constant complexity of

for the static algorithm owing to its simplicity. However, the overall complexity of the proposed dynamic adaptive slicing and SF-TP algorithm and TOPG algorithm is

.…”

Section: Comparison and Discussionmentioning

confidence: 99%

Section: Comparison and Discussionmentioning

confidence: 99%

Section: Review Of Adaptive Data Rate Algorithmsmentioning

confidence: 99%

See 2 more Smart Citations

A Survey on Adaptive Data Rate Optimization in LoRaWAN: Recent Solutions and Major Challenges

Kufakunesu

Hancke

Abu‐Mahfouz

2020

Sensors

120

View full text Add to dashboard Cite

show abstract

“…Cano-Ortega et al [30] developed an ABC-based algorithm for the optimization of the configuration parameters of the LoRa LPWAN network in real time to achieve the best performance of the data traffic in real time with a minimum loss of information packets. Dawaliby et al [31] studied the optimization of the spreading factor configuration parameter of the LoRa LPWAN network in smart cities. Spinsante et al [32] conducted an experimental study to obtain a LoRa network design tool.…”

Section: Related Workmentioning

confidence: 99%

Design and Testing of a Power Analyzer Monitor and Programming Device in Industries with a LoRA LPWAN Network

Sánchez-Sutil

Caño

2021

Electronics

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Electrical installations represent an important part of the industry. In this sense, knowing the state of the electrical installation in real time through the readings of the installed power analyzers is of vital importance. For this purpose, the RS485 bus can be used, which most electrical installations already have. An alternative to the bus wiring and its distance limitation is the use of low-power wide area networks (LPWAN). The long range (LoRa) protocol is ideal for industries due to its low-power consumption and coverage of up to 10 km. In this research, a device is developed to control all the reading and programming functions of a power analyzer and to integrate the device into the LoRa LPWAN network. The power analyzer monitor and programming device (PAMPD) is inexpensive and small enough to be installed in electrical panels, together with the power analyzer, without additional wiring. The information collected is available in the cloud in real time, allowing a multitude of analysis be run and optimization in real time. The results support high efficiency in information transmission with average information loss rate of 3% and a low average transmission time of 30 ms.

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Spade to Spoon: An IoT-Based End to End Solution for Farmer Using Machine Learning in Precision Agriculture

Swain

Singh

Hashmi

2021

Algorithms for Intelligent Systems

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Joint slice-based spreading factor and transmission power optimization in LoRa smart city networks

Cited by 19 publications

References 30 publications

A Survey on Adaptive Data Rate Optimization in LoRaWAN: Recent Solutions and Major Challenges

A Survey on Adaptive Data Rate Optimization in LoRaWAN: Recent Solutions and Major Challenges

Design and Testing of a Power Analyzer Monitor and Programming Device in Industries with a LoRA LPWAN Network

Spade to Spoon: An IoT-Based End to End Solution for Farmer Using Machine Learning in Precision Agriculture

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