Opportunistic LoRa-based gateways for delay-tolerant sensor data collection in urban settings

Florita, Nikki John B.; Senatin, Alyssa Nicole M.; Zabala, Angela Margaret A.; Tan, Wilson M.

doi:10.1016/j.comcom.2020.02.066

Cited by 16 publications

(11 citation statements)

References 2 publications

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“…The work [ 44 ] investigates the optimal SF parameter and transmission power (

allocated to EDs in LoRa networks. The other efforts have been dealing with the issue of sensor data collection delay in urban areas focusing on LoRa based gateways [ 45 ]. Moreover, the energy consumption and reliability trade-off were also considered in [ 46 ].…”

Section: Related Workmentioning

confidence: 99%

A Reinforcement Learning Based Transmission Parameter Selection and Energy Management for Long Range Internet of Things

Yazid

Guerrero-González

Ez‐zazi

et al. 2022

Sensors

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Internet of Things (IoT) landscape to cover long-range applications. The LoRa-enabled IoT devices adopt an Adaptive Data Rate-based (ADR) mechanism to assign transmission parameters such as spreading factors, transmission energy, and coding rates. Nevertheless, the energy assessment of these combinations should be considered carefully to select an accurate combination. Accordingly, the computational and transmission energy consumption trade-off should be assessed to guarantee the effectiveness of the physical parameter tuning. This paper provides comprehensive details of LoRa transceiver functioning mechanisms and provides a mathematical model for energy consumption estimation of the end devices EDs. Indeed, in order to select the optimal transmission parameters. We have modeled the LoRa energy optimization and transmission parameter selection problem as a Markov Decision Process (MDP). The dynamic system surveys the environment stats (the residual energy and channel state) and searches for the optimal actions to minimize the long-term average cost at each time slot. The proposed method has been evaluated under different scenarios and then compared to LoRaWAN default ADR in terms of energy efficiency and reliability. The numerical results have shown that our method outperforms the LoRa standard ADR mechanism since it permits the EDs to gain more energy. Besides, it enables the EDs to stand more, consequently performing more transmissions.

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“…The work [ 44 ] investigates the optimal SF parameter and transmission power (

Section: Related Workmentioning

confidence: 99%

A Reinforcement Learning Based Transmission Parameter Selection and Energy Management for Long Range Internet of Things

Yazid

Guerrero-González

Ez‐zazi

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…Poor scalability and large waiting time are the major issues in this work. A game-theoretical approach is presented for assigning SF for end nodes for a particular time period that works upon service requirement [10]. As the work only considers interference, the transmission delay is high for all nodes.…”

Section: Introductionmentioning

confidence: 99%

Deep reinforcement learning based transmission policy enforcement and multi-hop routing in QoS aware LoRa IoT networks

Muthanna

Rafiq

et al. 2022

Computer Communications

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“…In recent years, with the rapid development of higher education in sculpture in China, more and more colleges have o ered sculpture-related majors. However, judging from the current urban construction process in China, the sculpture majors o ered by existing colleges still cannot meet the needs of urban development, and the quality of sculpture education needs to be improved [2]. It is precise because other professional technology in various aspects has also been applied to this eld, such as biotechnology, material science, and technology [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

“…e main contents are as follows: (1). the basic concepts and operation models of EC and the video-structured monitoring system are analyzed, and the concept of edge processor is used to improve the excessive and complex monitoring elements and provide links to the existing security monitoring system of urban sculpture scenes; (2). because of the dispersion and functionality of urban sculpture, a monitoring method combining UAV (unmanned aerial vehicles) with urban sculpture is proposed to improve the performance of the safety monitoring system of urban sculpture; and (3).…”

Section: Introductionmentioning

confidence: 99%

The Usage of Designing the Urban Sculpture Scene Based on Edge Computing

Zhu

2022

Computational Intelligence and Neuroscience

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To not only achieve the goal of urban cultural construction but also save the cost of urban sculpture space design, EC (edge computing) is combined with urban sculpture space design and planning first. Then it briefly discusses the service category, system architecture, advantages, and characteristics of urban sculpture, as well as the key points and difficulties of its construction, and the layered architecture of EC for urban sculpture spaces is proposed. Secondly, the cloud edge combination technology is adopted, and the urban sculpture is used as a specific function of the edge system node to conduct an in-depth analysis to build an urban sculpture safety supervision system architecture platform. Finally, the actual energy required for implementation is predicted and evaluated, the specific monitoring system coverage is set up, and some equations are made for calculating the energy consumption of the monitored machines according to the number of devices and route planning required by the urban sculpture safety supervision system. An optimization algorithm for energy consumption is proposed based on reinforcement learning and compared with the three control groups. The results show that when the seven monitoring devices cover detection points less than 800, the required energy consumption increases linearly. When the detection devices cover more than 800 detection points, the required energy consumption is stable and varies from 10000 to 12000; that is, when the number of monitoring devices is 7, the optimal number of monitoring points is about 800. When the number of detection points is fixed, increasing the number of monitoring devices in a small range can reduce the total energy consumption. The optimization algorithm based on the reinforcement learning proposal can obtain an approximate optimal solution. The research results show that the combination of edge computing and urban sculpture can expand the function of urban sculpture and make it serve people better.

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Opportunistic LoRa-based gateways for delay-tolerant sensor data collection in urban settings

Cited by 16 publications

References 2 publications

A Reinforcement Learning Based Transmission Parameter Selection and Energy Management for Long Range Internet of Things

A Reinforcement Learning Based Transmission Parameter Selection and Energy Management for Long Range Internet of Things

Deep reinforcement learning based transmission policy enforcement and multi-hop routing in QoS aware LoRa IoT networks

The Usage of Designing the Urban Sculpture Scene Based on Edge Computing

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