<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e621" altimg="si49.svg"><mml:mrow><mml:mi>A</mml:mi><mml:mi>d</mml:mi><mml:mi>a</mml:mi><mml:mi>p</mml:mi><mml:mi>t</mml:mi><mml:mi>a</mml:mi><mml:mi>B</mml:mi><mml:mi>L</mml:mi><mml:mi>E</mml:mi></mml:mrow></mml:math>: Adaptive control of data rate, transmission power, and connection interval in bluetooth low energy

Park, Eunjeong; Lee, Myung-Sup; Kim, Hyung-Sin

doi:10.1016/j.comnet.2020.107520

Cited by 17 publications

(5 citation statements)

References 9 publications

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“…In the meantime, the nodes in the other rings (save the farthest ring) receive and transmit the packets to the gateway. As a result, the total energy consumption of the set of nodes at the farthest ring is identical to that of the single-hop uplink model using the equation (3). The set of nodes in the other rings, on the other hand, spend the energy that is equal to the sum of the energy consumed in transmitting, receiving, sleeping, and idle states.…”

Section: Network Structurementioning

confidence: 97%

“…IoT local connections now use three types of wireless technologies, which are classified by range: short-range, medium-range, and long-range networks. For sensing applications in short-range networks, wireless technology such as RFID/NFC [2], Bluetooth Low Energy (BLE) [3], IEEE 802.15.6-based wireless body area networks [4], or IEEE 802.11a/b/g/n/ad/ac [5] can be employed. Furthermore, wireless devices such as IEEE 802.15.3-based wireless low-rate personal area networks [6] and IEEE 802.15.4 Zigbee [7] are employed in short-range situations for low data rate applications.…”

Section: Introductionmentioning

confidence: 99%

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EAM-LoRaNet: Energy Aware Multi-hop LoRa Network for Internet of Things

Misbahuddin

Iqbal

Budiman

et al. 2022

KINETIK

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LoRa Technology is one of the devices used on Low-Power Wide Area Networks (LPWAN), which is a viable alternative wireless communication technology for the Internet of Things (IoT). The LoRa device is meant to traverse a large distance while using minimal power. However, because it uses single-hop communication, the Gateway's farthest nodes will die prematurely as a result of the increased energy usage. This research attempts to improve the range of LoRa networks utilizing multi-hop uplink communication while also reducing energy consumption by adjusting the LoRa transmission power to the lowest possible dBm in each hop. As a network model, a star topology-based tree made of some rings with a gateway as the central point is chosen. The performance of two forms of uplink communication, single-hop and multi-hop models was tested in terms of energy consumption and coverage. The results show that the network structure in the multi-hop uplink model can extend coverage over a greater distance while using less energy than the single-hop uplink model. This model can be used as a supplement to the LPWAN's uplink communication in the IoT to enhance the network's coverage range and lifetime.

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Section: Network Structurementioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

EAM-LoRaNet: Energy Aware Multi-hop LoRa Network for Internet of Things

Misbahuddin

Iqbal

Budiman

et al. 2022

KINETIK

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“…BLE allows for a low power consumption, but there are several works intended to improve even more the energy efficiency of the system working under BLE specifications [13,18,24,25]. These works dynamically change some parameters to adapt the energy consumption.…”

Section: A Energy Managementmentioning

confidence: 99%

Self-Powered Photovoltaic Bluetooth® Low Energy Temperature Sensor Node

et al. 2021

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A wireless self-powered temperature sensor node is presented. This sensor node is powered by a commercially available indoor photovoltaic energy harvester module. The sensor node uses Bluetooth ® Low Energy as wireless connection. Both the hardware and firmware have been optimized to obtain a very low power consumption. An auto adaptive energy management routine has been implemented to extend the autonomy of the sensor node. The system consumption and photovoltaic generation have been characterized at different conditions, obtaining a tool to estimate the autonomy of the system. The system has also been tested in a climatic chamber to study the effect of the temperature, a key factor that affects the power consumption, and hence the autonomy of the sensor.

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“…Further, BLE provides additional parameters that can be tuned to react to changes in the environment. AdaptaBLE controls the transmission power, BLE physical mode and connection interval to optimize the energy consumption and Quality of Service of BLE communication [15]. AdaptaBLE and eAFH are two orthogonal approaches, and can be used together to further improve Quality of Service and reliability.…”

Section: Related Workmentioning

confidence: 99%

eAFH: Informed Exploration for Adaptive Frequency Hopping in Bluetooth Low Energy

Poirot¹

2021

Preprint

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With more than 4 billion devices produced in 2020, Bluetooth and Bluetooth Low Energy (BLE) have become the backbone of the Internet of Things. Bluetooth and BLE mitigate interference in the crowded 2.4 GHz band via Adaptive Frequency Hopping (AFH), spreading communication over the entire spectrum, and further allows the exclusion of interfered channels. However, exclusion is challenging in dynamic environments or with user mobility: as a user moves around, interference affects new channels, forcing AFH to deprive itself of new frequencies, while some other excluded channels are now free of losses but remain excluded. Channel re-inclusion is a primordial, yet often left out, aspect of AFH, as it is non-trivial to assess the new situation of excluded frequencies.We present eAFH, a mechanism for channel exclusion-andinclusion. eAFH introduces informed exploration to AFH: using only past measurements, eAFH assesses which frequencies we are most likely to benefit from re-including in the hopping sequence. As a result, eAFH adapts in dynamic scenarios where interference varies over time. We show that eAFH achieves 98-99.5% linklayer reliability in the presence of dynamic Wifi interference with 1% control overhead and 40% higher channel diversity than state-of-the-art approaches.

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AdaptaBLE: Adaptive control of data rate, transmission power, and connection interval in bluetooth low energy

Cited by 17 publications

References 9 publications

EAM-LoRaNet: Energy Aware Multi-hop LoRa Network for Internet of Things

EAM-LoRaNet: Energy Aware Multi-hop LoRa Network for Internet of Things

Self-Powered Photovoltaic Bluetooth® Low Energy Temperature Sensor Node

eAFH: Informed Exploration for Adaptive Frequency Hopping in Bluetooth Low Energy

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