Optimizing power consumption in iot based wireless sensor networks using Bluetooth Low Energy

Nair, Karan; Kulkarni, Janhavi; Warde, Mansi; Dave, Zalak; Rawalgaonkar, Vedashree; Gore, Ganesh; Joshi, Jaya

doi:10.1109/icgciot.2015.7380533

Cited by 88 publications

(43 citation statements)

References 7 publications

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“…Therefore, owing to the widely distributed placement and complex functionality of the devices in the IoE environment, the management of power networks is a great challenge to ensure independent and cooperative work. Mesh networks with relatively high resistance to node failure are proposed to be used for large and complicated power supply systems to enhance the power efficiency and communication capability . Moreover, real‐time monitoring networks with failure prediction/diagnosis capability for power supply systems are essential to avoid irregularities/weak points in a timely manner .…”

Section: Power Supply Systems For the Ioementioning

confidence: 99%

“…Mesh networks with relatively high resistance to node failure are proposed to be used for large and complicated power supply systems to enhance the power efficiency and communication capability. 35 Moreover, real-time monitoring networks with failure prediction/diagnosis capability for power supply systems are essential to avoid irregularities/ weak points in a timely manner. 14 Due to the interrelated nature of these power supplies, providing backup power in the event of main power loss is an effective and efficient way to achieve self-sustainability of IoE devices.…”

Section: Power Managementmentioning

confidence: 99%

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Advances in the development of power supplies for the Internet of Everything

Fan

Liu

et al. 2019

InfoMat

102

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The Internet of Everything (IoE), which aims to realize information exchange and communications for anything with the Internet, has revolutionized our modern world. Serving as the driving force for devices in the IoE network, power supply systems play a fundamental role in the development of the IoE. However, due to the complexity, multifunctionality and wide‐scale deployment of diverse applications, power supply systems face great challenges, including distribution, connection, charging technologies, and management. In this review, some challenges and advances in the development of both power supply systems and their units are presented. In the overall system‐level field, establishing sustainable and maintenance‐free power supply systems through wireless connections, efficient power management and integrated energy harvesting and storage systems is highlighted. Additionally, the main performance metrics of power supply units are discussed, including energy density, service life, and self‐power ability. In addition, some directions of power quality assessment for both the system and unit levels of power supply systems are presented, aiming to provide insight into the future development of high‐performance power supply systems for the IoE.

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Section: Power Supply Systems For the Ioementioning

confidence: 99%

Section: Power Managementmentioning

confidence: 99%

Advances in the development of power supplies for the Internet of Everything

Fan

Liu

et al. 2019

InfoMat

102

View full text Add to dashboard Cite

show abstract

“…The open problem, in the contemporary transition period, is to adopt those new home automation technologies into already built and furnished houses, minimizing the annoyance during the installation phase. For this reason, the power management is a crucial factor, and despite the vastness of smart homes literature [19][20][21][22][23][24][25], it is still challenging to state that the batteries life issue has been solved.…”

Section: Introductionmentioning

confidence: 99%

Wireless Sensor Networks for Smart Homes: A Fuzzy-Based Solution for an Energy-Effective Duty Cycle

Pau

Salerno

2019

Electronics

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This paper introduces a fuzzy-based method that, according to the ratio of Throughput to Workload and the battery level, manages the sleeping time of devices in Wireless Sensor Networks (WSNs) for smart homes. The purpose of this work is a system that can be executed on off-the-shelf hardware and offers enhanced performance confronted with other approaches. The challenge here is to achieve a practical method that reaches the target while bypassing complex and computationally expensive solutions, which would diminish the possible applicability of the method in real scenarios. The retrieved results prove that the proposed approach outperforms other solutions, significantly prolonging the life of battery-powered wireless devices with also satisfactory values of the ratio Throughput to Workload. Besides, a proof-of-concept implementation on off-the-shelf devices confirms that the proposed method does not expect powerful hardware and can be surely implemented on a low-cost device.

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“…Wireless communications are the most used in modern sensor networks because, in a large scale network, it becomes difficult or impossible to link nodes by wired channels. In Wireless Sensor Network ( wsn ), nodes can have different communication technologies (eg, ZigBee, Bluetooth, rfid ,). Each technology has specific characteristics such as throughput and range.…”

Section: Introductionmentioning

confidence: 99%

Model driven framework to enhance sensor network design cycle

Kifouche

Hamouche²,

Kocik³

et al. 2019

Trans Emerging Tel Tech

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Recent advances in sensor network provide more and more equipment with a large amount of sensors and actuators. However, their adoptions in modern life face several challenges. First, sensor network design is complex and requires several steps including network sizing, hardware and software development, deployment, and data exploitation. Often, each step is managed by a particular tool. These tools are rarely connected to each other. Therefore, descriptions are required in each used tool. These multiple descriptions are costly in terms of development time and can lead to design errors. In order to address these issues, we propose a new model-driven framework named Modesene to efficiently design a sensor network for different kind of application. Modesene is designed to ensure four main process including multifacets modeling, network simulations, deployment, and data exploitation. The proposed framework supports sensor network tools by providing bridges with these tools. Therefore, one description in Modesene can be automatically transformed in each used tool. The framework can perform simulations and code generation. It promotes a data-driven approach; in fact, data obtained by simulations is used to drive design choices. We validate our framework through use case of smart building with two possible solutions. Based on Omnet++ simulator, Modesene can assess node lifetime, costs, and packets loss. Thereafter, the obtained results drive the choice of the suitable solution. Then, the code generator provides source codes for sensor nodes, gateway nodes, and for data exploitation. Compared to existing frameworks, Modesene deals with all design steps. Abbreviations: IoT, internet of things; WSN, Wireless sensor network Trans Emerging Tel Tech. 2019;30:e3560. wileyonlinelibrary.com/journal/ett communication technologies), and sink node (to collect and process data). Nodes can use different communication media to transmit and receive data (eg, wired channel, wireless channel, optical channel). Wireless communications are the most used in modern sensor networks because, in a large scale network, it becomes difficult or impossible to link nodes by wired channels. In Wireless Sensor Network (wsn), nodes can have different communication technologies (eg, ZigBee, 4 Bluetooth, 5 rfid, 6,7 ). Each technology has specific characteristics such as throughput and range. Sensor network development involves different steps including network sizing, software and hardware development, analyses and simulations, physical deployment, and data exploitation. These steps can be grouped in sensor network life cycle terminology. The motivations of our work are related to the fact that sensor network design requires to deal with many domains, involving many actors such as hardware engineer, software developer, and network expert. Data collected from sensor network may be also used by nontechnical actor, such as doctors in health domain. Therefore, many domain specific tools are used through the life cycle to help actors involved in each step. T...

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Optimizing power consumption in iot based wireless sensor networks using Bluetooth Low Energy

Cited by 88 publications

References 7 publications

Advances in the development of power supplies for the Internet of Everything

Advances in the development of power supplies for the Internet of Everything

Wireless Sensor Networks for Smart Homes: A Fuzzy-Based Solution for an Energy-Effective Duty Cycle

Model driven framework to enhance sensor network design cycle

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