Improvements of Energy-Efficient Techniques in WSNs: A MAC-Protocol Approach

Quintero, Vanessa; Estevez, Claudio; Orchard, Marcos E.; Pérez, A.

doi:10.1109/comst.2018.2875810

Cited by 49 publications

(32 citation statements)

References 91 publications

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“…Generally, MAC mechanisms in WSNs are based on duty-cycling as a traditional approach for energy savings. Numerous algorithms have been proposed to adapt the MAC parameters of LR-WPANs to a broad range of applications [31,32]. However, energy efficiency and communication reliability are often conflicting requirements.…”

Section: Advances In Lr-wpan Networkingmentioning

confidence: 99%

Emerging Wireless Sensor Networks and Internet of Things Technologies—Foundations of Smart Healthcare

Gardasevic

Katzis

Bajić

et al. 2020

Sensors

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Future smart healthcare systems—often referred to as Internet of Medical Things (IoMT) – will combine a plethora of wireless devices and applications that use wireless communication technologies to enable the exchange of healthcare data. Smart healthcare requires sufficient bandwidth, reliable and secure communication links, energy-efficient operations, and Quality of Service (QoS) support. The integration of Internet of Things (IoT) solutions into healthcare systems can significantly increase intelligence, flexibility, and interoperability. This work provides an extensive survey on emerging IoT communication standards and technologies suitable for smart healthcare applications. A particular emphasis has been given to low-power wireless technologies as a key enabler for energy-efficient IoT-based healthcare systems. Major challenges in privacy and security are also discussed. A particular attention is devoted to crowdsourcing/crowdsensing, envisaged as tools for the rapid collection of massive quantities of medical data. Finally, open research challenges and future perspectives of IoMT are presented.

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Section: Advances In Lr-wpan Networkingmentioning

confidence: 99%

Emerging Wireless Sensor Networks and Internet of Things Technologies—Foundations of Smart Healthcare

Gardasevic

Katzis

Bajić

et al. 2020

Sensors

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“…During this state, it remains inactive and no longer performs any task. However, in idle state, a small amount of residual energy is still consumed due to the leakage of current [25]. In order to preserve energy, relevant circuitry of the device need to be switched off during this state.…”

Section: Energy State Model Of a Patient Monitoring Devicementioning

confidence: 99%

A Centralized Cluster-Based Hierarchical Approach for Green Communication in a Smart Healthcare System

Yang

Jan

Menon³

et al. 2020

IEEE Access

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The emergence of the Internet of Things (IoT) has revolutionized our digital and virtual worlds of connected devices. IoT is a key enabler for a wide range of applications in today's world. For example, in smart healthcare systems, the sensor-embedded devices monitor various vital signs of the patients. These devices operate on small batteries, and their energy need to be utilized efficiently. The need for green IoT to preserve the energy of these devices has never been more critical than today. The existing smart healthcare approaches adopt a heuristic approach for energy conservation by minimizing the duty-cycling of the underlying devices. However, they face numerous challenges in terms of excessive overhead, idle listening, overhearing, and collision. To circumvent these challenges, we have proposed a cluster-based hierarchical approach for monitoring the patients in an energy-efficient manner, i.e., green communication. The proposed approach organizes the monitoring devices into clusters of equal sizes. Within each cluster, a cluster head is designated to gather data from its member devices and broadcast to a centralized base station. Our proposed approach models the energy consumption of each device in various states, i.e., idle, sleep, awake, and active, and also performs the transitions between these states. We adopted an analytical approach for modeling the role of each device and its energy consumption in various states. Extensive simulations were conducted to validate our analytical approach by comparing it against the existing schemes. The experimental results of our approach enhance the network lifetime with a reduced energy consumption during various states. Moreover, it delivers a better quality of data for decision making on the patient's vital signs.

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“…The design of the MAC protocol for sensor networks is guided by the operational goals of the network, and it is usually an attempt to balance between two conflicting goals: achieving high-throughput and maintaining energy-efficient operation. Recent survey articles describe the taxonomy of MAC protocols and outline the development of different MAC protocols [33][34][35][36][37]. The MAC protocols for WSNs can be categorized into synchronous, asynchronous, frame-slotted, and multi-channel protocols.…”

Section: Uwb Network Architecturementioning

confidence: 99%

LocSpeck: A Collaborative and Distributed Positioning System for Asymmetric Nodes Based on UWB Ad-Hoc Network and Wi-Fi Fingerprinting

Sakr

Masiero

El‐Sheimy

2019

Sensors

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This paper presents LocSpeck, a collaborative and distributed indoor positioning system for dynamic nodes connected using an ad-hoc network, based on inter-node relative range measurements and Wi-Fi fingerprinting. The proposed system operates using peer-to-peer range measurements and does not need ultra-wideband (UWB) fixed anchor, nor it needs a predefined network topology. The nodes could be asymmetric in terms of the available sensors onboard, the computational resources, and the power capacity. This asymmetry adversely affects the positioning performance of the weaker nodes. Collaboration between different nodes is achieved through a distributed estimator without the need of a single centralized computing element. The ranging measurement component of the system is based on the DW1000 UWB transceiver chip from Decawave, which is attached to a set of smartphones equipped with asymmetric sensors. The distributed positioning filter fuses, locally on each node, the relative range measurements, the reading from the internal sensors, and the Wi-Fi received signal strength indicator (RSSI) readings to obtain an estimate of the position of each node. The described system does not depend on fixed UWB anchors and supports online addition and removal of nodes and dynamic node role assignment, either as an anchor or as a rover. The performance of the system is evaluated by real-world test scenarios using a set of four smartphones navigating an indoor environment on foot. The performance is compared to that of a commercial UWB-based system. The results presented in this paper show that weak mobile nodes, in terms of available positioning sensors, can benefit from collaboration with other nearby nodes.Sensors 2020, 20, 78 2 of 28 using relative measurements can augment the stand-alone observations of each node and improve the positioning accuracy of the ensemble [2,3]. The use of relative range measurements introduces an additional constraint to the position estimation filter, which can improve the positioning accuracy of the collaborating nodes [4]. Ultra-wideband (UWB) ranging devices are more immune to multipath errors because it can distinguish between different events with a precise temporal resolution, thanks to its large channel bandwidth. This makes the UWB-based devices capable of achieving centimeter-level ranging accuracy in ideal operating conditions [5].The objective of this paper is to present LocSpeck, a collaborative and distributed positioning system targeting smartphones and handheld applications, which uses UWB-based relative range measurements, along with Wi-Fi fingerprinting and inertial sensors. The system is evaluated experimentally, and the results are compared to the performance of Pozyx, a commercial UWB-based positioning system. The rest of this section will provide a brief overview of different ranging and positioning techniques used in UWB-based systems, and then it will discuss the different network architectures used for range-based positioning applications. UWB-Based RangingSensors 2020, 20,...

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Improvements of Energy-Efficient Techniques in WSNs: A MAC-Protocol Approach

Cited by 49 publications

References 91 publications

Emerging Wireless Sensor Networks and Internet of Things Technologies—Foundations of Smart Healthcare

Emerging Wireless Sensor Networks and Internet of Things Technologies—Foundations of Smart Healthcare

A Centralized Cluster-Based Hierarchical Approach for Green Communication in a Smart Healthcare System

LocSpeck: A Collaborative and Distributed Positioning System for Asymmetric Nodes Based on UWB Ad-Hoc Network and Wi-Fi Fingerprinting

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