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Special Issue "Low Energy Wireless Sensor Networks: Protocols, Architectures and Solutions"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: 25 January 2019

Special Issue Editor

Guest Editor
Assoc. Prof. Carles Gomez

Department of Network Engineering, Universitat Politecnica de Catalunya, 08860 Castelldefels, Spain
Website | E-Mail
Phone: 0034 934137206
Interests: low-power wireless technologies; Internet of Things; Wireless Sensor Networks; Bluetooth Low Energy; LPWAN; 6LoWPAN; 6Lo; IP-based protocols for constrained-node networks

Special Issue Information

Dear Colleagues,

Wireless Sensor Networks (WSNs) comprise connected sensor and actuator devices that allow to obtain information from and act upon the physical world in an intelligent manner, enabling innovative applications in a wide range of trending domains. Examples of the latter include smart cities, smart grid, smart home, industry 4.0, remote health, etc. 

For the sake of flexible and low-cost installation, many WSN devices run on autonomous, yet limited energy sources (e.g. batteries, energy harvesting solutions, etc.). In order to achieve multiyear device operation while fulfilling application requirements, energy conservation becomes a fundamental requirement in the design of suitable communication protocols and solutions for WSNs.

In the last two decades, a plethora of low-power wireless communication technologies and protocol architectures for WSN have been developed and/or standardized. Remarkably, the publication and success of IEEE 802.15.4, a seminal low-power radio interface, fuelled activity in the area. Among others, the IETF initiated work with the aim of supporting and optimizing IPv6 (and several companion protocols) over IEEE 802.15.4 networks. IPv6 support has been (and is still being) extended to many other low-power wireless technologies for WSNs, which contributes crucially to enabling the emerging paradigm of the Internet of Things (IoT).

Unfortunately, minimizing energy consumption often impacts negatively on other important performance parameters, such as latency, throughput, reliability or connectivity of a WSN. This Special Issue aims at collecting high quality research papers and review articles focusing on recent advances in low energy communications protocols, architectures and solutions for WSN devices. Original, high quality contributions that have not been published before and are not currently under review by other journals or conferences are sought.

Potential topics of interest include, but are not limited to, the following:

  • Low energy WPAN technologies: IEEE 802.15.4, Bluetooth Low Energy, etc.
  • LPWAN technologies: LoRa/LoRaWAN, SIGFOX, NB-IoT, etc.
  • Lightweight IP-based protocols: 6LoWPAN, 6Lo, 6TiSCH, RPL, CoAP, etc.
  • Low-energy protocol architectures: ZigBee, Thread, Z-Wave, EnOcean, etc.
  • Low-energy approaches for 5G-based WSNs
  • Energy-efficient routing and data aggregation for WSNs
  • Duty cycling techniques: scheduling, listen-after-send, channel sampling, etc.
  • Radio-triggered and visible light-triggered wake-up systems
  • Networking solutions for energy-harvesting devices
  • Energy-neutral WSNs
  • Cross-layer solutions for low energy consumption in WSNs
  • Low energy protocols for WSNs in smart-x environments: smart cities, smart home, smart grid, smart factories, smart agriculture, etc.
  • Low energy security mechanisms for WSNs
  • Low energy techniques for management of WSNs
  • Energy-efficient encoding formats for WSNs
  • Experimental, simulation and/or theoretical evaluation of low-energy WSNs

Assoc. Prof. Carles Gomez 
Guest Editor

Manuscript Submission Information

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Keywords

  • Low-energy wireless protocols
  • Low-energy WPAN
  • LPWAN
  • Internet of Things protocols: 6LoWPAN, 6Lo, 6TiSCH, RPL, CoAP
  • Low-energy WSNs in smart-x applications
  • Energy-harvesting WSNs

Published Papers (24 papers)

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Research

Open AccessArticle M2M Communication Assessment in Energy-Harvesting and Wake-Up Radio Assisted Scenarios Using Practical Components
Sensors 2018, 18(11), 3992; https://doi.org/10.3390/s18113992
Received: 14 August 2018 / Revised: 2 November 2018 / Accepted: 12 November 2018 / Published: 16 November 2018
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Abstract
Techniques for wireless energy harvesting (WEH) are emerging as a fascinating set of solutions to extend the lifetime of energy-constrained wireless networks, and are commonly regarded as a key functional technique for almost perpetual communications. For example, with WEH technology, wireless devices are
[...] Read more.
Techniques for wireless energy harvesting (WEH) are emerging as a fascinating set of solutions to extend the lifetime of energy-constrained wireless networks, and are commonly regarded as a key functional technique for almost perpetual communications. For example, with WEH technology, wireless devices are able to harvest energy from different light sources or Radio Frequency (RF) signals broadcast by ambient or dedicated wireless transmitters to support their operation and communications capabilities. WEH technology will have increasingly wider range of use in upcoming applications such as wireless sensor networks, Machine-to-Machine (M2M) communications, and the Internet of Things. In this paper, the usability and fundamental limits of joint RF and solar cell or photovoltaic harvesting based M2M communication systems are studied and presented. The derived theoretical bounds are in essence based on the Shannon capacity theorem, combined with selected propagation loss models, assumed additional link nonidealities, diversity processing, as well as the given energy harvesting and storage capabilities. Fundamental performance limits and available capacity of the communicating link are derived and analyzed, together with extensive numerical results evaluated in different practical scenarios, including realistic implementation losses and state-of-the-art printed supercapacitor performance figures with voltage doubler-based voltage regulator. In particular, low power sensor type communication applications using passive and semi-passive wake-up radio (WuR) are addressed in the study. The presented analysis principles and results establish clear feasibility regions and performance bounds for wireless energy harvesting based low rate M2M communications in the future IoT networks. Full article
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Open AccessArticle Optimized Gateway Placement for Interference Cancellation in Transmit-Only LPWA Networks
Sensors 2018, 18(11), 3884; https://doi.org/10.3390/s18113884
Received: 17 September 2018 / Revised: 29 October 2018 / Accepted: 3 November 2018 / Published: 11 November 2018
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Abstract
We study the placement of gateways in a low-power wide-area sensor network, when the gateways perform interference cancellation and when the model of the residual error of interference cancellation is proportional to the power of the packet being canceled. For the case of
[...] Read more.
We study the placement of gateways in a low-power wide-area sensor network, when the gateways perform interference cancellation and when the model of the residual error of interference cancellation is proportional to the power of the packet being canceled. For the case of two sensor nodes sending packets that collide, by which we mean overlap in time, we deduce a symmetric two-crescent region wherein a gateway can decode both collided packets. For a large network of many sensors and multiple gateways, we propose two greedy algorithms to optimize the locations of the gateways. Simulation results show that the gateway placements by our algorithms achieve lower average contention, which means higher packet delivery ratio in the same conditions, than when gateways are naively placed, for several area distributions of sensors. Full article
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Open AccessArticle Machine Learning Aided Scheme for Load Balancing in Dense IoT Networks
Sensors 2018, 18(11), 3779; https://doi.org/10.3390/s18113779
Received: 18 September 2018 / Revised: 31 October 2018 / Accepted: 1 November 2018 / Published: 5 November 2018
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Abstract
With the dramatic increase of connected devices, the Internet of things (IoT) paradigm has become an important solution in supporting dense scenarios such as smart cities. The concept of heterogeneous networks (HetNets) has emerged as a viable solution to improving the capacity of
[...] Read more.
With the dramatic increase of connected devices, the Internet of things (IoT) paradigm has become an important solution in supporting dense scenarios such as smart cities. The concept of heterogeneous networks (HetNets) has emerged as a viable solution to improving the capacity of cellular networks in such scenarios. However, achieving optimal load balancing is not trivial due to the complexity and dynamics in HetNets. For this reason, we propose a load balancing scheme based on machine learning techniques that uses both unsupervised and supervised methods, as well as a Markov Decision Process (MDP). As a use case, we apply our scheme to enhance the capabilities of an urban IoT network operating under the LoRaWAN standard. The simulation results show that the packet delivery ratio (PDR) is increased when our scheme is utilized in an unbalanced network and, consequently, the energy cost of data delivery is reduced. Furthermore, we demonstrate that better outcomes are attained when some techniques are combined, achieving a PDR improvement of up to about 50% and reducing the energy cost by nearly 20% in a multicell scenario with 5000 devices requesting downlink traffic. Full article
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Open AccessArticle A Simple Wireless Sensor Node System for Electricity Monitoring Applications: Design, Integration, and Testing with Different Piezoelectric Energy Harvesters
Sensors 2018, 18(11), 3733; https://doi.org/10.3390/s18113733
Received: 7 September 2018 / Revised: 31 October 2018 / Accepted: 31 October 2018 / Published: 2 November 2018
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Abstract
Real time electricity monitoring is critical to enable intelligent and customized energy management for users in residential, educational, and commercial buildings. This paper presents the design, integration, and testing of a simple, self-contained, low-power, non-invasive system at low cost applicable for such purpose.
[...] Read more.
Real time electricity monitoring is critical to enable intelligent and customized energy management for users in residential, educational, and commercial buildings. This paper presents the design, integration, and testing of a simple, self-contained, low-power, non-invasive system at low cost applicable for such purpose. The system is powered by piezoelectric energy harvesters (EHs) based on PZT and includes a microcontroller unit (MCU) and a central hub. Real-time information regarding the electricity consumption is measured and communicated by the system, which ultimately offers a dependable and promising solution as a wireless sensor node. The dynamic power management ensures the system to work with different types of PZT EHs at a wide range of input power. Thus, the system is robust against fluctuation of the current in the electricity grid and requires minimum adjustment if EH unit requires exchange or upgrade. Experimental results demonstrate that this unit is in a position to read and transmit 60 Hz alternating current (AC) sensor signals with a high accuracy no less than 91.4%. The system is able to achieve an operation duty cycle from <1 min up to 18 min when the current in an electric wire varies from 7.6 A to 30 A, depending on the characteristics of different EHs and intensity of current being monitored. Full article
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Open AccessArticle On-Demand LoRa: Asynchronous TDMA for Energy Efficient and Low Latency Communication in IoT
Sensors 2018, 18(11), 3718; https://doi.org/10.3390/s18113718
Received: 24 September 2018 / Revised: 23 October 2018 / Accepted: 29 October 2018 / Published: 1 November 2018
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Abstract
Energy efficiency is crucial in the design of battery-powered end devices, such as smart sensors for the Internet of Things applications. Wireless communication between these distributed smart devices consumes significant energy, and even more when data need to reach several kilometers in distance.
[...] Read more.
Energy efficiency is crucial in the design of battery-powered end devices, such as smart sensors for the Internet of Things applications. Wireless communication between these distributed smart devices consumes significant energy, and even more when data need to reach several kilometers in distance. Low-power and long-range communication technologies such as LoRaWAN are becoming popular in IoT applications. However, LoRaWAN has drawbacks in terms of (i) data latency; (ii) limited control over the end devices by the gateway; and (iii) high rate of packet collisions in a dense network. To overcome these drawbacks, we present an energy-efficient network architecture and a high-efficiency on-demand time-division multiple access (TDMA) communication protocol for IoT improving both the energy efficiency and the latency of standard LoRa networks. We combine the capabilities of short-range wake-up radios to achieve ultra-low power states and asynchronous communication together with the long-range connectivity of LoRa. The proposed approach still works with the standard LoRa protocol, but improves performance with an on-demand TDMA. Thanks to the proposed network and protocol, we achieve a packet delivery ratio of 100% by eliminating the possibility of packet collisions. The network also achieves a round-trip latency on the order of milliseconds with sensing devices dissipating less than 46 mJ when active and 1.83 μ W during periods of inactivity and can last up to three years on a 1200-mAh lithium polymer battery. Full article
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Open AccessArticle A Novel RPL Algorithm Based on Chaotic Genetic Algorithm
Sensors 2018, 18(11), 3647; https://doi.org/10.3390/s18113647
Received: 21 September 2018 / Revised: 24 October 2018 / Accepted: 25 October 2018 / Published: 27 October 2018
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Abstract
RPL (routing protocol for low-power and lossy networks) is an important candidate routing algorithm for low-power and lossy network (LLN) scenarios. To solve the problems of using a single routing metric or no clearly weighting distribution theory of additive composition routing metric in
[...] Read more.
RPL (routing protocol for low-power and lossy networks) is an important candidate routing algorithm for low-power and lossy network (LLN) scenarios. To solve the problems of using a single routing metric or no clearly weighting distribution theory of additive composition routing metric in existing RPL algorithms, this paper creates a novel RPL algorithm according to a chaotic genetic algorithm (RPL-CGA). First of all, we propose a composition metric which simultaneously evaluates packet queue length in a buffer, end-to-end delay, residual energy ratio of node, number of hops, and expected transmission count (ETX). Meanwhile, we propose using a chaotic genetic algorithm to determine the weighting distribution of every routing metric in the composition metric to fully evaluate candidate parents (neighbors). Then, according to the evaluation results of candidate parents, we put forward a new holistic objective function and a new method for calculating the rank values of nodes which are used to select the optimized node as the preferred parent (the next hop). Finally, theoretical analysis and a series of experimental consequences indicate that RPL-CGA is significantly superior to the typical existing relevant routing algorithms in the aspect of average end-to-end delay, average success rate, etc. Full article
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Open AccessArticle A Joining Procedure and Synchronization for TSCH-RPL Wireless Sensor Networks
Sensors 2018, 18(10), 3556; https://doi.org/10.3390/s18103556
Received: 3 August 2018 / Revised: 16 October 2018 / Accepted: 17 October 2018 / Published: 20 October 2018
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Abstract
Wireless Sensor Networks have become a key enabler for Industrial Internet of Things (IoT) applications; however, to adapt to the derived robust communication requirements, deterministic and scheduled medium access should be used, along with other features, such as channel hopping and frequency diversity.
[...] Read more.
Wireless Sensor Networks have become a key enabler for Industrial Internet of Things (IoT) applications; however, to adapt to the derived robust communication requirements, deterministic and scheduled medium access should be used, along with other features, such as channel hopping and frequency diversity. Implementing these mechanisms requires a correct synchronization of all devices in the network, a stage in deployment that can lead to non-operational networks. The present article presents an analysis of such situations and possible solutions, including the common current approaches and recommendations, and proposes a new beacon advertising method based on a specific Trickle Timer for the Medium Access Control (MAC) Time-Slotted Channel Hopping (TSCH) layer, decoupling from the timers in the network and routing layers. With this solution, improvements in connection success, time to join, and energy consumption can be obtained for the widely extended IEEE802.15.4e standard. Full article
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Open AccessArticle An Equilibrium Strategy-Based Routing Optimization Algorithm for Wireless Sensor Networks
Sensors 2018, 18(10), 3477; https://doi.org/10.3390/s18103477
Received: 13 September 2018 / Revised: 12 October 2018 / Accepted: 14 October 2018 / Published: 16 October 2018
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Abstract
In energy-constrained wireless sensor networks (WSNs), the design of an energy-efficient smart strategy is a key to extend the network lifetime, but the unbalance of energy consumption and node load severely restrict the long-term operation of the network. To address these issues, a
[...] Read more.
In energy-constrained wireless sensor networks (WSNs), the design of an energy-efficient smart strategy is a key to extend the network lifetime, but the unbalance of energy consumption and node load severely restrict the long-term operation of the network. To address these issues, a novel routing algorithm which considers both energy saving and load balancing is proposed in this paper. First of all, the transmission energy consumption, node residual energy and path hops are considered to create the link cost, and then a minimum routing graph is generated based on the link cost. Finally, in order to ensure the balance of traffic and residual energy of each node in the network, an “edge-cutting” strategy is proposed to optimize the minimum routing graph and turn it into a minimum routing tree. The simulation results show that, the proposed algorithm not only can balance the network load and prolong the lifetime of network, but meet the needs of delay and packet loss rate. Full article
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Open AccessArticle Adaptive Compressive Sensing and Data Recovery for Periodical Monitoring Wireless Sensor Networks
Sensors 2018, 18(10), 3369; https://doi.org/10.3390/s18103369
Received: 20 August 2018 / Revised: 29 September 2018 / Accepted: 30 September 2018 / Published: 9 October 2018
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Abstract
The development of compressive sensing (CS) technology has inspired data gathering in wireless sensor networks to move from traditional raw data gathering towards compression based gathering using data correlations. While extensive efforts have been made to improve the data gathering efficiency, little has
[...] Read more.
The development of compressive sensing (CS) technology has inspired data gathering in wireless sensor networks to move from traditional raw data gathering towards compression based gathering using data correlations. While extensive efforts have been made to improve the data gathering efficiency, little has been done for data that is gathered and recovered data with unknown and dynamic sparsity. In this work, we present an adaptive compressive sensing data gathering scheme to capture the dynamic nature of signal sparsity. By only re-sampling a few measurements, the current sparsity as well as the new sampling rate can be accurately determined, thus guaranteeing recovery performance and saving energy. In order to recover a signal with unknown sparsity, we further propose an adaptive step size variation integrated with a sparsity adaptive matching pursuit algorithm to improve the recovery performance and convergence speed. Our simulation results show that the proposed algorithm can capture the variation in the sparsities of the original signal and obtain a much longer network lifetime than traditional raw data gathering algorithms. Full article
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Open AccessArticle BATS: Adaptive Ultra Low Power Sensor Network for Animal Tracking
Sensors 2018, 18(10), 3343; https://doi.org/10.3390/s18103343
Received: 11 September 2018 / Revised: 25 September 2018 / Accepted: 28 September 2018 / Published: 7 October 2018
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Abstract
In this paper, the BATS project is presented, which aims to track the behavior of bats via an ultra-low power wireless sensor network. An overview about the whole project and its parts like sensor node design, tracking grid and software infrastructure is given
[...] Read more.
In this paper, the BATS project is presented, which aims to track the behavior of bats via an ultra-low power wireless sensor network. An overview about the whole project and its parts like sensor node design, tracking grid and software infrastructure is given and the evaluation of the project is shown. The BATS project includes a lightweight sensor node that is attached to bats and combines multiple features. Communication among sensor nodes allows tracking of bat encounters. Flight trajectories of individual tagged bats can be recorded at high spatial and temporal resolution by a ground node grid. To increase the communication range, the BATS project implemented a long-range telemetry system to still receive sensor data outside the standard ground node network. The whole system is designed with the common goal of ultra-low energy consumption while still maintaining optimal measurement results. To this end, the system is designed in a flexible way and is able to adapt its functionality according to the current situation. In this way, it uses the energy available on the sensor node as efficient as possible. Full article
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Open AccessArticle A Type of Annulus-Based Energy Balanced Data Collection Method in Wireless Rechargeable Sensor Networks
Sensors 2018, 18(9), 3150; https://doi.org/10.3390/s18093150
Received: 24 August 2018 / Revised: 12 September 2018 / Accepted: 13 September 2018 / Published: 18 September 2018
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Abstract
With the increasing number of ubiquitous terminals and the continuous expansion of network scale, the problem of unbalanced energy consumption in sensor networks has become increasingly prominent in recent years. However, a node scheduling strategy or an energy consumption optimization algorithm may be
[...] Read more.
With the increasing number of ubiquitous terminals and the continuous expansion of network scale, the problem of unbalanced energy consumption in sensor networks has become increasingly prominent in recent years. However, a node scheduling strategy or an energy consumption optimization algorithm may be not enough to meet the requirements of large-scale application. To address this problem a type of Annulus-based Energy Balanced Data Collection (AEBDC) method is proposed in this paper. The circular network is divided into several annular sectors of different sizes. Nodes in the same annulus-sector form a cluster. Based on this model, a multi-hop data forwarding strategy with the help of the candidate cluster headers is proposed to balance energy consumption during transmission and to avoid buffer overflow. Meanwhile, in each annulus, there is a Wireless Charging Vehicle (WCV) that is responsible for periodically recharging the cluster headers as well as the candidate cluster headers. By minimizing the recharging cost, the energy efficiency is enhanced. Simulation results show that AEBDC can not only alleviate the “energy hole problem” in sensor networks, but also effectively prolong the network lifetime. Full article
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Open AccessArticle Design and Analysis of Non-Binary LDPC-CPM System for Hybrid Check Matrix Construction Algorithm of WSN
Sensors 2018, 18(8), 2418; https://doi.org/10.3390/s18082418
Received: 22 June 2018 / Revised: 16 July 2018 / Accepted: 24 July 2018 / Published: 25 July 2018
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Abstract
In order to enhance the reliability and anti-interference performance of wireless sensor network (WSN) data transmission, this paper designs the low power scheme of the WSN from the angle of error correction coding and proposes the hybrid check matrix construction (HC) algorithm based
[...] Read more.
In order to enhance the reliability and anti-interference performance of wireless sensor network (WSN) data transmission, this paper designs the low power scheme of the WSN from the angle of error correction coding and proposes the hybrid check matrix construction (HC) algorithm based on iterative coding algorithms with linear coding complexity. The algorithm first improves the traditional iterative coding algorithm, making it suitable for non-binary low-density parity check (LDPC) codes. Then, the algorithm applies the backward iteration method to change the coding scheme and uses the check matrix construction method so that the progressive edge growth (PEG) algorithm has a lower triangular structure, which is used as a base matrix. An improved quasi-cyclic LDPC (QC-LDPC) algorithm, with a lower triangular structure, is used to generate a cyclic shift matrix and a finite domain coefficient matrix. Simultaneously, the short loop is eliminated and the optimal check matrix is selected for use in the channel coding process. The non-binary LDPC-CPM system is modeled and simulated. The simulation results show that the non-binary LDPC code constructed by the HC algorithm not only has linear coding and storage complexity but also has strong error correction capability. The design of non-binary LDPC-CPM system parameters can enhance the reliability, anti-jamming capability and reduce the complexity and reduce the complexity of the WSN. Full article
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Open AccessArticle The Bluetooth Mesh Standard: An Overview and Experimental Evaluation
Sensors 2018, 18(8), 2409; https://doi.org/10.3390/s18082409
Received: 28 June 2018 / Revised: 19 July 2018 / Accepted: 20 July 2018 / Published: 25 July 2018
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Abstract
Mesh networks enable a many-to-many relation between nodes, which means that each node in the network can communicate with every other node using multi-hop communication and path diversity. As it enables the fast roll-out of sensor and actuator networks, it is an important
[...] Read more.
Mesh networks enable a many-to-many relation between nodes, which means that each node in the network can communicate with every other node using multi-hop communication and path diversity. As it enables the fast roll-out of sensor and actuator networks, it is an important aspect within the Internet of Things (IoT). Utilizing Bluetooth Low Energy (BLE) as an underlying technology to implement such mesh networks has gained a lot of interest in recent years. The result was a variety of BLE meshing solutions that were not interoperable because of the lack of a common standard. This has changed recently with the advent of the Bluetooth Mesh standard. However, a detailed overview of how this standard operates, performs and how it tackles other issues concerning BLE mesh networking is missing. Therefore, this paper investigates this new technology thoroughly and evaluates its performance by means of three approaches, namely an experimental evaluation, a statistical approach and a graph-based simulation model, which can be used as the basis for future research. Apart from showing that consistent results are achieved by means of all three approaches, we also identify possible drawbacks and open issues that need to be dealt with. Full article
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Open AccessArticle Cooperative Dynamic Game-Based Optimal Power Control in Wireless Sensor Network Powered by RF Energy
Sensors 2018, 18(7), 2393; https://doi.org/10.3390/s18072393
Received: 1 June 2018 / Revised: 4 July 2018 / Accepted: 16 July 2018 / Published: 23 July 2018
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Abstract
This paper focuses on optimal power control in wireless sensor networks powered by RF energy, under the simultaneous wireless information and power transfer (SWIFT) protocol, where the information and power can be transmitted at the same time. We aim to maximize the utility
[...] Read more.
This paper focuses on optimal power control in wireless sensor networks powered by RF energy, under the simultaneous wireless information and power transfer (SWIFT) protocol, where the information and power can be transmitted at the same time. We aim to maximize the utility for each sensor through the optimal power control, considering the influences of both the SINR and the harvested energy. The utility maximization problem is formulated as a cooperative dynamic game of a given time duration. All the sensors cooperate together to control their transmission power to maximize the utility and agree to act cooperatively so that a team optimum can be achieved. As a result, a feedback Nash equilibrium solution for each sensor is given based on the dynamic programming theory. Simulation results verify the effectiveness of the proposed approach, by comparing the grand coalition solutions with the non-cooperative solutions. Full article
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Open AccessArticle Joint Energy Supply and Routing Path Selection for Rechargeable Wireless Sensor Networks
Sensors 2018, 18(6), 1962; https://doi.org/10.3390/s18061962
Received: 22 May 2018 / Revised: 15 June 2018 / Accepted: 15 June 2018 / Published: 17 June 2018
Cited by 2 | PDF Full-text (8275 KB) | HTML Full-text | XML Full-text
Abstract
The topic of network lifetime has been attracting much research attention because of its importance in prolonging the standing operation of battery-restricted wireless sensor networks, and the rechargeable wireless sensor network has emerged as a promising solution. In this paper, we propose a
[...] Read more.
The topic of network lifetime has been attracting much research attention because of its importance in prolonging the standing operation of battery-restricted wireless sensor networks, and the rechargeable wireless sensor network has emerged as a promising solution. In this paper, we propose a joint energy supply and routing path selection algorithm to extend the network lifetime based on an initiative power supply. We develop a two-stage energy replenishment strategy to supplement the energy consumption of nodes as much as possible. Furthermore, the influence of charging factors on the selection of next-hop nodes in data routing is considered. The simulation results show that our algorithm effectively prolong the network lifetime, and different demands of network delay and energy consumption can be obtained by dynamically adjusting parameters. Full article
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Open AccessArticle An Optimization Routing Algorithm for Green Communication in Underground Mines
Sensors 2018, 18(6), 1950; https://doi.org/10.3390/s18061950
Received: 24 April 2018 / Revised: 12 June 2018 / Accepted: 13 June 2018 / Published: 15 June 2018
PDF Full-text (899 KB) | HTML Full-text | XML Full-text
Abstract
With the long-term dependence of humans on ore-based energy, underground mines are utilized around the world, and underground mining is often dangerous. Therefore, many underground mines have established networks that manage and acquire information from sensor nodes deployed on miners and in other
[...] Read more.
With the long-term dependence of humans on ore-based energy, underground mines are utilized around the world, and underground mining is often dangerous. Therefore, many underground mines have established networks that manage and acquire information from sensor nodes deployed on miners and in other places. Since the power supplies of many mobile sensor nodes are batteries, green communication is an effective approach of reducing the energy consumption of a network and extending its longevity. To reduce the energy consumption of networks, all factors that negatively influence the lifetime should be considered. The degree constraint minimum spanning tree (DCMST) is introduced in this study to consider all the heterogeneous factors and assign weights for the next step of the evaluation. Then, a genetic algorithm (GA) is introduced to cluster sensor nodes in the network and balance energy consumption according to several heterogeneous factors and routing paths from DCMST. Based on a comparison of the simulation results, the optimization routing algorithm proposed in this study for use in green communication in underground mines can effectively reduce the network energy consumption and extend the lifetimes of networks. Full article
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Open AccessArticle New Energy Efficient Multi-Hop Routing Techniques for Wireless Sensor Networks: Static and Dynamic Techniques
Sensors 2018, 18(6), 1863; https://doi.org/10.3390/s18061863
Received: 30 April 2018 / Revised: 1 June 2018 / Accepted: 5 June 2018 / Published: 7 June 2018
Cited by 1 | PDF Full-text (13249 KB) | HTML Full-text | XML Full-text
Abstract
The performance of Wireless Sensor Networks (WSNs) faces a number of challenges. Of these challenges, energy consumption is considered a hot research area. Most WSN energy is used in transmitting the data from the sensor nodes either among each other or to a
[...] Read more.
The performance of Wireless Sensor Networks (WSNs) faces a number of challenges. Of these challenges, energy consumption is considered a hot research area. Most WSN energy is used in transmitting the data from the sensor nodes either among each other or to a Base Station (BS). For this reason, many routing protocols have been developed to facilitate the data dissemination in the WSNs. One of these protocols, Low Energy Adaptive Clustering Hierarchy (LEACH) has provided a distinctive hierarchical approach that efficiently forwards the nodes data to the BS, but it suffers from increased energy consumption and a significant decline in the network performance in the case of large-scale networks. This paper aims to present a new approach for splitting the whole sensor network into several levels. Thus, every node will be acting accordingly on its position and status. Further, two techniques, a static one and a dynamic one, have been developed to route the data between the levels. The simulation results demonstrated that the proposed techniques prolong the lifespan, improve the stability and raise the throughput of the network compared with the LEACH, the Improved MHT-LEACH (IMHT-LEACH), and the Enhancing DMHT-LEACH (EDMHT-LEACH) protocols. Full article
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Open AccessArticle Performance Evaluation of Energy-Autonomous Sensors Using Power-Harvesting Beacons for Environmental Monitoring in Internet of Things (IoT)
Sensors 2018, 18(6), 1709; https://doi.org/10.3390/s18061709
Received: 5 May 2018 / Revised: 21 May 2018 / Accepted: 22 May 2018 / Published: 25 May 2018
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Abstract
Environmental conditions and air quality monitoring have become crucial today due to the undeniable changes of the climate and accelerated urbanization. To efficiently monitor environmental parameters such as temperature, humidity, and the levels of pollutants, such as fine particulate matter (PM2.5) and volatile
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Environmental conditions and air quality monitoring have become crucial today due to the undeniable changes of the climate and accelerated urbanization. To efficiently monitor environmental parameters such as temperature, humidity, and the levels of pollutants, such as fine particulate matter (PM2.5) and volatile organic compounds (VOCs) in the air, and to collect data covering vast geographical areas, the development of cheap energy-autonomous sensors for large scale deployment and fine-grained data acquisition is required. Rapid advances in electronics and communication technologies along with the emergence of paradigms such as Cyber-Physical Systems (CPSs) and the Internet of Things (IoT) have led to the development of low-cost sensor devices that can operate unattended for long periods of time and communicate using wired or wireless connections through the Internet. We investigate the energy efficiency of an environmental monitoring system based on Bluetooth Low Energy (BLE) beacons that operate in the IoT environment. The beacons developed measure the temperature, the relative humidity, the light intensity, and the CO2 and VOC levels in the air. Based on our analysis we have developed efficient sleep scheduling algorithms that allow the sensor nodes developed to operate autonomously without requiring the replacement of the power supply. The experimental results show that low-power sensors communicating using BLE technology can operate autonomously (from the energy perspective) in applications that monitor the environment or the air quality in indoor or outdoor settings. Full article
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Open AccessArticle An Energy Balanced and Lifetime Extended Routing Protocol for Underwater Sensor Networks
Sensors 2018, 18(5), 1596; https://doi.org/10.3390/s18051596
Received: 26 March 2018 / Revised: 5 May 2018 / Accepted: 14 May 2018 / Published: 17 May 2018
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Abstract
Energy limitation is an adverse problem in designing routing protocols for underwater sensor networks (UWSNs). To prolong the network lifetime with limited battery power, an energy balanced and efficient routing protocol, called energy balanced and lifetime extended routing protocol (EBLE), is proposed in
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Energy limitation is an adverse problem in designing routing protocols for underwater sensor networks (UWSNs). To prolong the network lifetime with limited battery power, an energy balanced and efficient routing protocol, called energy balanced and lifetime extended routing protocol (EBLE), is proposed in this paper. The proposed EBLE not only balances traffic loads according to the residual energy, but also optimizes data transmissions by selecting low-cost paths. Two phases are operated in the EBLE data transmission process: (1) candidate forwarding set selection phase and (2) data transmission phase. In candidate forwarding set selection phase, nodes update candidate forwarding nodes by broadcasting the position and residual energy level information. The cost value of available nodes is calculated and stored in each sensor node. Then in data transmission phase, high residual energy and relatively low-cost paths are selected based on the cost function and residual energy level information. We also introduce detailed analysis of optimal energy consumption in UWSNs. Numerical simulation results on a variety of node distributions and data load distributions prove that EBLE outperforms other routing protocols (BTM, BEAR and direct transmission) in terms of network lifetime and energy efficiency. Full article
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Open AccessArticle An Adaption Broadcast Radius-Based Code Dissemination Scheme for Low Energy Wireless Sensor Networks
Sensors 2018, 18(5), 1509; https://doi.org/10.3390/s18051509
Received: 24 March 2018 / Revised: 30 April 2018 / Accepted: 7 May 2018 / Published: 10 May 2018
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Abstract
Due to the Software Defined Network (SDN) technology, Wireless Sensor Networks (WSNs) are getting wider application prospects for sensor nodes that can get new functions after updating program codes. The issue of disseminating program codes to every node in the network with minimum
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Due to the Software Defined Network (SDN) technology, Wireless Sensor Networks (WSNs) are getting wider application prospects for sensor nodes that can get new functions after updating program codes. The issue of disseminating program codes to every node in the network with minimum delay and energy consumption have been formulated and investigated in the literature. The minimum-transmission broadcast (MTB) problem, which aims to reduce broadcast redundancy, has been well studied in WSNs where the broadcast radius is assumed to be fixed in the whole network. In this paper, an Adaption Broadcast Radius-based Code Dissemination (ABRCD) scheme is proposed to reduce delay and improve energy efficiency in duty cycle-based WSNs. In the ABCRD scheme, a larger broadcast radius is set in areas with more energy left, generating more optimized performance than previous schemes. Thus: (1) with a larger broadcast radius, program codes can reach the edge of network from the source in fewer hops, decreasing the number of broadcasts and at the same time, delay. (2) As the ABRCD scheme adopts a larger broadcast radius for some nodes, program codes can be transmitted to more nodes in one broadcast transmission, diminishing the number of broadcasts. (3) The larger radius in the ABRCD scheme causes more energy consumption of some transmitting nodes, but radius enlarging is only conducted in areas with an energy surplus, and energy consumption in the hot-spots can be reduced instead due to some nodes transmitting data directly to sink without forwarding by nodes in the original hot-spot, thus energy consumption can almost reach a balance and network lifetime can be prolonged. The proposed ABRCD scheme first assigns a broadcast radius, which doesn’t affect the network lifetime, to nodes having different distance to the code source, then provides an algorithm to construct a broadcast backbone. In the end, a comprehensive performance analysis and simulation result shows that the proposed ABRCD scheme shows better performance in different broadcast situations. Compared to previous schemes, the transmission delay is reduced by 41.11~78.42%, the number of broadcasts is reduced by 36.18~94.27% and the energy utilization ratio is improved up to 583.42%, while the network lifetime can be prolonged up to 274.99%. Full article
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Open AccessArticle On the Energy Efficiency of On-Off Keying Transmitters with Two Distinct Types of Batteries
Sensors 2018, 18(4), 1291; https://doi.org/10.3390/s18041291
Received: 3 February 2018 / Revised: 16 April 2018 / Accepted: 18 April 2018 / Published: 23 April 2018
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Abstract
As nodes in wireless sensor networks are usually powered by nonrenewable batteries, energy efficient design becomes critical. This paper considers a battery-powered transmitter using on-off keying (OOK) modulation and studies its energy efficiency in terms of the battery’s energy consumption for per bit
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As nodes in wireless sensor networks are usually powered by nonrenewable batteries, energy efficient design becomes critical. This paper considers a battery-powered transmitter using on-off keying (OOK) modulation and studies its energy efficiency in terms of the battery’s energy consumption for per bit transmission (BECPB). In particular, the transmitter may use one of two distinct types of batteries with battery utilization factor (BUF) depending on discharge current. The first has an instantaneous discharge current (IDC)-based BUF, while the second has a mean discharge current (MDC)-based BUF. For each type of battery, a closed-form BECPB expression is derived under a Rayleigh channel when a prescribed symbol error rate (SER) is guaranteed. Then theoretical analysis is made to study the impact of battery characteristic parameter γ , communication distance d and bandwidth B on the BECPB. Finally, the analysis is corroborated by numerical experimental results, which reveal that: the BECPB for each type of battery increases with γ and d; the BECPB for the two batteries first decreases and then increases with B, and there exists the optimal bandwidth corresponding to the minimum BECPB; the battery with IDC-based BUF corresponds to a larger BECPB. When γ and d are large, the BECPB for each type of battery is significantly higher than that for the ideal battery whose BUF is aways 1. For instance, when γ = 0.015 , d = 90 m and B = 10 kHz, the BECPB for IDC-based and MDC-based battery is nearly 60% amd 25% higher than that of the ideal battery, respectively. Full article
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Open AccessArticle Sigma Routing Metric for RPL Protocol
Sensors 2018, 18(4), 1277; https://doi.org/10.3390/s18041277
Received: 3 March 2018 / Revised: 16 April 2018 / Accepted: 17 April 2018 / Published: 21 April 2018
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Abstract
This paper presents the adaptation of a specific metric for the RPL protocol in the objective function MRHOF. Among the functions standardized by IETF, we find OF0, which is based on the minimum hop count, as well as MRHOF, which is based on
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This paper presents the adaptation of a specific metric for the RPL protocol in the objective function MRHOF. Among the functions standardized by IETF, we find OF0, which is based on the minimum hop count, as well as MRHOF, which is based on the Expected Transmission Count (ETX). However, when the network becomes denser or the number of nodes increases, both OF0 and MRHOF introduce long hops, which can generate a bottleneck that restricts the network. The adaptation is proposed to optimize both OFs through a new routing metric. To solve the above problem, the metrics of the minimum number of hops and the ETX are combined by designing a new routing metric called SIGMA-ETX, in which the best route is calculated using the standard deviation of ETX values between each node, as opposed to working with the ETX average along the route. This method ensures a better routing performance in dense sensor networks. The simulations are done through the Cooja simulator, based on the Contiki operating system. The simulations showed that the proposed optimization outperforms at a high margin in both OF0 and MRHOF, in terms of network latency, packet delivery ratio, lifetime, and power consumption. Full article
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Open AccessArticle Adaptive LINE-P: An Adaptive Linear Energy Prediction Model for Wireless Sensor Network Nodes
Sensors 2018, 18(4), 1105; https://doi.org/10.3390/s18041105
Received: 15 February 2018 / Revised: 29 March 2018 / Accepted: 29 March 2018 / Published: 5 April 2018
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Abstract
In the context of wireless sensor networks, energy prediction models are increasingly useful tools that can facilitate the power management of the wireless sensor network (WSN) nodes. However, most of the existing models suffer from the so-called fixed weighting parameter, which limits their
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In the context of wireless sensor networks, energy prediction models are increasingly useful tools that can facilitate the power management of the wireless sensor network (WSN) nodes. However, most of the existing models suffer from the so-called fixed weighting parameter, which limits their applicability when it comes to, e.g., solar energy harvesters with varying characteristics. Thus, in this article we propose the Adaptive LINE-P (all cases) model that calculates adaptive weighting parameters based on the stored energy profiles. Furthermore, we also present a profile compression method to reduce the memory requirements. To determine the performance of our proposed model, we have used real data for the solar and wind energy profiles. The simulation results show that our model achieves 90–94% accuracy and that the compressed method reduces memory overheads by 50% as compared to state-of-the-art models. Full article
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Open AccessArticle A Data-Gathering Scheme with Joint Routing and Compressive Sensing Based on Modified Diffusion Wavelets in Wireless Sensor Networks
Sensors 2018, 18(3), 724; https://doi.org/10.3390/s18030724
Received: 8 February 2018 / Revised: 24 February 2018 / Accepted: 26 February 2018 / Published: 28 February 2018
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Abstract
Compressive sensing (CS)-based data gathering is a promising method to reduce energy consumption in wireless sensor networks (WSNs). Traditional CS-based data-gathering approaches require a large number of sensor nodes to participate in each CS measurement task, resulting in high energy consumption, and do
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Compressive sensing (CS)-based data gathering is a promising method to reduce energy consumption in wireless sensor networks (WSNs). Traditional CS-based data-gathering approaches require a large number of sensor nodes to participate in each CS measurement task, resulting in high energy consumption, and do not guarantee load balance. In this paper, we propose a sparser analysis that depends on modified diffusion wavelets, which exploit sensor readings’ spatial correlation in WSNs. In particular, a novel data-gathering scheme with joint routing and CS is presented. A modified ant colony algorithm is adopted, where next hop node selection takes a node’s residual energy and path length into consideration simultaneously. Moreover, in order to speed up the coverage rate and avoid the local optimal of the algorithm, an improved pheromone impact factor is put forward. More importantly, theoretical proof is given that the equivalent sensing matrix generated can satisfy the restricted isometric property (RIP). The simulation results demonstrate that the modified diffusion wavelets’ sparsity affects the sensor signal and has better reconstruction performance than DFT. Furthermore, our data gathering with joint routing and CS can dramatically reduce the energy consumption of WSNs, balance the load, and prolong the network lifetime in comparison to state-of-the-art CS-based methods. Full article
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