Solution For Wireless Sensor Networks Research Articles

Hybridized Fuzzy Based Clustering For Wireless Sensor Networks Based On Cognitive Internet Of Things

Wireless sensor network explosive growth has increased demand for radio spectrum and has created problems with spectrum shortage since different wireless services and technologies have already been assigned the full range of wireless sensor networks. Cognitive radio has become a promising solution for resource-controlled wireless sensor network to access the reserved under-used frequency bands resourcefully. Artificial intelligence algorithms allow sensor nodes to avoid crowded congested bands by detecting under utilized licensed bands and to decide to adapt their transmission parameters. However, clusters are based on fixed spectrum distribution and cannot deal with the dynamic spectrum allocation required for future generation networks. Clusters are used to reduce power usage and support scalability of sensor networks. This article proposes an Hybridized Fuzzy Clustering (HFC), which groups adjacent nodes with comparable sets of idle channels and optimally forming power-efficient clusters based on three fuzzy energy parameters, proximity to the base station, and the level of the node to determine the possibility of each node being a cluster head.

CARMA: Channel-Aware Reinforcement Learning-Based Multi-Path Adaptive Routing for Underwater Wireless Sensor Networks

Routing solutions for multi-hop underwater wireless sensor networks suffer significant performance degradation as they fail to adapt to the overwhelming dynamics of underwater environments. To respond to this challenge, we propose a new data forwarding scheme where relay selection swiftly adapts to the varying conditions of the underwater channel. Our protocol, termed CARMA for Channel-aware Reinforcement learning-based Multi-path Adaptive routing, adaptively switches between single-path and multi-path routing guided by a distributed reinforcement learning framework that jointly optimizes route-long energy consumption and packet delivery ratio. We compare the performance of CARMA with that of three other routing solutions, namely, CARP, QELAR and EFlood, through SUNSET-based simulations and experiments at sea. Our results show that CARMA obtains a packet delivery ratio that is up to 40% higher than that of all other protocols. CARMA also delivers packets significantly faster than CARP, QELAR and EFlood, while keeping network energy consumption at bay.

In-Band Network Telemetry in Industrial Wireless Sensor Networks

With the emergence of the Internet of Things (IoT) and Industry 4.0 concepts, industrial applications are going through a tremendous change that is imposing increasingly diverse and demanding network dynamics and requirements with a wider and more fine-grained scale. Therefore, there is a growing need for more flexible and reconfigurable industrial networking solutions complemented with powerful monitoring and management functionalities. In this sense, this paper presents a novel efficient network monitoring and telemetry solution for Industrial Wireless Sensor Networks mainly focusing on the 6TiSCH Network stack, a complete protocol stack for ultra-reliable ultra-low-power wireless mesh networks. The proposed monitoring solution creates a flexible and powerful in-band network telemetry design with minimized resource consumption and communication overhead while supporting a wide range of monitoring operations and strategies for dealing with various network scenarios and use cases. Besides, the technical capabilities and characteristics of the proposed solution are evaluated via a real-life implementation, practical and theoretical analysis. These experiments demonstrate that in-band telemetry can provide ultra-efficient network monitoring operations without any effect on the network behavior and performance, validating its suitability for Industrial Wireless Sensor Networks.

Energy storage solution for wireless sensor network used in bridge surface corrosion monitoring

This Letter presents a radio-frequency energy storage solution for monitoring corrosion on bridge in wireless sensor network system. In this monitoring system, wireless terminals and sensors are installed on the bridges to monitor surface corrosion remotely. The proposed energy storage module to supply power to the sensors consists of a rectifier, a supercapacitor, and a DC–DC boost converter. The rectifier circuit is designed to convert 920 MHz RF energy to DC source. Experimental results demonstrate that the harvested energy can power up the sensor nodes for several times in a week, at input power density of 0.81 μW/cm2.

Network Restoration in Wireless Sensor Networks for Next-Generation Applications

This paper investigates highly efficient network restoration models for wireless sensor networks (WSNs) to be deployed for next-generation (xG) applications. The developed network restoration models are designed with two main goals in mind. The first goal is to optimize network resource utilization, and the second is to protect the network against failures. In realizing the goal of optimizing resource usage, a peculiar feature of WSNs is exploited, namely, their ability to remain in active service even when one or more of their active elements (sensor nodes and/or connecting links) fail. To achieve the second goal of network protection, we leverage the advantage of p-cycle-based restoration solutions - the fact that they can provide ring-like recovery speeds with mesh-like capacity efficiencies - in developing optimal p-cycle restoration models that provide sufficient protection for the network against both link and node failures. In the restoration models developed, we employ a selection process that jointly considers the shortest lengths, best topologies, and capacity requirements of the available p-cycles in achieving new capacity-optimal p-cycle-based restoration solutions for the network. Comparative results obtained show that our developed selection-based capacity-efficient p-cycle restoration solutions for WSNs outperform other similar approaches for both network realization and protection, making them particularly ideal for xG applications.

E‐LiteSense: Self‐adaptive energy‐aware data sensing in WSN environments

SummaryCurrently deployed in a wide variety of applicational scenarios, wireless sensor networks (WSNs) are typically a resource‐constrained infrastructure. Consequently, characteristics such as WSN adaptability, low‐overhead, and low‐energy consumption are particularly relevant in dynamic and autonomous sensing environments where the measuring requirements change and human intervention is not viable. To tackle this issue, this article proposes e‐LiteSense as an adaptive, energy‐aware sensing solution for WSNs, capable of auto‐regulate how data are sensed, adjusting it to each applicational scenario. The proposed adaptive scheme is able to maintain the sensing accuracy of the physical phenomena, while reducing the overall process overhead. In this way, the adaptive algorithm relies on low‐complexity rules to establish the sensing frequency weighting the recent drifts of the physical parameter and the levels of remaining energy in the sensor. Using datasets from WSN operational scenarios, we prove e‐LiteSense effectiveness in self‐regulating data sensing accurately through a low‐overhead process where the WSN energy levels are preserved. This constitutes a step‐forward for implementing self‐adaptive energy‐aware data sensing in dynamic WSN environments.

A dynamic technique to enhance quality of service in software-defined network-based wireless sensor network (DTEQT) using machine learning

Wireless Sensor Network (WSN) is the interconnection between things or objects embedded with hardware and software. In WSN, small end devices (like sensors) and high end devices (like servers) are connected to the Internet. For WSN enabled in Software-Defined Network (SDN), the routers are controlled using a controller server node. It is a dynamic network due to the presence of mobile nodes and energy constrained nodes. The routing is the process of detecting route from source to target. In dynamic networks like WSN, routing is a challengeable task. This paper is to provide a routing solution for backboneless SDN-enabled WSN. The proposed work enhances routing Quality of Service (QoS) in WSN. The paths are dynamically reallocated to reduce the packet loss.

Proposition and Real-Time Implementation of an Energy-Aware Routing Protocol for a Software Defined Wireless Sensor Network.

A wireless sensor network (WSN) has achieved significant importance in tracking different physical or environmental conditions using wireless sensor nodes. Such types of networks are used in various applications including smart cities, smart building, military target tracking and surveillance, natural disaster relief, and smart homes. However, the limited power capacity of sensor nodes is considered a major issue that hampers the performance of a WSN. A plethora of research has been conducted to reduce the energy consumption of sensor nodes in traditional WSN, however the limited functional capability of such networks is the main constraint in designing sophisticated and dynamic solutions. Given this, software defined networking (SDN) has revolutionized traditional networks by providing a programmable and flexible framework. Therefore, SDN concepts can be utilized in designing energy-efficient WSN solutions. In this paper, we exploit SDN capabilities to conserve energy consumption in a traditional WSN. To achieve this, an energy-aware multihop routing protocol (named EASDN) is proposed for software defined wireless sensor network (SDWSN). The proposed protocol is evaluated in a real environment. For this purpose, a test bed is developed using Raspberry Pi. The experimental results show that the proposed algorithm exhibits promising results in terms of network lifetime, average energy consumption, the packet delivery ratio, and average delay in comparison to an existing energy efficient routing protocol for SDWSN and a traditional source routing algorithm.

SD-WISE: A Software-Defined WIreless SEnsor network

In this paper we introduce SD-WISE, a Software-Defined WIreless SEnsor networking solution for Wireless Sensor (and actuator) Networks (WSNs). SD-WISE has several unique features making it a flexible and expandable solution that can be applied in heterogeneous application domains. Its fundamental feature is that it provides software abstractions of the nodes’ resources on both the controller and the nodes sides. By leveraging these abstractions, SD-WISE (i) extends the Software Defined Networking (SDN) approach to WSNs, introducing a more flexible way to define flows as well as the possibility to control the duty cycles of the node radios to increase energy efficiency; (ii) enables Network Function Virtualization (NFV) in WSNs; (iii) leverages the tight interplay between trusted hardware and software to support regulation compliant behavior of sensor nodes. In this paper SD-WISE is introduced, its major operations are described, and its features are demonstrated in three relevant scenarios, thus assessing the effectiveness of the approach.

Enabling Communication Networks for Water Quality Monitoring Applications: A Survey

This paper considers newly emerging wireless technologies that can be explored for potential exploitation in the future wireless sensor network solutions for water quality monitoring applications. The reviewed technologies promise to address long-standing issues that confront existing wireless sensor network solutions devoted to the monitoring of water quality parameters. Such issues include energy efficiency and long-range water quality data communication. These issues can be attributed to the shortcomings of legacy communication networks commonly combined with wireless sensor network solutions, due to a discrepancy caused by traditionally powering the sensors nodes using batteries. In particular, some of the legacy communication networks suffer from short communication range, while others are limited by high power consumption. These shortcomings provide scope for the utilization of newly emerging solutions identified in this study to advance the field of a wireless sensor network for water quality monitoring. To achieve this, three key categories of communication networks have been recommended in this paper, including their architectural design and network deployment for water quality monitoring applications. Also, this paper provides future directions on the identified communication networks to enhance their performance for the next-generation of wireless sensor network solutions for water quality monitoring applications.

Mist and Edge Storage: Fair Storage Distribution in Sensor Networks

Sensor/Actuator devices are currently being massively adopted, often as nodes of larger sensor networks. These sensor networks are typically dedicated to context acquisition (e.g., get temperature) as well as providing acting services (e.g., open the blinds). However, regarding their own data storage, data is usually sent to Fog/Cloud servers. Fog/Cloud storage solutions provide several advantages over sensor network storage solutions, but also some drawbacks. For instance, in Cloud environments, privacy and legal issues may appear, while in Fog, additional costly hardware must be purchased and maintained, at least a server with redundant storage or many servers when distributed data storage is required. Nowadays, sensor nodes count in thousands around us, and they have significantly increased their storage and computational capabilities over the past few years. Therefore, traditional Fog/Cloud storage solutions could be combined or even replaced by Mist/Edge storage solutions for many use cases. A principal contribution of this paper is a novel data distribution and replication storage solution for wireless sensor networks, the first to consider sensor node heterogeneity to find the optimal storage replication according to node capabilities. The solution has been carefully planned and implemented to run even in very low-end microcontrollers, that lives in many of our surrounding smart devices. Other contributions include data comparing Mist/Edge and Amazon S3 regular storage, showing that there remains plenty of room for research into Mist/Edge storage, as well as into the industry itself.

A Survey on Wireless Sensor Network-Based IoT Designs For Gas Leakage Detection and Fire-Fighting Applications

The rapid advancements in wireless sensor network (WSN) technology gave impetus for large-scale deployment of Internet-of-things (IoT) services and applications. One of the envisioned IoT applications is the use of wireless sensor nodes in gas-leakage monitoring and detection applications. Such IoT applications can provide better protection to fire fighters and provide safety and early-warning gas detection alarms within a timely manner for individuals, factories and institutions. In this article, we highlight the unique characteristics of WSNs, discuss the main WSN design requirements associated with gas leakage and monitoring applications, discuss main differences between data collection- and event detection-based WSN solutions and present a detailed overview of the works that have been accomplished on providing WSN solutions for gas leakage detection and monitoring.

Reliable Through-Metal Wireless Communication Using Magnetic Induction

Wireless sensors or robots in metal-constrained environments leverage through-metal wireless communications to send data and receive instructions. It is well-known that wireless radio frequency (RF) signals cannot penetrate through metal efficiently, which prevents us from applying existing wireless solutions. Moreover, most applications, e.g., metal inspection robots in an oil pipeline, require noncontact wireless communications, where the ultrasonic signals do not work. To this end, we propose to use magnetic induction communication to provide a reliable and flexible solution for wireless sensor and robotic networks in metal-constrained environments. We consider the transceivers are located on two different sides of a metal wall. Then, we develop an analytical model to obtain the optimal configurations of the magnetic coil and the carrier frequency to maximize the communication channel capacity. The received power and wireless channel bandwidth are studied. The results show that the optimal carrier frequency is around 1 kHz. In addition, we study the negative effects caused by coil misalignment and interference, which are circumvented by leveraging a coil array with optimal receiving strategy. The results are evaluated using numerical simulation and verified by finite element method-based simulation.

SPEEDA: A Secure Protocol and Energy Efficient for Data Aggregation in Wireless Sensor Networks

Wireless Sensor Networks (WSN) consists of a set of small and resources-constrained devices. They have received much attention over the last few years for the study and development of a plethora of potential applications. However, the common denominator of all applications of these sensor networks is the vulnerability of micro-sensors because of their limited material resources the most constraining of which is energy. In fact, wireless sensors are limited in terms of calculation, storage, battery, etc. Therefore, every possible solution that aims to conserve these resources is extensively sought. Thus, a great deal of researches has been conducted leading to an effective technique answering the established problem. This solution concerns the aggregation of data which is one of the techniques that is actually considered as an essential paradigm for sensor networks since it tends to save computation and communication resources. Data aggregation allows in-network processing which leads to lesser packet transmissions and reduces redundancy, and therefore, helps in increasing network’s overall lifetime. However, sensor networks are usually deployed in unattended and hostile environments.Thus, the designer should not only consider the limited resources of the sensor nodes but also the security threats that can occur in an easily accessible network to the attacker. In this paper, we will give an overview study of the existing data aggregation solutions in wireless sensor networks then, we will propose a new efficient and secure approach to aggregation which can be evaluated with specific criteria.

A Low-Power Compression-Based CMOS Image Sensor With Microshift-Guided SAR ADC

This brief presents a low-power compression-based CMOS image sensor for wireless vision applications. The sensor implements low-bit-depth imaging with planned sensor distortion (PSD) to effectively compress both data bandwidth and processing power while maintaining high reconstruction image quality. Accordingly, a column-parallel microshift-guided successive-approximation-register (SAR) ADC is proposed to enable 3-bit PSD imaging based on a ${3\times 3}$ pattern. To support normal imaging with low area overhead, the circuit is reconfigurable as an 8-bit SAR/single-slope ADC. The data bandwidth is further compressed by a customized lossless encoder based on predictive coding and run length coding. A ${256\times 216}$ prototype imaging system composed of the compression-based image sensor and the lossless encoder is fabricated in a 0.18- ${\mu }\text{m}$ standard CMOS process. Measurement results show that the image sensor achieves 3 bit/pixel (bpp) with 34.9-dB reconstruction peak signal-to-noise ratio (PSNR) and 0.91 structural similarity index (SSIM). With 1/4 spatial downsampling and lossless encoding, 0.31 bpp is obtained with 29.2-dB PSNR and 0.83 SSIM. The sensor consumes $14.8~{\mu }\text{W}$ (full resolution) and $4.3~{\mu }\text{W}$ (downsampling) at 15 fps, achieving state-of-the-art FoMs of 17.8 and 5.2 pJ/pixel $\cdot $ frame, respectively. Including the encoder, the overall system dissipates as low as $1.2~{\mu }\text{J}$ /frame, making it an attractive solution for wireless sensor networks.

A New Centralized Solution for Multi-event Wireless Sensor and Actor Networks

A New Centralized Solution for Multi-event Wireless Sensor and Actor Networks

Multistatic Scatter Radio Sensor Networks for Extended Coverage

Scatter radio, i.e., communication by means of reflection, has been recently proposed as a viable ultra-low power solution for wireless sensor networks (WSNs). This paper offers a detailed comparison between monostatic and multistatic scatter radio architectures. In monostatic architecture, the reader consists of both the illuminating transmitter and the receiver of signals scattered back from the sensors. The multistatic architecture includes several ultra-low cost illuminating carrier emitters and a single reader. Maximum-likelihood coherent and noncoherent bit error rate (BER), diversity order, average information, and energy outage probability comparison is performed, under dyadic Nakagami fading and filling a gap in the literature. It is found that: 1) diversity order, BER, and tag location-independent performance bounds of multistatic architecture outperform monostatic; 2) energy outage due to radio frequency (RF) harvesting for passive tags, is less frequent in multistatic than monostatic architecture; and 3) multistatic coverage is higher than monostatic. Furthermore, a proof-of-concept digital multistatic scatter radio WSN with a single receiver, four low-cost emitters, and multiple ambiently-powered low-bitrate tags, perhaps the first of its kind, is experimentally demonstrated (at 13 dBm transmission power), covering an area of 3500 m2. Research findings are applicable in the industries of WSNs, RF identification, and emerging Internet-of-Things.

Max-SNR Opportunistic Routing for Large-Scale Energy Harvesting Sensor Networks

Providing sensors with adequate energy in large-scale wireless sensor networks (WSNs) over long periods is a major bottleneck in their implementation. In this regard, energy harvesting (EH), i.e., capturing energy from ambient renewable energy sources, is a promising solution for low-power and low data-rate WSNs. The randomness in the energy available forces the redesign of WSN protocols. Our specific interest here is to enable the delivery of sensed data to a fusion center (FC) in a large-scale EH-WSN. We propose a novel, energy-aware, opportunistic routing protocol in a large-scale EH-WSN requiring multi-hop communication. In choosing the best forwarding partner, our scheme considers the energy available at sensor nodes, their distances from the FC and also the amount of data to be transmitted. Our protocol requires no prior knowledge of the network topology. We provide a mathematical analysis of our routing protocol to confirm the achieved numerical results. As our results show, the proposed protocol significantly increases data delivery as compared to the state-of-the-art technologies. We also introduce an EH-aware manner for distributing sensors in the environment such that all nodes have approximately equal transmission load independent of their locations, which significantly increases the data delivery ratio.

A Framework to Design the Computational Load Distribution of Wireless Sensor Networks in Power Consumption Constrained Environments.

In this paper, we present a work based on the computational load distribution among the homogeneous nodes and the Hub/Sink of Wireless Sensor Networks (WSNs). The main contribution of the paper is an early decision support framework helping WSN designers to take decisions about computational load distribution for those WSNs where power consumption is a key issue (when we refer to “framework” in this work, we are considering it as a support tool to make decisions where the executive judgment can be included along with the set of mathematical tools of the WSN designer; this work shows the need to include the load distribution as an integral component of the WSN system for making early decisions regarding energy consumption). The framework takes advantage of the idea that balancing sensors nodes and Hub/Sink computational load can lead to improved energy consumption for the whole or at least the battery-powered nodes of the WSN. The approach is not trivial and it takes into account related issues such as the required data distribution, nodes, and Hub/Sink connectivity and availability due to their connectivity features and duty-cycle. For a practical demonstration, the proposed framework is applied to an agriculture case study, a sector very relevant in our region. In this kind of rural context, distances, low costs due to vegetable selling prices and the lack of continuous power supplies may lead to viable or inviable sensing solutions for the farmers. The proposed framework systematize and facilitates WSN designers the required complex calculations taking into account the most relevant variables regarding power consumption, avoiding full/partial/prototype implementations, and measurements of different computational load distribution potential solutions for a specific WSN.

Security analysis and improvement of a mutual authentication and key agreement solution for wireless sensor networks using chaotic maps

AbstractA characteristic of wireless sensor networks (WSNs) different from traditional networks is that WSNs are vulnerable to various types of attacks because of their distinctive features, involving distributed and nomadic attribute, wireless transmission medium, and lack of centralized infrastructure of security protection. Recently, Kumari et al presented a mutual authentication and key agreement scheme for WSNs using chaotic maps. Unfortunately, we find that the scheme of Kumari et al cannot resist sensor node capture attack, session‐specific temporary information attack, sensor node impersonation attack, and man‐in‐the‐middle attack. To overcome the security weaknesses in the solution of Kumari et al, this paper introduces a secure and efficient mutual authentication and key agreement scheme for heterogeneous ad hoc WSNs in fully public channel. Consequently, compared with the solution of Kumari et al, while providing relatively higher level of security and more security features, the proposed solution remains a favorable performance on communication overhead, computation overhead, and storage overhead separately.