Configuration Of Wireless Sensor Networks Research Articles

Reliability Assessment of Wireless Sensor Networks by Strain-Based Region Analysis for Redundancy Estimation in Measurements on the Example of an Aircraft Wing Box.

Wireless sensor networks (WSNs) are attracting increasing research interest due to their ability to monitor large areas independently. Their reliability is a crucial issue, as it is influenced by hardware, data, and energy-related factors such as loading conditions, signal attenuation, and battery lifetime. Proper selection of sensor node positions is essential to maximise system reliability during the development of products equipped with WSNs. For this purpose, this paper presents an approach to estimate WSN system reliability during the development phase based on the analysis of measurements, using strain measurements in finite element (FE) models as an example. The approach involves dividing the part under consideration into regions with similar strains using a region growing algorithm (RGA). The WSN configuration is then analysed for reliability based on data paths and measurement redundancy resulting from the sensor positions in the identified measuring regions. This methodology was tested on an exemplary WSN configuration at an aircraft wing box under bending load and found to effectively estimate the hardware perspective on system reliability. Therefore, the methodology and algorithm show potential for optimising sensor node positions to achieve better reliability results.

Hybrid optimization approach for energy minimization in wireless sensor networks leveraging XGBoost and random forest

Wireless Sensor Networks (WSNs) have garnered significant attention from both the academic and industrial communities. However, the limited battery capacity of WSN nodes imposes a set of restrictions on energy dissipations, which has compelled researchers to seek ways to save and minimize energy consumption. This paper presents a hybrid optimization model to minimize energy dissipation in Wireless Sensor Networks (WSNs). Employing linear programming and a combination of XGBoost and Random Forest algorithms, it effectively predicts internode distances and network lifetime. The results demonstrate significant energy savings in WSN deployments, outperforming traditional methods. This approach contributes to the field by offering a practical, energy-efficient strategy for WSN configuration planning, highlighting the model’s applicability in real-world scenarios, where energy conservation is critical.

Control Message Quenching-Based Communication Protocol for Energy Management in SDWSN

The rise of the Internet of Things has facilitated the growth of Wireless Sensor Networks (WSNs). WSN has many challenges concerning network and management. It is discovered that Software-Defined Wireless Sensor Networks (SDWSNs) could simplify WSN configuration, routing, and management. However, for obtaining a thorough view of the underlying topology, SDWSN causes many control messages to be exchanged. This consequently depletes the energy of nodes. Wherefore, solving the energy challenges of SDWSN is imperative, before they could be successfully implemented. Realizing this, we propose an architecture that adopts the control message quenching technique in the data layer devices. Based on the proposed architecture, we propose a communication protocol, Control Message Quenching-based SDWSN (CMQ-SDWSN) that facilitates a minimal exchange of control messages between the infrastructure layer and the control layer by placing entry loggers in the data layer. Furthermore, we formulated an Integer Linear Programming (ILP) problem in the control layer which enables better partitioning and distribution of rules. The simulation results show that the proposed architecture and the communication protocol reduce the control message overhead by 33.66% on average and minimize the energy consumption of nodes by 33.51% on average when compared to its counterparts.

Energy‐aware versatile wireless sensor network configuration for structural health monitoring

Energy‐aware versatile wireless sensor network configuration for structural health monitoring

Piezoelectric Energy Harvester for IoT Sensor Devices

Limited battery power is a major challenge for wireless sensor network (WSN) in internet of things (IoT) applications, especially in hard-to-reach places that require periodic battery replacement. The energy harvesting application is intended as an alternative to maintain network lifetime by utilizing environmental energy. The proposed method utilized piezoelectricity to convert vibration or pressure energy into electrical energy through a modular piezoelectric energy harvesting design used to supply energy to sensor nodes in WSN. The module design consisted of several piezoelectric elements, of which each had a different character in generating energy. A bridge diode was connected to each element to reduce the feedback effect of other elements when pressure was exerted. The energy produced by the piezoelectric is an impulse so that the capacitor was used to quickly store the energy. The proposed module produced 7.436 μJ for each step and 297.4 μJ of total energy with pressure of a 45 kg load 40 times with specific experiments installed under each step. The energy could supply WSN nodes in IoT application with a simple energy harvesting system. This paper presents a procedure for measuring the energy harvested from a commonly available piezoelectric buzzer. The specific configurations of the piezoelectric and the experiment setups will be explained. Therefore, the output energy characteristics will be understood. In the end, the potentially harvested energy can be estimated. Therefore, the configuration of IoT WSN could be planned.

Wireless Sensor Network (WSN) Configuration Method to Increase Node Energy Efficiency through Clustering and Location Information

Wireless Sensor Network (WSN) technology, for services that are difficult to access or which need to be continuously monitored regardless of location, needs further research and development due to an expansion of fields where it can be applied and due to increases in efficiency. In particular, in the field of defense, research on the latest IT technologies including sensor networks is being actively conducted as an alternative to the risky use of personnel in areas such as surveillance and surveillance reconnaissance. This paper experimented with analyzing the conditions necessary for increasing the energy efficiency of the nodes constituting a sensor network using a clustering routing technique and a location-based routing technique. The derived factors include a method for selecting a cluster head (CH), a method for establishing a path from each channel to a base station (BS), and a method for transmitting collected data. We experimented with the derived factors and proposed a WSN configuration method that increases the energy efficiency of each node by applying optimal results and methods that were verified experimentally.

Virtual Network Embedding for Wireless Sensor Networks Time-Efficient QoS/QoI-Aware Approach

A recent trend in wireless sensor networks (WSNs) is network virtualization to support on-demand sharing of sensing functionality. The efficient allocation of WSN resources to sensing requests is obtained using virtual network embedding (VNE). This must take into account Quality of Service (e.g., reliability), Quality of Information (e.g., sensing accuracy), and deal with wireless interference. With increased computational complexity due to the added constraints, finding an optimal solution can be prohibitive at scale. We developed an offline embedding algorithm that searches through all possible embeddings, which allowed us to explore the tradeoff between solution quality and search time. We identify a defined set of initial processing steps that lead to high-quality solutions (within 10% of the best solution) in bounded time. We evaluated the algorithm under high stress (large networks with long paths, high data rates, beyond typical WSN configuration) to understand its limitations and the limitations imposed by the underlying WSN substrate.

Collaborative Beamforming in Wireless Sensor Networks Using a Novel Particle Swarm Optimization Algorithm Variant

Wireless Sensor Network (WSN) nodes inherently feature limited transmission range. A recent solution to the long range transmission problem is Collaborative Beamforming (CBF). The outcome of an ideal CBF process ought to be a radiation pattern whose main beam is oriented towards the intended transmission destination (WSN sink), inherently increasing the transmission range. Owing to the random and complex nature of WSNs, development and use of improved metaheuristic algorithms in CBF is of essence. This paper delves into the development and application of an improved Particle Swarm Optimization (PSO) algorithm in CBF from the perspective of a 3 dimension WSN configuration (wherein the sink is elevated from the nodes’ plane). The modifications done on the PSO algorithm entail use of fuzzy-adaptive confidence and inertia weight parameters alongside a particle culling procedure. The modified PSO algorithm has been christened Culled Fuzzy Adaptive Particle Swarm Optimization (CFAPSO) algorithm. Comparisons against use of a linearly-adaptive PSO algorithm variant, basic PSO algorithm and the Genetic Algorithm (GA) in CBF have established the superiority of the proposed CFAPSO algorithm. The CFAPSO algorithm is found to generate a beamsteering outcome statistically identical to that of conventional beamsteering. It is noteworthy that conventional beamsteering is inapplicable to beam-pattern optimization with respect to processes such as sidelobe minimization, nulling among others. The developed CFAPSO algorithm befits utilization in a plethora of CBF schemes.

Performance evaluation of LoRa LPWAN technology for IoT-based blast-induced ground vibration system

The recent proliferation of wireless sensor networks (WSNs) evolution into the Internet of Things (IoT) vision enables a variety of low-cost monitoring applications which allows a seamless transfer of information via embedded computing and network devices. Ambiguous ground vibration can be induced by blasting demolition is a severe concern which grievously damages the nearby dwellings and plants. It is an indispensable prerequisite for measuring the blast-induced ground vibration (BIGV), accomplishing a topical and most active research area. Thus, proposed and developed an architecture which emphasizes the IoT realm and implements a low-power wide-area networks (LPWANs) based system. Especially, using the available Long-Range (LoRa) Correct as Radio Frequency (RF) module, construct a WSN configuration for acquisition and streaming of required data from and to an IoT gateway. The system can wirelessly deliver the information to mine management and surrounding rural peoples to aware of the intensity of BIGV level. In this article, an endeavor has been made to introduce a LoRa WAN connectivity and proved the potentiality of the integrated WSN paradigm by testing of data transmission-reception in a non-line of sight (NLOS) condition. The path loss metrics and other required parameters have been measured using the LoRa WAN technology at 2.4 GHz frequency.

Hierarchical copula-based distributed detection

Abstract Detection is one of the main tasks of wireless sensor networks (WSN) in many applications. The data of network nodes are usually assumed to be statistically independent since considering dependence results in intractable decision rules. However, detection performance degrades when the correlation rises. In this paper, a practically popular configuration of WSNs is considered where homogeneous nodes - each of them consisting of several heterogeneous sensors - send their processed data to a fusion center (FC). Here, data fusion should be implemented in two levels: 1. Nodes fuse the data of their sensors. 2. The FC takes the final decision by fusing the data of the nodes. We propose to implement a copula-based local decision rule in nodes. At the FC, it is shown that the correlation among nodes’ decisions can be resolved by simply adding the logarithm of the sum of nodes’ decisions to the statistic of the FC. The proposed distributed detection scheme is evaluated in a practical example of fire detection. Simulations show that considering correlation by implementing the proposed methods would improve detection performance.

Flexible Configuration of Wireless Sensor Network for Monitoring of Rainfall-Induced Landslide

<p>Establishment of wireless sensor network for Monitoring and Early Warning System (MEWS) of rainfall-induced landslide is still a challenging task due to problems of energy consumption. This research aim is to propose a new flexible system for the configuration of MEWS for rainfall-induced landslides. The proposed system is an integration a star topology and a tree topology, in which, the star topology is automatically used for the sensor nodes around the gateway node, whereas the tree topology is adopted for the other nodes. Consequently, the proposed configuration method is flexible and capable to save the energy consumption in the MEWS. Experiment result showed that the performance of the MEWS with the proposed method Wireless Sensor Network is better than those from the systems only use the tree topology or the star topology. The result of this study is useful for designing WSN for MEWS of rainfall-induced landslides.</p>

Optimal wireless sensor network configuration for structural monitoring using automatic-learning firefly algorithm

Wireless sensor networks are becoming attractive data communication patterns in structural health monitoring systems. Designing and applying effective wireless sensor network–based structural health monitoring systems for large-scale civil infrastructure require a great number of wireless sensors and the optimal wireless sensor networks configuration becomes critical for such spatially separated large structures. In this article, optimal wireless sensor network configuration for structural health monitoring is treated as a discrete optimization problem, where parameter identification and network performance are simultaneously addressed. To solve this rather complicated optimization problem, a novel swarm intelligence algorithm called the automatic-learning firefly algorithm is proposed by integrating the original firefly algorithm with the Lévy flight and the automatic-learning mechanism. In the proposed algorithm, the Lévy flight is adopted to maximize the searching capability in unknown solution space and avoid premature convergence and the automatic-learning mechanism is designed to drive fireflies to move toward better locations at high speed. Numerical experiments are performed on a long-span bridge to demonstrate the effectiveness of the proposed automatic-learning firefly algorithm. Results indicate that automatic-learning firefly algorithm can find satisfactory wireless sensor network configurations, which facilitate easy discrimination of identified mode vectors and long wireless sensor network lifetime, and the innovations in automatic-learning firefly algorithm make it superior to the simple discrete firefly algorithm as to solution quality and convergence speed.

Integrated Evaluation of Reliability and Power Consumption of Wireless Sensor Networks.

Power consumption is a primary interest in Wireless Sensor Networks (WSNs), and a large number of strategies have been proposed to evaluate it. However, those approaches usually neither consider reliability issues nor the power consumption of applications executing in the network. A central concern is the lack of consolidated solutions that enable us to evaluate the power consumption of applications and the network stack also considering their reliabilities. To solve this problem, we introduce a fully automatic solution to design power consumption aware WSN applications and communication protocols. The solution presented in this paper comprises a methodology to evaluate the power consumption based on the integration of formal models, a set of power consumption and reliability models, a sensitivity analysis strategy to select WSN configurations and a toolbox named EDEN to fully support the proposed methodology. This solution allows accurately estimating the power consumption of WSN applications and the network stack in an automated way.

Software Defined Networking for Improved Wireless Sensor Network Management: A Survey.

Wireless sensor networks (WSNs) are becoming increasingly popular with the advent of the Internet of things (IoT). Various real-world applications of WSNs such as in smart grids, smart farming and smart health would require a potential deployment of thousands or maybe hundreds of thousands of sensor nodes/actuators. To ensure proper working order and network efficiency of such a network of sensor nodes, an effective WSN management system has to be integrated. However, the inherent challenges of WSNs such as sensor/actuator heterogeneity, application dependency and resource constraints have led to challenges in implementing effective traditional WSN management. This difficulty in management increases as the WSN becomes larger. Software Defined Networking (SDN) provides a promising solution in flexible management WSNs by allowing the separation of the control logic from the sensor nodes/actuators. The advantage with this SDN-based management in WSNs is that it enables centralized control of the entire WSN making it simpler to deploy network-wide management protocols and applications on demand. This paper highlights some of the recent work on traditional WSN management in brief and reviews SDN-based management techniques for WSNs in greater detail while drawing attention to the advantages that SDN brings to traditional WSN management. This paper also investigates open research challenges in coming up with mechanisms for flexible and easier SDN-based WSN configuration and management.

Application modeling for performance evaluation on event-triggered wireless sensor networks

This paper presents an approach for event-triggered wireless sensor network (WSN) application modeling, aiming to evaluate the performance of WSN configurations with regards to metrics that are meaningful to specific application domains and respective end-users. It combines application, environment-generated workload and computing/communication infrastructure within a high-level modeling simulation framework, and includes modeling primitives to represent different kind of events based on different probabilities distributions. Such primitives help end-users to characterize their application workload to capture realistic scenarios. This characterization allows the performance evaluation of specific WSN configurations, including dynamic management techniques as load balancing. Extensive experimental work shows that the proposed approach is effective in verifying whether a given WSN configuration can fulfill non-functional application requirements, such as identifying the application behavior that can lead a WSN to a break point after which it cannot further maintain these requirements. Furthermore, through these experiments, we discuss the impact of different distribution probabilities to model temporal and spatial aspects of the workload on WSNs performance, considering the adoption of dynamic and decentralized load balancing approaches.

Wireless Sensor Network to Monitoring an Ozone Sterilizer

The success of the ozone sterilization process depends on some variables: gas concentration, temperature and humidity. When these variables are monitored and stored remotely, the data redundancy and operational safety are increased. For this purpose, the use of wireless sensor networks is a technological alternative with benefits. This paper studies the implementation and analysis of data from a wireless sensor network configuration in monitoring the ozone sterilization process, where critical variables can be monitored and their records stored away. Additionally the Received Signal Strength Indication is checked to serve as the network performance indicator. The result showed that the wireless sensor network sensors not only improved the monitoring process as it allowed redundancy records, collaborating with process safety.

Cooperative Transmission for Security Enhancement in Clustered Wireless Sensor Networks

We study opportunistic decode-and-forward relaying transmission in cooperative cluster-based wireless sensor networks (WSNs) with secrecy constraints, where a passive eavesdropper may overhear the source message. To deal with this problem, we consider the novel opportunistic relay section cooperative transmission for the cluster configuration of WSNs. The system performance in terms of the secrecy outage probability and the probability of nonzero secrecy capacity are analyzed and the exact closed-form expressions are derived over Rayleigh fading channels. Furthermore, we derive the asymptotic secrecy outage probability which accurately reveals the secrecy diversity order. Finally, numerical results are presented to verify the theoretical analysis and depict that node cooperation has a great potential to enhance physical layer security against eavesdropping.

An adaptive neighbour detection scheme for rapid configuration of wireless sensor networks

The purpose of this paper is to represent an adaptive neighbour detection scheme for rapid sensor network configuration, especially in wireless sensor network WSN systems. In typical WSNs, the sensor nodes have no knowledge about the locations of other nodes and the connections between them after deployment. For the purpose of network configuration and future data transmission schedule assignments, neighbour detection process should be carried out, but this work are usually ignored in most communication protocol designs. In our real network establishment, it is proved that neighbour detection is critically important at the beginning configuration state of the entire network and when the topology is changed. Therefore, an adaptive neighbour detection scheme is introduced, which uses signalling packet broadcasting and the corresponding adaptive back-off mechanism to guarantee a high connectivity detection probability. The work is verified by simulation and testbed experiments, and has been used in practical large scale sensor networks.

Wireless Sensor Networks Configurations for Applications in Construction

The global wireless sensor networks market is forecasted to increase at a 14.4% annual growth rate through 2016 [1]. This emerging technology trend is fueled by recent availability of sensors that are smaller, cheaper, and more intelligent. Wireless sensor networks have many potential applications in construction management such as progress tracking, equipment management, surveillance, site safety and others. This paper focuses on designing and configuring wireless sensor networks hardware and software for selected construction applications. The framework is design based on application's objective using a rapid prototyping and iterative system refinement mechanism. The rapid prototyping allows early evaluation of the configured system behavior and performance. The proposed design incorporates a self-adaptive computing concept, which is able to self-control its internal functions and operations, while adapting to the continually changing job site environment. Five prototype designs are presented to support current practices of construction operations in outdoor and indoor environments. The paper articulates the designs objectives, system functionalities, hardware constraints and the performance measures. The developed hardware were tested in real time, and quickly adjusted until targeted performance measures were satisfied. The obtained results show the consistency of the developed prototypes with their experimental applications and their efficiency in comparison to traditional practices.

The Nonuniform Node Configuration of Wireless Sensor Networks for Long-Span Bridge Health Monitoring

This paper presents a nonuniform node configuration of wireless sensor networks (WSNs) for long-span bridge health monitoring. The methodology and strategy of two-phase node arrangement for nonuniform WSN configuration are firstly presented, and then numerical examples are carried out by a long-span suspension bridge. Three cases, which are four sensor nodes distributed on one side of the girder, ten sensor nodes distributed on one side of the girder, and eight sensor nodes distributed averagely on two sides of the girder, are employed. In case I and case II, three schemes that are the nonuniform node configuration arranged by the two-phase node arrangement method, the uniform nodes configuration, and the independent sensor nodes configuration are used for comparison. And in case III, two schemes that are nonuniform nodes configuration and the independent sensor nodes configuration are adopted. The results indicate that the nonuniform node configuration can balance energy consumption, eliminate “energy hole,” and maximize network performance effectively, which shows the most outstanding performance when compared with other conventional node configurations. So, the efficiency of the two-phase node arrangement method is validated.