Mesh Sensor Network Research Articles

Stability Analysis through a Stability Factor Metric for IQRF Mesh Sensor Networks Utilizing Merged Data Collection.

This paper introduces a novel stability metric specifically developed for IQRF wireless mesh sensor networks, emphasizing flooding routing and data collection methodologies, particularly IQRF's Fast Response Command (FRC) technique. A key feature of this metric is its ability to ensure network resilience against disruptions by effectively utilizing redundant paths in the network. This makes the metric an indispensable tool for field engineers in both the design and deployment of wireless sensor networks. Our findings provide valuable insights, demonstrating the metric's efficacy in achieving robust and reliable network operations, especially in data collection tasks. The inclusion of redundant paths as a factor in the stability metric significantly enhances its practicality and relevance. Furthermore, this research offers practical ideas for enhancing the design and management of wireless mesh sensor networks. The stability metric uniquely assesses the resilience of data collection activities within these networks, with a focus on the benefits of redundant paths, underscoring the significance of stability in network evaluation.

Ad Hoc Mesh Network Localization Using Ultra-Wideband for Mobile Robotics.

This article explores the implementation of high-accuracy GPS-denied ad hoc localization. Little research exists on ad hoc ultra-wideband-enabled localization systems with mobile and stationary nodes. This work aims to demonstrate the localization of bicycle-modeled robots in a non-static environment through a mesh network of mobile, stationary robots, and ultra-wideband sensors. The non-static environment adds a layer of complexity when actors can enter and exit the node's field of view. The method starts with an initial localization step where each unmanned ground vehicle (UGV) uses the surrounding, available anchors to derive an initial local or, if possible, global position estimate. The initial localization uses a simplified implementation of the iterative multi-iteration ad hoc localization system (AHLos). This estimate was refined using an unscented Kalman filter (UKF) following a constant turn rate and velocity magnitude model (CTRV). The UKF then fuses the robot's odometry and the range measurements from the Decawave ultra-wideband receivers stationed on the network nodes. Through this position estimation stage, the robot broadcasts its estimated position to its neighbors to help the others further improve their localization estimates and localize themselves. This wave-like cycle of nodes helping to localize each other allows the network to act as a mobile ad hoc localization network.

Performance Assessment of a Wireless Mesh Network for Post-harvest Food Quality Traceability of Fruit Products: A Case Study

This paper presents the performance evaluation of a wireless sensor mesh network, for monitoring temperature and humidity in horticultural products when transported in truck galleys. For this purpose a software solution was proposed using ESP8266 devices powered by batteries. The mesh network was managed by the painlessMesh library. The proposed solution aims to minimize the energy consumption of the sensor nodes. The validation of the solution was performed in an area simulating a galley of a truck, where five sensor nodes and a root node were distributed. The tests were developed considering four different models involving variations in messages delivery confirmation, number of attempts until successful delivery and duty cycle duration of the nodes. The performance evaluation of the solution aimed to determine, connectivity rate, sending rate after connection and delivery rates of the first and second attempts. The results obtained show that the message delivery confirmation does not bring added value to the solution, contributing only to increase energy consumption. The use of synchronous duty cycles also showed worse results than the asynchronous use. These results allow the creation of a knowledge base for the use of this solution in a real context.

Microservice architecture for a remote management platform for pastured poultry farming using Amazon Web Services and wireless mesh sensor networks

Introduction: A variety of innovative solutions known as Precision Livestock Farming (PLF) technologies have been developed for the management of animal production industries, including Wireless Sensor Networks (WSN) for poultry farming.
 Problem: Current WSN-based systems for poultry farming lack the design of robust but flexible software architectures that ensure the integrity and proper delivery of data.
 Objective: Designing a microservice-based software architecture (MSA) for a multiplatform remote environmental management system based on Wireless Mesh Sensor Networks (WMSN) to be deployed in pastured poultry farming spaces.
 Methodology: A review about MSAs designed for animal farming was conducted, to synthesize key factors considered for the design process of the system data flow, microservice definition and the environmental monitoring system technology selection.
 Results: A cloud MSA with a multi layered scheme using the Amazon Web Services (AWS) platform was developed, validating the persistence of environmental data transmitted from WMSN prototype nodes to be deployed in mobile chicken coops.
 Conclusion: Defining an End-to-End data flow facilitates the organization of tasks by domains, allowing efficient event communication between components and network reliability both at the hardware and software levels.
 Originality: This study presents a novel design for a remote environmental monitoring system based on WMSN for mobile coops used in pastured poultry and a multi layered MSA cloud management platform for this specific type of food production industry.
 Limitations: Software architecture technology selection was based only on services offered, to the date of the study, in the free tier of the Amazon Web Service platform.

An Efficient Wireless Sensor Network Based on the ESP-MESH Protocol for Indoor and Outdoor Air Quality Monitoring

The main aim of this work is to establish a sensor MESH network using an ESP-MESH networking protocol with the ESP32 MCU (a Wi-Fi-enabled microcontroller) for indoor and outdoor air quality monitoring in real time. Each sensor node is deployed at a different location on the college campus and includes sensor arrays (CO2, CO, and air quality) interfaced with the ESP32. The ESP-MESH networking protocol is a low-cost, easy-to-implement, medium-range, and low-power option. ESP32 microcontrollers are inexpensive and are used to establish the ESP-MESH network that allows numerous sensor nodes spread over a large physical area to be interconnected under the same wireless network to monitor air quality parameters accurately. The data of different air quality parameters (temperature, humidity, PM2.5, gas concentrations, etc.) is taken (every 2 min) from the indoor and outdoor nodes and continuously monitored for 72 min. A custom time-division multiple-access (TDMA) scheduling scheme for energy efficiency is applied to construct an appropriate transmission schedule that reduces the end-to-end transmission time from the sensor nodes to the router. The performance of the MESH network is estimated in terms of the package loss rate (PLR), package fault rate (PFR), and rate of packet delivery (RPD). The value of the RPD is more than 97%, and the value of the PMR and PER for each active node is less than 1.8%, which is under the limit. The results show that the ESP-MESH network protocol offers a considerably good quality of service, mainly for medium-area networks.

Based on mesh sensor network: design and implementation of security monitoring system with Bluetooth technology

One of the most <span>critical aspects to consider in wireless sensor networks is security, particularly in internet of things (IoT) implementations. Sensor network applications had risen in the past 5 years since these networks have been used in various parts of life (smart residential and commercial buildings, medical, and agriculture). In this study, we provide a novel network of sensors based on the Bluetooth network that may be used to protect commercial buildings. The Bluetooth type HC 06 was chosen since it has a low energy consumption and a communication range of 100 meters. Such security network includes motion sensors and control cameras that are controlled by an Arduino Nano microcontroller. The motion sensor's primary characteristics are solely applicable to humans, and the Arduino Nano is an open-source microcontroller. The key benefit of this research is that it demonstrates how to create a low-cost Bluetooth sensor security network with limited storage space for control movies.</span>

Battery lifespan enhancement strategies for edge computing-enabled wireless Bluetooth mesh sensor network for structural health monitoring

Wireless sensor networks (WSN) offer an automated, convenient, and low-cost option for building IoT networks for monitoring the structural health of complex infrastructures. The limited bandwidth of a typical WSN is not favorable for intensive data transfer. Therefore, utilizing edge computing that allows raw data to be processed and compressed at IoT devices enables efficient data transfer to the central terminal for data storage and further analytics. However, edge computing requires an additional microcontroller unit (MCU), which significantly increases the edge device power consumption and thus reduces the device's battery lifespan. In this paper, three strategies are developed for saving the battery power of sensor devices with edge computing: (1) managing the connectivity settings of the wireless protocol settings, (2) managing the operations of the edge computing chip, and (3) adding battery capacity with parallel connections. The first strategy focuses on fine-tuning the trade-off between the WSN data throughput and power consumption. The second strategy develops two modes for power saving in certain computationally relaxing periods: Shutdown mode and Low-power mode. The Shutdown mode suspends the operations of the edge computing chip, allowing the edge computing chip to run for a limited time per day. The Low-power mode allows continuous operation of the edge computing chop at low clock speed, which consumes less current. The third strategy doubles the device lifespan by doubling the battery charge capacity using parallel connections. Combining all three strategies significantly enhances the sensor battery lifespan from three weeks to at least six months, notably reducing the frequency of on-site hardware maintenance while providing smooth data transfer due to edge computing.

Local Trust in Internet of Things Based on Contract Theory.

Autonomous trust mechanisms enable Internet of Things (IoT) devices to function cooperatively in a wide range of ecosystems, from vehicle-to-vehicle communications to mesh sensor networks. A common property desired in such networks is a mechanism to construct a secure, authenticated channel between any two participating nodes to share sensitive information, nominally a challenging proposition for a large, heterogeneous network where node participation is constantly in flux. This work explores a contract-theoretic framework that exploits the principles of network economics to crowd-source trust between two arbitrary nodes based on the efforts of their neighbors. Each node in the network possesses a trust score, which is updated based on useful effort contributed to the authentication step. The scheme functions autonomously on locally adjacent nodes and is proven to converge onto an optimal solution based on the available nodes and their trust scores. Core building blocks include the use of Stochastic Learning Automata to select the participating nodes based on network and social metrics, and the formulation of a Bayesian trust belief distribution from the past behavior of the selected nodes. An effort-reward model incentivizes selected nodes to accurately report their trust scores and contribute their effort to the authentication process. Detailed numerical results obtained via simulation highlight the proposed framework’s efficacy and performance. The performance achieved near-optimal results despite incomplete information regarding the IoT nodes’ trust scores and the presence of malicious or misbehaving nodes. Comparison metrics demonstrate that the proposed approach maximized the overall social welfare and achieved better performance compared to the state of the art in the domain.

A cloud-assisted mesh sensor network solution for public zone air pollution real-time data acquisition

A cloud-assisted mesh sensor network solution for public zone air pollution real-time data acquisition

Wireless Sensor Network as a Mesh: Vision and Challenges

Nowadays, network technologies are developing very rapidly. The growing volume of transmitted information (video, data, VoIP, etc.), the physical growth of networks, and inter-network traffic are forcing manufacturers to produce more powerful and “smart” devices that use new methods of transferring and sorting data. Such connected smart devices (IoT) are used in intelligently controlled traffic for self-driving vehicles in Vehicle Adhoc Networks (VANET), in electricity and water in smart cities, and in-home automation in smart homes. These types of connected Internet of Things (IoT) devices are used to leverage different types of network structures. Such IoT sensor devices can be deployed as a wireless sensor network (WSN) in a mesh topology. Both WSNs and Wireless Mesh Networks (WMNs) are easy to organize as well as to deploy. In this case, there are many reasons for combining these different types of networks. In particular, the detailed sensory capabilities of sensor networks may be improved by increasing bandwidth, reliability and power consumption in the mesh topology. However, there are currently only a handful of studies devoting to integrate these two different types of networks. In addition, there is no systematic review of existing interconnection methods. That is why in this article we explore the existing methods of these two networks and provide an analytical basis for their relationship. We introduce the definition of WSN and WMN and then look at some case studies. Afterward, we present several challenges and opportunities in the area of combined Wireless Mesh Sensor Network (WMSN) followed by a discussion on this interconnection through literature review and hope that this document will attract the attention of the community and inspire further research in this direction.

Secure Routing Algorithm in Wireless Mesh Network

In the today’s’ era of communication technology disaster management plays important role in life saving. Regardless of men made disasters or natural disasters proper communication network can be used to exchange information. In natural calamities wireless sensor mesh network proved to be as good option for communication. Low-altitude Unmanned Aerial Vehicles (UAVs) which is associated with WLAN Mesh Networks (WMNs) can be used in disaster management areas. The advantage of it is it can be installed on demand and it can use for efficient exploration of sized areas. The WMN is consisting of different components such as mesh clients, mesh routers and base station. It is more prone to have attacks of different types such as Denial of Service attack, black hole, gray hole , reply attack, Sybil attack etc. The most important attack which can damage whole working of WMN is routing attack. IEEE 802.11i is used as standard protocol for security in WLAN and IEEE 802.11s is used as secure algorithm for communication in WLAN mesh network. But both of them fail to address issue of routing problem in WLAN mesh network. The primary purpose of this paper is to outline routing algorithm and to design assured routing protocol. In this paper we have proposed improved secure Position-Aware, Secure, and Efficient mesh Routing approach (S-PASER). The proposed mechanisms have obviated more attack than regular IEEE 802.11s/i security mechanism and well known, secure routing protocol. The proposed methodology can be implemented on omnet++ simulator. The simulation results proved to be have better performance and throughput than existing algorithm.

Random Neural Networks with Hierarchical Committees for Improved Routing in Wireless Mesh Networks with Interference

We propose a hierarchical (nested) variant of a recurrent random neural network (RNN) with reinforced learning, introduced by Gelenbe. Each neuron (committee) in a top-level RNN represents a different bottom-level RNN (or sub-committee). The bottom-level RNNs choose the best routing and the top-level RNN chooses the currently best bottom-level RNN. Each of the bottom RNNs is trained in a different way. When they differ in their choice of the best path, several cognitive packets are routed according to the different decisions. In that case, a respective ACK packet trains individual bottom RNNs and not all bottom RNNs at once. An example presents an optimisation of a real-time routing in a dense mesh network of wireless sensors relaying small metering messages between each other, until the messages reach a common gateway. The network is experiencing a periodic electromagnetic interference. The hierarchical variant causes a small increase in the number of smart packets but allows a considerably better routing quality.

An improved cooperative team spraying control of a diffusion process with a moving or static pollution source

This paper is concerned with a control problem of a diffusion process with the help of static mesh sensor networks in a certain region of interest and a team of networked mobile actuators carrying chemical neutralizers. The major contribution of this paper can be divided into three parts: the first is the construction of a cyber-physical system framework based on centroidal Voronoi tessellations &#x0028 CVTs &#x0029 , the second is the convergence analysis of the actuators location, and the last is a novel proportional integral &#x0028 PI &#x0029 control method for actuator motion planning and neutralizing control &#x0028 e.g., spraying &#x0029 of a diffusion process with a moving or static pollution source, which is more effective than a proportional &#x0028 P &#x0029 control method. An optimal spraying control cost function is constructed. Then, the minimization problem of the spraying amount is addressed. Moreover, a new CVT algorithm based on the novel PI control method, henceforth called PI-CVT algorithm, is introduced together with the convergence analysis of the actuators location via a PI control law. Finally, a modified simulation platform called diffusion-mobile-actuators-sensors-2-dimension-proportional integral derivative &#x0028 Diff-MAS2D-PID &#x0029 is illustrated. In addition, a numerical simulation example for the diffusion process is presented to verify the effectiveness of our proposed controllers.

Coordination of nonholonomic mobile robots for diffusive threat defense

This paper studies coordination of a team of nonholonomic mobile robots with smart actuators for defending against invasive threat to a planar convex area. The threat refers to a kind of harmful substance such as chemical pollutant appearing outside and moving towards the area. The invasion of threat can be modeled by a 2D unsteady reaction-diffusion process. To reflect the adverse effect of threat on the area, a so-called risk intensity field is introduced. The value of risk intensity is equal to the concentration of threat measured by a static mesh sensor network. Based on this risk intensity field, a coordination control scenario using Voronoi tessellation is formulated. In order to minimize the actuator performance loss and reduce the total average risk intensity simultaneously, a generalized centroidal Voronoi tessellation (CVT) algorithm including optimal motion control and risk mitigation control is designed. The proposed algorithm is gradient-based and guides mobile robots to track their optimal trajectories asymptotically. Meanwhile, two conditions of choosing control gains are derived to keep the total average risk intensity below a safety level. Several simulation examples with different cases of threat invasion are provided and the advantage of proposed algorithm over traditional control method is presented.

Design and Implementation of an Internet-of-Things Roadside Parking System Based on Raspberry Pi 3 and Bluetooth Low Energy Mesh Sensor Network

Design and Implementation of an Internet-of-Things Roadside Parking System Based on Raspberry Pi 3 and Bluetooth Low Energy Mesh Sensor Network

Distributed coordination of multiple mobile actuators for pollution neutralization

Abstract This paper is concerned with distributed coordination of multiple mobile actuators for pollution neutralization in a polluted environment, where a static mesh sensor network is pre-deployed for measuring the concentration of contaminants, and mobile actuators with neutralizing chemicals implement spraying operation at a steady rate to reduce the contaminants continuously. A hazard intensity distribution is introduced to evaluate adverse impact of contaminants on the environment. Autonomous actuators are dynamically deployed to minimize the total hazard intensity. This coordination problem can be formulated as a distributed deployment problem based on centroidal Voronoi tessellation (CVT). Two control strategies with switching motion controllers are proposed to achieve optimal deployment of mobile actuators for unlimited and limited actuating range respectively. To escape local minimum and balance the actuator workload, a novel workload adjustment strategy is designed to change the normalized amount of neutralizer sprayed by mobile actuators, which makes each actuator approach a common workload. Compared with pure CVT and switching motion controller, the total hazard intensity can be further decreased if the workload adjustment strategy is implemented. Simulation examples are provided to validate the effectiveness of the proposed method.

Green Survivable Collaborative Edge Computing in Smart Cities

As an integrated environment deployed with wired and wireless infrastructures, the smart city heavily relies on the wireless-optical broadband access network. The information flows captured by indoor devices are sent to optical network units through front-end wireless mesh sensor networks (WMNs) and, finally, reach the optical line terminal for industrial/commercial decision making via the passive optical network backhaul. To reduce the backhaul bandwidth saturated by this conventional approach, edge devices are deployed at the front-end WMN to preprocess information flows. Based on collaborative edge computing, home users or factory workers customize their computing services as virtual networks embedded onto the common WMN. In this paper, we propose the green survivable virtual network embedding for the collaborative edge computing in smart cities. We mathematically formulate the problem and derive the corresponding bound. Extensive simulations with real traces demonstrate the algorithm effectiveness.

Graph Signal Processing in a Nutshell

The framework of graph signal processing was conceived in the last decade with the ambition of generalizing the tools from classical digital signal processing to the case in which the signal is defined over an irregular structure modelled by a graph. Instead of discrete time - what one would call a regular 1-D domain, in which a signal sample is adjacent to only two neighbors and for any pair of contiguous samples the distance is the same - the signals here are defined over graphs and, therefore, the distance and relations between adjacent samples vary along the signal. For instance, one may consider the temperature signal defined from the data of a sensor mesh network. When creating the tools in such a scenario, many challenges arise even with basic concepts of the classical theory. In this paper, the core ideas of graph signal processing are presented, focusing on the two main frameworks developed along the years, and a couple of examples and applications are shown. We conclude drawing attention to a few of the many open opportunities for further studies in the field.

Robust Wireless Communication for Small Exploration Rovers Equipped with Multiple Antennas by Estimating Attitudes of Rovers in Several Experimental Environments

We are developing a robotic system for an asteroid surface exploration. The system consists ofmultiplesmall size rovers, that communicate with each other over a wireless network. Since the rovers configure over a wireless mesh sensor network on an asteroid, it is possible to explore a large area on the asteroid effectively. The rovers will be equipped with a hopping mechanism for transportation, which is suitable for exploration in a micro-gravity environment like a small asteroid’s surface. However, it is difficult to control the rover’s attitude during the landing. Therefore, a cube-shaped rover was designed. As every face has two antennas respectively, the rover has a total of twelve antennas. Furthermore, as the body shape and the antenna arrangements are symmetric, irrespective of the face on top, a reliable communication state among the rovers can be established by selecting the proper antennas on the top face. Therefore, it is important to estimate which face of the rover is on top. This paper presents an attitude estimation method based on the received signal strength indicators (RSSIs) obtained when the twelve antennas communicate among each other. Since the RSSI values change depending on an attitude of the rover and the surrounding environment, a significantly large number of RSSIs were collected as a training data set in different kinds of environments similar to an asteroid; consequently, a classifier for estimating the rover attitude was trained from the data set. A few of the experimental results establish the validity and effectiveness of the proposed exploration system and attitude estimation method.

Practical and self-configurable multihop wireless infrastructure: a functional perspective

Multihop wireless networks require self-configurable and reliable communication infrastructure that can quickly adapt itself to the rapidly changing network conditions without manual reconfiguration. The key to developing such a communication infrastructure requires (i) efficient link estimation mechanisms, (ii) reliable routing algorithms, and (iii) stable addressing schemes. In the past decade, a number of practical solutions have been developed for these three main components of multihop wireless infrastructure in inherently similar mesh networks, sensor networks, and MANETs. However, we lack a comprehensive review that classifies these solutions and compares them on the basis of a set of properties desired in wireless networks. In this review, we classify different techniques implemented and evaluated by the research community, define a set of properties, and functionally compare representative techniques from each class.