The Deployment in the Wireless Sensor Networks: Methodologies, Recent Works and Applications

International audienceThe wireless sensor networks (WSN) is a research area in continuous evolution with a variety of application contexts. Wireless sensor networks pose many optimization problems, particularly because sensors have limited capacity in terms of energy, processing and memory. The deployment of sensor nodes is a critical phase that significantly affects the functioning and performance of the network. Often, the sensors constituting the network cannot be accurately positioned, and are scattered erratically. To compensate the randomness character of their placement, a large number of sensors is typically deployed, which also helps to increase the fault tolerance of the network. In this paper, we are interested in studying the positioning and placement of sensor nodes in a WSN. First, we introduce the problem of deployment and then we present the latest research works about the different proposed methods to solve this problem. Finally, we mention some similar issues related to the deployment and some of its interesting applications

Covering a 3D flat surface with autonomous and mobile wireless sensor nodes

International audienceWireless Sensor Networks (WSNs) are used in a wide range of applications due to their monitoring and tracking abilities. Depending on the applications goals, sensor nodes are deployed either in a two dimensional (2D) area or in a three-dimensional (3D) area. In addition, WSN deployment can be either in a distributed or a centralized manner. In this paper, we are interested in a fully distributed deployment of WSN in several 3D-flat-surface configurations using autonomous and mobile nodes. Our goal is to ensure full 3D flat surfaces coverage and maintain network connectivity for these surfaces. To reach our goal we propose 3D-DVFA-FSC, a distributed deployment algorithm based on virtual forces strategy to move sensor nodes over different 3D-flat-surface shapes. Simulation results show that 3D-DVFA-FSC provides a full coverage rate regardless of the 3D-flat-surface configuration while maintaining network connectivity

The use of computational geometry techniques to resolve the issues of coverage and connectivity in wireless sensor networks

Wireless Sensor Networks (WSNs) enhance the ability to sense and control the physical environment in various applications. The functionality of WSNs depends on various aspects like the localization of nodes, the strategies of node deployment, and a lifetime of nodes and routing techniques, etc. Coverage is an essential part of WSNs wherein the targeted area is covered by at least one node. Computational Geometry (CG) -based techniques significantly improve the coverage and connectivity of WSNs. This paper is a step towards employing some of the popular techniques in WSNs in a productive manner. Furthermore, this paper attempts to survey the existing research conducted using Computational Geometry-based methods in WSNs. In order to address coverage and connectivity issues in WSNs, the use of the Voronoi Diagram, Delaunay Triangulation, Voronoi Tessellation, and the Convex Hull have played a prominent role. Finally, the paper concludes by discussing various research challenges and proposed solutions using Computational Geometry-based techniques.Web of Science2218art. no. 700

Edge Computing for Internet of Things

The Internet-of-Things is becoming an established technology, with devices being deployed in homes, workplaces, and public areas at an increasingly rapid rate. IoT devices are the core technology of smart-homes, smart-cities, intelligent transport systems, and promise to optimise travel, reduce energy usage and improve quality of life. With the IoT prevalence, the problem of how to manage the vast volumes of data, wide variety and type of data generated, and erratic generation patterns is becoming increasingly clear and challenging. This Special Issue focuses on solving this problem through the use of edge computing. Edge computing offers a solution to managing IoT data through the processing of IoT data close to the location where the data is being generated. Edge computing allows computation to be performed locally, thus reducing the volume of data that needs to be transmitted to remote data centres and Cloud storage. It also allows decisions to be made locally without having to wait for Cloud servers to respond

Mobile Search Strategies and Detection Analysis of Nuclear Radiation Sources

This work focuses on detection analysis and search strategies for nuclear radiation sources in metropolitan areas with mobile sensor networks. A mobile sensor detecting a stationary nuclear source experiences continually changing statistics. In this work we provide an analysis of the probability of detection of a nuclear source that incorporates these continual changes. We apply the analysis technique to several patterns of motion including linear and circular paths. Analysis is also presented for cases in which there is a significant vertical offset between source and mobile sensor (the three-dimensional problem). The resulting expressions are computationally simple to evaluate and have application to both analysis and simulation of nuclear detection systems in a variety of scenarios. In metropolitan areas, with vehicles equipped with detectors and Global Position System (GPS) devices, we consider the design of a robust detection system to provide consistent surveillance. Various strategies for providing this surveillance with a mobile sensor network are considered and the results are compared. Both time-from-last-visit based algorithms and detection algorithms that utilize both time and probability-of-miss estimates are considered. The algorithms are shown to perform well in a variety of scenarios, and it is further shown that the algorithms that utilize probability information outperform those that do not

Wireless Sensor Networks for Building Robotic Paths - A Survey of Problems and Restrictions

The conjugation of small nodes with sensing, communication and processing capabilities allows for the creation of wireless sensor networks (WSNs). These networks can be deployed to measure a very wide range of environmental phenomena and send data from remote locations back to users. They offer new and exciting possibilities for applications and research. This paper presents the background of WSNs by firstly exploring the different fields applications, with examples for each of these fields, then the challenges faced by these networks in areas such as energy-efficiency, node localization, node deployment, limited storage and routing. It aims at explaining each issue and giving solutions that have been proposed in the research literature. Finally, the paper proposes a practical scenario of deploying a WSN by autonomous robot path construction. The requirements for such a scenario and the open issues that can be tackled by it are exposed, namely the issues of associated with measuring RSSI, the degree of autonomy of the robot and connectivity restoration.The authors would like to acknowledge the company Inspiring Sci, Lda for the interest and valuable contribution to the successful development of this work.info:eu-repo/semantics/publishedVersio

Distributed navigation of multi-robot systems for sensing coverage

A team of coordinating mobile robots equipped with operation specific sensors can perform different coverage tasks. If the required number of robots in the team is very large then a centralized control system becomes a complex strategy. There are also some areas where centralized communication turns into an issue. So, a team of mobile robots for coverage tasks should have the ability of decentralized or distributed decision making. This thesis investigates decentralized control of mobile robots specifically for coverage problems. A decentralized control strategy is ideally based on local information and it can offer flexibility in case there is an increment or decrement in the number of mobile robots. We perform a broad survey of the existing literature for coverage control problems. There are different approaches associated with decentralized control strategy for coverage control problems. We perform a comparative review of these approaches and use the approach based on simple local coordination rules. These locally computed nearest neighbour rules are used to develop decentralized control algorithms for coverage control problems. We investigate this extensively used nearest neighbour rule-based approach for developing coverage control algorithms. In this approach, a mobile robot gives an equal importance to every neighbour robot coming under its communication range. We develop our control approach by making some of the mobile robots playing a more influential role than other members of the team. We develop the control algorithm based on nearest neighbour rules with weighted average functions. The approach based on this control strategy becomes efficient in terms of achieving a consensus on control inputs, say heading angle, velocity, etc. The decentralized control of mobile robots can also exhibit a cyclic behaviour under some physical constraints like a quantized orientation of the mobile robot. We further investigate the cyclic behaviour appearing due to the quantized control of mobile robots under some conditions. Our nearest neighbour rule-based approach offers a biased strategy in case of cyclic behaviour appearing in the team of mobile robots. We consider a clustering technique inside the team of mobile robots. Our decentralized control strategy calculates the similarity measure among the neighbours of a mobile robot. The team of mobile robots with the similarity measure based approach becomes efficient in achieving a fast consensus like on heading angle or velocity. We perform a rigorous mathematical analysis of our developed approach. We also develop a condition based on relaxed criteria for achieving consensus on velocity or heading angle of the mobile robots. Our validation approach is based on mathematical arguments and extensive computer simulations

Large Geographical Area Aerial Surveillance Systems Data Network Infrastructure Managed by Artificial Intelligence and Certified Over Blockchain: a Review

This paper proposes an aerial data network infrastructure for large geographical area surveillance systems. The work presents a review of previous works from the authors, existing technologies in the market and other scientific work, with the goal of creating a data network supported by Autonomous Tethered Aerostat Airships used for sensor fixing, drones deployment base and meshed data network nodes installation. The proposed approach for data network infrastructure supports several independent and heterogeneous services from independent, private and public companies. The presented solution employs Edge Artificial Intelligence (AI) systems for autonomous infrastructure management. The Edge AI used in the presented solution enables the AI management solution to work without the need of a permanent connection to cloud services and is constantly feed by the locally generated sensor data. These systems interact with other network AI services to accomplish coordinated tasks. Blockchain technology services are deployed to ensure secure and auditable decisions and operations, validated by the different involved ledgers