A Review on Sensor Node Placement Techniques in Wireless Sensor Networks

One way to provide Wireless Sensor Network (WSN) with maximum coverage, maximum connectivity, minimum deployment cost and minimum energy consumption is through an effective planning mechanism in arranging an optimum number of sensor nodes. Proper planning will provide a cost-effective deployment by having optimal placements for the sensor nodes. Sensor node placement schemes are needed to accommodate the balance of coverage and energy consumption since closer sensor nodes not only reduces the energy consumption but will result in the network coverage becoming smaller. This paper critically reviews the research and development work done in sensor node placement. Based on the review, the design objectives that need to be considered are identified. Most of the work reviewed focused on two or three design objectives

Utilization Of A Large-Scale Wireless Sensor Network For Intrusion Detection And Border Surveillance

To control the border more effectively, countries may deploy a detection system that enables real-time surveillance of border integrity. Events such as border crossings need to be monitored in real time so that any border entries can be noted by border security forces and destinations marked for apprehension. Wireless Sensor Networks (WSNs) are promising for border security surveillance because they enable enforcement teams to monitor events in the physical environment. In this work, probabilistic models have been presented to investigate senor development schemes while considering the environmental factors that affect the sensor performance. Simulation studies have been carried out using the OPNET to verify the theoretical analysis and to find an optimal node deployment scheme that is robust and efficient by incorporating geographical coordination in the design. Measures such as adding camera and range-extended antenna to each node have been investigated to improve the system performance. A prototype WSN based surveillance system has been developed to verify the proposed approach

Advances in analytical models and applications for RFID, WSN and AmI systems

Experimentos llevados a cabo con el equipo de división de honor UCAM Volleyball Murcia.[SPA] Internet de las cosas (IoT) integra distintos elementos que actúan tanto como fuentes, como sumideros de información, a diferencia de la percepción que se ha tenido hasta ahora de Internet, centrado en las personas. Los avances en IoT engloban un amplio número de áreas y tecnologías, desde la adquisición de información hasta el desarrollo de nuevos protocolos y aplicaciones. Un concepto clave que subyace en el concepto de IoT, es el procesamiento de forma inteligente y autónoma de los flujos de información que se dispone. En este trabajo, estudiamos tres aspectos diferentes de IoT. En primer lugar, nos centraremos en la infraestructura de obtención de datos. Entre las diferentes tecnologías de obtención de datos disponibles en los sistemas IoT, la Identificación por Radio Frecuencia (RFID) es considerada como una de las tecnologías predominantes. RFID es la tecnología detrás de aplicaciones tales como control de acceso, seguimiento y rastreo de contenedores, gestión de archivos, clasificación de equipaje o localización de equipos. Con el auge de la tecnología RFID, muchas instalaciones empiezan a requerir la presencia de múltiples lectores RFID que operan próximos entre sí y conjuntamente. A estos escenarios se les conoce como dense reader environments (DREs). La coexistencia de varios lectores operando simultáneamente puede causar graves problemas de interferencias en el proceso de identificación. Uno de los aspectos claves a resolver en los RFID DREs consiste en lograr la coordinación entre los lectores. Estos problemas de coordinación son tratados en detalle en esta tesis doctoral. Además, dentro del área de obtención de datos relativa a IoT, las Redes de Sensores Inalámbricas (WSNs) desempeñan un papel fundamental. Durante la última década, las WSNs han sido estudiadas ampliamente de forma teórica, y la mayoría de problemas relacionados con la comunicación en este tipo de redes se han conseguido resolver de forma favorable. Sin embargo, con la implementación de WSNs en proyectos reales, han surgido nuevos problemas, siendo uno de ellos el desarrollo de estrategias realistas para desplegar las WSN. En este trabajo se estudian diferentes métodos que resuelven este problema, centrándonos en distintos criterios de optimización, y analizando las diferentes ventajas e inconvenientes que se producen al buscar una solución equilibrada. Por último, la Inteligencia Ambiental (AmI) forma parte del desarrollo de aplicaciones inteligentes en IoT. Hasta ahora, han sido las personas quienes han tenido que adaptarse al entorno, en cambio, AmI persigue crear entornos de obtención de datos capaces de anticipar y apoyar las acciones de las personas. AmI se está introduciendo progresivamente en diversos entornos reales tales como el sector de la educación y la salud, en viviendas, etc. En esta tesis se introduce un sistema AmI orientado al deporte que busca mejorar el entrenamiento de los atletas, siendo el objetivo prioritario el desarrollo de un asistente capaz de proporcionar órdenes de entrenamiento, basadas tanto en el entorno como en el rendimiento de los atletas. [ENG] Internet of Things (IoT) is being built upon many different elements acting as sources and sinks of information, rather than the previous human-centric Internet conception. Developments in IoT include a vast set of fields ranging from data sensing, to development of new protocols and applications. Indeed, a key concept underlying in the conception of IoT is the smart and autonomous processing of the new huge data flows available. In this work, we aim to study three different aspects within IoT. First, we will focus on the sensing infrastructure. Among the different kind of sensing technologies available to IoT systems, Radio Frequency Identification (RFID) is widely considered one of the leading technologies. RFID is the enabling technology behind applications such as access control, tracking and tracing of containers, file management, baggage sorting or equipment location. With the grow up of RFID, many facilities require multiple RFID readers usually operating close to each other. These are known as Dense Reader Environments (DREs). The co-existence of several readers operating concurrently is known to cause severe interferences on the identification process. One of the key aspects to solve in RFID DREs is achieving proper coordination among readers. This is the focus of the first part of this doctoral thesis. Unlike previous works based on heuristics, we address this problem through an optimization-based approach. The goal is identifying the maximum mean number of tags while network constraints are met. To be able to formulate these optimization problems, we have obtained analytically the mean number of identifications in a bounded -discrete or continuous- time period, an additional novel contribution of our work. Results show that our approach is overwhelmingly better than previous known methods. Along sensing technologies of IoT, Wireless Sensor Networks (WSNs) plays a fundamental role. WSNs have been largely and theoretically studied in the past decade, and many of their initial problems related to communication aspects have been successfully solved. However, with the adoption of WSNs in real-life projects, new issues have arisen, being one of them the development of realistic strategies to deploy WSNs. We have studied different ways of solving this aspect by focusing on different optimality criteria and evaluating the different trade-offs that occur when a balanced solution must be selected. On the one hand, deterministic placements subject to conflicting goals have been addressed. Results can be obtained in the form of Pareto-frontiers, allowing proper solution selection. On the other hand, a number of situations correspond to deployments were the nodes¿ position is inherently random. We have analyzed these situations leading first to a theoretical model, which later has been particularized to a Moon WSN survey. Our work is the first considering a full model with realistic properties such as 3D topography, propellant consumptions or network lifetime and mass limitations. Furthermore, development of smart applications within IoT is the focus of the Ambient Intelligence (AmI) field. Rather than having people adapting to the surrounding environment, AmI pursues the development of sensitive environments able to anticipate support in people¿s actions. AmI is progressively being introduced in many real-life environments like education, homes, health and so forth. In this thesis we develop a sport-oriented AmI system designed to improve athletes training. The goal is developing an assistant able to provide real-time training orders based on both environment and athletes¿ biometry, which is aimed to control the aerobic and the technical-tactical training. Validation experiments with the honor league UCAM Volleyball Murcia team have shown the suitability of this approach.[ENG] Internet of Things (IoT) is being built upon many different elements acting as sources and sinks of information, rather than the previous human-centric Internet conception. Developments in IoT include a vast set of fields ranging from data sensing, to development of new protocols and applications. Indeed, a key concept underlying in the conception of IoT is the smart and autonomous processing of the new huge data flows available. In this work, we aim to study three different aspects within IoT. First, we will focus on the sensing infrastructure. Among the different kind of sensing technologies available to IoT systems, Radio Frequency Identification (RFID) is widely considered one of the leading technologies. RFID is the enabling technology behind applications such as access control, tracking and tracing of containers, file management, baggage sorting or equipment location. With the grow up of RFID, many facilities require multiple RFID readers usually operating close to each other. These are known as Dense Reader Environments (DREs). The co-existence of several readers operating concurrently is known to cause severe interferences on the identification process. One of the key aspects to solve in RFID DREs is achieving proper coordination among readers. This is the focus of the first part of this doctoral thesis. Unlike previous works based on heuristics, we address this problem through an optimization-based approach. The goal is identifying the maximum mean number of tags while network constraints are met. To be able to formulate these optimization problems, we have obtained analytically the mean number of identifications in a bounded -discrete or continuous- time period, an additional novel contribution of our work. Results show that our approach is overwhelmingly better than previous known methods. Along sensing technologies of IoT, Wireless Sensor Networks (WSNs) plays a fundamental role. WSNs have been largely and theoretically studied in the past decade, and many of their initial problems related to communication aspects have been successfully solved. However, with the adoption of WSNs in real-life projects, new issues have arisen, being one of them the development of realistic strategies to deploy WSNs. We have studied different ways of solving this aspect by focusing on different optimality criteria and evaluating the different trade-offs that occur when a balanced solution must be selected. On the one hand, deterministic placements subject to conflicting goals have been addressed. Results can be obtained in the form of Pareto-frontiers, allowing proper solution selection. On the other hand, a number of situations correspond to deployments were the nodes¿ position is inherently random. We have analyzed these situations leading first to a theoretical model, which later has been particularized to a Moon WSN survey. Our work is the first considering a full model with realistic properties such as 3D topography, propellant consumptions or network lifetime and mass limitations. Furthermore, development of smart applications within IoT is the focus of the Ambient Intelligence (AmI) field. Rather than having people adapting to the surrounding environment, AmI pursues the development of sensitive environments able to anticipate support in people¿s actions. AmI is progressively being introduced in many real-life environments like education, homes, health and so forth. In this thesis we develop a sport-oriented AmI system designed to improve athletes training. The goal is developing an assistant able to provide real-time training orders based on both environment and athletes¿ biometry, which is aimed to control the aerobic and the technical-tactical training. Validation experiments with the honor league UCAM Volleyball Murcia team have shown the suitability of this approach.Universidad Politécnica de CartagenaPrograma de doctorado en Tecnología de la Información y de las Comunicacione

Self organization of sensor networks for energy-efficient border coverage

Networking together hundreds or thousands of cheap sensor nodes allows users to accurately monitor a remote environment by intelligently combining the data from the individual nodes. As sensor nodes are typically battery operated, it is important to efficiently use the limited energy of the nodes to extend the lifetime of the wireless sensor network (WSN). One of the fundamental issues in WSNs is the coverage problem. In this paper, the border coverage problem in WSNs is rigorously analyzed. Most existing results related to the coverage problem in wireless sensor networks focused on planar networks; however, three dimensional (3D) modeling of the sensor network would reflect more accurately real-life situations. Unlike previous works in this area, we provide distributed algorithms that allow the selection and activation of an optimal border cover for both 2D and 3D regions of interest. We also provide self-healing algorithms as an optimization to our border coverage algorithms which allow the sensor network to adaptively reconfigure and repair itself in order to improve its own performance. Border coverage is crucial for optimizing sensor placement for intrusion detection and a number of other practical applications

Problem Specific MOEA/D for Barrier Coverage with Wireless Sensors

Barrier coverage with wireless sensors aims at detecting intruders who attempt to cross a specific area, where wireless sensors are distributed remotely at random. This paper considers limited-power sensors with adjustable ranges deployed along a linear domain to form a barrier to detect intruding incidents. We introduce three objectives to minimize: 1) total power consumption while satisfying full coverage; 2) the number of active sensors to improve the reliability; and 3) the active sensor nodes' maximum sensing range to maintain fairness. We refer to the problem as the tradeoff barrier coverage (TBC) problem. With the aim of obtaining a better tradeoff among the three objectives, we present a multiobjective optimization framework based on multiobjective evolutionary algorithm (MOEA)/D, which is called problem specific MOEA/D (PS-MOEA/D). Specifically, we define a 2-tuple encoding scheme and introduce a cover-shrink algorithm to produce feasible and relatively optimal solutions. Subsequently, we incorporate problem-specific knowledge into local search, which allows search procedures for neighboring subproblems collaborate each other. By considering the problem characteristics, we analyze the complexity and incorporate a strategy of computational resource allocation into our algorithm. We validate our approach by comparing with four competitors through several most-used metrics. The experimental results demonstrate that PS-MOEA/D is effective and outperforms the four competitors in all the cases, which indicates that our approach is promising in dealing with TBC

Optimal Deployment of Solar Insecticidal Lamps over Constrained Locations in Mixed-Crop Farmlands

Solar Insecticidal Lamps (SILs) play a vital role in green prevention and control of pests. By embedding SILs in Wireless Sensor Networks (WSNs), we establish a novel agricultural Internet of Things (IoT), referred to as the SILIoTs. In practice, the deployment of SIL nodes is determined by the geographical characteristics of an actual farmland, the constraints on the locations of SIL nodes, and the radio-wave propagation in complex agricultural environment. In this paper, we mainly focus on the constrained SIL Deployment Problem (cSILDP) in a mixed-crop farmland, where the locations used to deploy SIL nodes are a limited set of candidates located on the ridges. We formulate the cSILDP in this scenario as a Connected Set Cover (CSC) problem, and propose a Hole Aware Node Deployment Method (HANDM) based on the greedy algorithm to solve the constrained optimization problem. The HANDM is a two-phase method. In the first phase, a novel deployment strategy is utilised to guarantee only a single coverage hole in each iteration, based on which a set of suboptimal locations is found for the deployment of SIL nodes. In the second phase, according to the operations of deletion and fusion, the optimal locations are obtained to meet the requirements on complete coverage and connectivity. Experimental results show that our proposed method achieves better performance than the peer algorithms, specifically in terms of deployment cost

Covering the Boundary of a Simple Polygon with Geodesic Unit Disks

We consider the problem of covering the boundary of a simple polygon on n vertices using the minimum number of geodesic unit disks. We present an O(n \log^2 n+k) time 2-approximation algorithm for finding the centers of the disks, with k denoting the number centers found by the algorithm