Self-Calibration Methods for Uncontrolled Environments in Sensor Networks: A Reference Survey

Growing progress in sensor technology has constantly expanded the number and range of low-cost, small, and portable sensors on the market, increasing the number and type of physical phenomena that can be measured with wirelessly connected sensors. Large-scale deployments of wireless sensor networks (WSN) involving hundreds or thousands of devices and limited budgets often constrain the choice of sensing hardware, which generally has reduced accuracy, precision, and reliability. Therefore, it is challenging to achieve good data quality and maintain error-free measurements during the whole system lifetime. Self-calibration or recalibration in ad hoc sensor networks to preserve data quality is essential, yet challenging, for several reasons, such as the existence of random noise and the absence of suitable general models. Calibration performed in the field, without accurate and controlled instrumentation, is said to be in an uncontrolled environment. This paper provides current and fundamental self-calibration approaches and models for wireless sensor networks in uncontrolled environments

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs

Design and stochastic analysis of emerging large-scale wireless-powered sensor networks

Premi Extraordinari de Doctorat, promoció 2016-2017. Àmbit d’Enginyeria de les TICUndeniably, the progress in wireless networks during the last two decades is extraordinary. However, the ever-increasing upward trend in the numbers of wireless devices that will overwhelm every field of our everyday life, e.g., building automation, traffic management, health-care, etc., will introduce several issues in terms of communication and energy provision that need to be handled in advance. Regarding the communication issues, it is imperative to ensure the correct operation of the vast collection of nodes, especially for life-critical applications. Two well-known metrics that can characterize sufficiently the network reliability are the coverage and the connectivity probability that are derived by taking into account the network topology, the channel conditions between every transmitter-receiver pair, and the interference from other nodes. Nevertheless, considering all those factors is not straightforward. Lately, stochastic geometry has come into prominence, which is a mathematical tool to study the average network performance over many spatial realizations, while considering all aforementioned factors. Moreover, the other crucial issue for the large-scale dense network deployments of the future is their energy supply. Traditional battery charging or swapping for the wireless devices is both inconvenient and harms the environment, especially if we take into account the enormous numbers of nodes. Therefore, novel solutions have to be found using renewable energy sources to zero down the significant electricity consumption. Wireless energy harvesting is a convenient and environmentally-friendly approach to prolong the lifetime of networks by harvesting the energy from radio-frequency (RF) signals and converting it to direct current electricity through specialized hardware. The RF energy could be harvested from signals generated in the same or other networks. However, if the amount of harvested energy is not sufficient, solar-powered dedicated transmitters could be employed. In this way, we can achieve a favorable outcome by having both a zero-energy network operation and convenience in the charging of the wireless devices. Still, extensive investigation should be done in order to ensure that the communication performance is not affected. To that end, in this thesis, we study the communication performance in large-scale networks using tools from stochastic geometry. The networks that we study comprise wireless devices that are able to harvest the energy of RF signals. In the first part of the thesis, we present the effects of wireless energy harvesting from the transmissions of the cooperative network on the coverage probability and the network lifetime. In the second part of the thesis, we first employ batteryless nodes that are powered by dedicated RF energy transmitters to study the connectivity probability. Then, we assume that the dedicated transmitters are powered by solar energy to study the connectivity in a clustered network and investigate, for the first time, the reliability of zero-energy networks. Finally, we conclude the thesis by providing insightful research challenges for future works.Innegablemente, el progreso en las redes inalámbricas durante las últimas dos décadas es extraordinario. Sin embargo, la creciente tendencia al alza en el número de dispositivos inalámbricos que abarcarán todos los ámbitos de nuestra vida cotidiana, como la automatización de edificios, la gestión del tráfico, la atención sanitaria, etc., introducirá varias cuestiones en términos de comunicación y suministro de energía que se debe tener en cuenta con antelación. Respecto a los problemas de comunicación, es imprescindible asegurar el correcto funcionamiento de la vasta colección de nodos, especialmente para las aplicaciones vitales. Dos métricas bien conocidas que pueden caracterizar suficientemente la fiabilidad de la red son la probabilidad de cobertura y la de conectividad, que se derivan teniendo en cuenta la topología de la red, las condiciones del canal entre cada par transmisor-receptor y la interferencia de otros nodos. Sin embargo, considerar todos esos factores no es sencillo. Últimamente, la geometría estocástica ha llegado a la prominencia como un metodo de análisis, que es una herramienta matemática para estudiar el rendimiento promedio de la red sobre muchas realizaciones espaciales, teniendo en cuenta todos los factores mencionados. Además, la otra cuestión crucial para los despliegues de alta densidad de las redes futuras es su suministro de energía. La carga o el intercambio de baterías para los dispositivos inalámbricos es inconveniente y daña el medio ambiente, especialmente si tenemos en cuenta el enorme número de nodos utilizados. Por lo tanto, se deben encontrar nuevas soluciones utilizando fuentes de energía renovables para reducir el consumo de electricidad. La recolección de energía inalámbrica es un método conveniente y respetuoso con el medio ambiente para prolongar la vida útil de las redes recolectando la energía de las señales de radiofrecuencia (RF) y convirtiéndola en electricidad de corriente continua mediante un hardware especializado. La energía de RF podría ser obtenida a partir de señales generadas en la misma o en otras redes. Sin embargo, si la cantidad de energía obtenida no es suficiente, podrían emplearse transmisores de energía inalambricos que la obtuvieran mediante paneles fotovoltaicos. De esta manera, podemos lograr un resultado favorable teniendo tanto una operación de red de energía cero como una conveniencia en la carga de los dispositivos inalámbricos. Por lo tanto, una investigación exhaustiva debe hacerse con el fin de garantizar que el rendimiento de la comunicación no se ve afectada. En esta tesis se estudia el rendimiento de la comunicación en redes de gran escala utilizando técnicas de geometría estocástica. Las redes que se estudian comprenden dispositivos inalámbricos capaces de recoger la energía de las señales RF. En la primera parte de la tesis, presentamos los efectos de la recolección de energía inalámbrica de las transmisiones de la red cooperativa sobre la probabilidad de cobertura y la vida útil de la red. En la segunda parte de la tesis, primero empleamos nodos sin baterías que son alimentados por transmisores de energía de RF para estudiar la probabilidad de conectividad. A continuación, asumimos que los transmisores dedicados son alimentados por energía solar para estudiar la conectividad en una red agrupada (clustered network) e investigar, por primera vez, la fiabilidad de las redes de energía cero. Finalmente, concluimos la tesis aportando nuevas lineas de investigación para trabajos futurosAward-winningPostprint (published version

Design and stochastic analysis of emerging large-scale wireless-powered sensor networks

Undeniably, the progress in wireless networks during the last two decades is extraordinary. However, the ever-increasing upward trend in the numbers of wireless devices that will overwhelm every field of our everyday life, e.g., building automation, traffic management, health-care, etc., will introduce several issues in terms of communication and energy provision that need to be handled in advance. Regarding the communication issues, it is imperative to ensure the correct operation of the vast collection of nodes, especially for life-critical applications. Two well-known metrics that can characterize sufficiently the network reliability are the coverage and the connectivity probability that are derived by taking into account the network topology, the channel conditions between every transmitter-receiver pair, and the interference from other nodes. Nevertheless, considering all those factors is not straightforward. Lately, stochastic geometry has come into prominence, which is a mathematical tool to study the average network performance over many spatial realizations, while considering all aforementioned factors. Moreover, the other crucial issue for the large-scale dense network deployments of the future is their energy supply. Traditional battery charging or swapping for the wireless devices is both inconvenient and harms the environment, especially if we take into account the enormous numbers of nodes. Therefore, novel solutions have to be found using renewable energy sources to zero down the significant electricity consumption. Wireless energy harvesting is a convenient and environmentally-friendly approach to prolong the lifetime of networks by harvesting the energy from radio-frequency (RF) signals and converting it to direct current electricity through specialized hardware. The RF energy could be harvested from signals generated in the same or other networks. However, if the amount of harvested energy is not sufficient, solar-powered dedicated transmitters could be employed. In this way, we can achieve a favorable outcome by having both a zero-energy network operation and convenience in the charging of the wireless devices. Still, extensive investigation should be done in order to ensure that the communication performance is not affected. To that end, in this thesis, we study the communication performance in large-scale networks using tools from stochastic geometry. The networks that we study comprise wireless devices that are able to harvest the energy of RF signals. In the first part of the thesis, we present the effects of wireless energy harvesting from the transmissions of the cooperative network on the coverage probability and the network lifetime. In the second part of the thesis, we first employ batteryless nodes that are powered by dedicated RF energy transmitters to study the connectivity probability. Then, we assume that the dedicated transmitters are powered by solar energy to study the connectivity in a clustered network and investigate, for the first time, the reliability of zero-energy networks. Finally, we conclude the thesis by providing insightful research challenges for future works.Innegablemente, el progreso en las redes inalámbricas durante las últimas dos décadas es extraordinario. Sin embargo, la creciente tendencia al alza en el número de dispositivos inalámbricos que abarcarán todos los ámbitos de nuestra vida cotidiana, como la automatización de edificios, la gestión del tráfico, la atención sanitaria, etc., introducirá varias cuestiones en términos de comunicación y suministro de energía que se debe tener en cuenta con antelación. Respecto a los problemas de comunicación, es imprescindible asegurar el correcto funcionamiento de la vasta colección de nodos, especialmente para las aplicaciones vitales. Dos métricas bien conocidas que pueden caracterizar suficientemente la fiabilidad de la red son la probabilidad de cobertura y la de conectividad, que se derivan teniendo en cuenta la topología de la red, las condiciones del canal entre cada par transmisor-receptor y la interferencia de otros nodos. Sin embargo, considerar todos esos factores no es sencillo. Últimamente, la geometría estocástica ha llegado a la prominencia como un metodo de análisis, que es una herramienta matemática para estudiar el rendimiento promedio de la red sobre muchas realizaciones espaciales, teniendo en cuenta todos los factores mencionados. Además, la otra cuestión crucial para los despliegues de alta densidad de las redes futuras es su suministro de energía. La carga o el intercambio de baterías para los dispositivos inalámbricos es inconveniente y daña el medio ambiente, especialmente si tenemos en cuenta el enorme número de nodos utilizados. Por lo tanto, se deben encontrar nuevas soluciones utilizando fuentes de energía renovables para reducir el consumo de electricidad. La recolección de energía inalámbrica es un método conveniente y respetuoso con el medio ambiente para prolongar la vida útil de las redes recolectando la energía de las señales de radiofrecuencia (RF) y convirtiéndola en electricidad de corriente continua mediante un hardware especializado. La energía de RF podría ser obtenida a partir de señales generadas en la misma o en otras redes. Sin embargo, si la cantidad de energía obtenida no es suficiente, podrían emplearse transmisores de energía inalambricos que la obtuvieran mediante paneles fotovoltaicos. De esta manera, podemos lograr un resultado favorable teniendo tanto una operación de red de energía cero como una conveniencia en la carga de los dispositivos inalámbricos. Por lo tanto, una investigación exhaustiva debe hacerse con el fin de garantizar que el rendimiento de la comunicación no se ve afectada. En esta tesis se estudia el rendimiento de la comunicación en redes de gran escala utilizando técnicas de geometría estocástica. Las redes que se estudian comprenden dispositivos inalámbricos capaces de recoger la energía de las señales RF. En la primera parte de la tesis, presentamos los efectos de la recolección de energía inalámbrica de las transmisiones de la red cooperativa sobre la probabilidad de cobertura y la vida útil de la red. En la segunda parte de la tesis, primero empleamos nodos sin baterías que son alimentados por transmisores de energía de RF para estudiar la probabilidad de conectividad. A continuación, asumimos que los transmisores dedicados son alimentados por energía solar para estudiar la conectividad en una red agrupada (clustered network) e investigar, por primera vez, la fiabilidad de las redes de energía cero. Finalmente, concluimos la tesis aportando nuevas lineas de investigación para trabajos futuro

Quality of Information in Mobile Crowdsensing: Survey and Research Challenges

Smartphones have become the most pervasive devices in people's lives, and are clearly transforming the way we live and perceive technology. Today's smartphones benefit from almost ubiquitous Internet connectivity and come equipped with a plethora of inexpensive yet powerful embedded sensors, such as accelerometer, gyroscope, microphone, and camera. This unique combination has enabled revolutionary applications based on the mobile crowdsensing paradigm, such as real-time road traffic monitoring, air and noise pollution, crime control, and wildlife monitoring, just to name a few. Differently from prior sensing paradigms, humans are now the primary actors of the sensing process, since they become fundamental in retrieving reliable and up-to-date information about the event being monitored. As humans may behave unreliably or maliciously, assessing and guaranteeing Quality of Information (QoI) becomes more important than ever. In this paper, we provide a new framework for defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the current state-of-the-art on the topic. We also outline novel research challenges, along with possible directions of future work.Comment: To appear in ACM Transactions on Sensor Networks (TOSN

Quality-of-service provisioning for dynamic heterogeneous wireless sensor networks

A Wireless Sensor Network (WSN) consists of a large collection of spatially dis- tributed autonomous devices with sensors to monitor physical or environmental conditions, such as air-pollution, temperature and traffic flow. By cooperatively processing and communicating information to central locations, appropriate ac- tions can be performed in response. WSNs perform a large variety of applications, such as the monitoring of elderly persons or conditions in a greenhouse. To correctly and efficiently perform a task, the behaviour of the WSN should be such that sufficient Quality-of-Service (QoS) is provided. QoS is defined by constraints and objectives on network quality metrics, such as a maximum end- to-end packet loss or minimum network lifetime. After defining the application we want the WSN to perform, many steps are involved in designing the WSN such that sufficient QoS is provided. First, a (heterogeneous) set of sensor nodes and protocols need to be selected. Furthermore, a suitable deployment has to be found and the network should be configured for its first use. This configuration involves setting all controllable parameters that influence its behaviour, such as selecting the neighbouring node(s) to communicate to and setting the transmission power of its radio, to ensure that the WSN provides the required QoS. Configuring the network is a complex task as the number of parameters and their possible values are large and trade-offs between multiple quality metrics exist. High transmission power may result in a low packet loss to a neighbouring node, but also in a high power consumption and low lifetime. Heterogeneity in the network causes the impact of parameters to be different between nodes, requiring parameters of nodes to be set individually. Moreover, a static configuration is typically not sufficient to make the most efficient trade-off between the quality metrics at all times in a dynamic environment. Run-time mechanisms are needed to maintain the required level of QoS under changing circumstances, such as changing external interference, mobility of nodes or fluctuating traffic load. This thesis deals with run-time reconfiguration of dynamic heterogeneous wire- less sensor networks to maintain a required QoS, given a deployed network with selected communication protocols and their controllable parameters. The main contribution of this thesis is an efficient QoS provisioning strategy. It consists of three parts: a re-active reconfiguration method, a generic distributed service to estimate network metrics and a pro-active reconfiguration method. In the re-active method, nodes collaboratively respond to discrepancies be- tween the current and required QoS. Nodes use feedback control which, at a given speed, adapts parameters of the node to continuously reduce any error between the locally estimated network QoS and QoS requirements. A dynamic predictive model is used and updated at run-time, to predict how different parameter adap- tations influence the QoS. Setting the speed of adaptation allows us to influence the trade-off between responsiveness and overhead of the approach, and to tune it to the characteristics of the application scenario. Simulations and experiments with an actual deployment show the successful integration in practical scenar- ios. Compared to existing configuration strategies, we are able to extend network lifetime significantly, while maintaining required packet delivery ratios. To solve the non-trivial problem of efficiently estimating network quality met- rics, we introduce a generic distributed service to distributively compute various network metrics. This service takes into account the possible presence of links with asymmetric quality that may vary over time, by repeated forwarding of informa- tion over multiple hops combined with explicit information validity management. The generic service is instantiated from the definition of a recursive local update function that converges to a fixed point representing the desired metric. We show the convergence and stability of various instantiations. Parameters can be set in accordance with the characteristics of the deployment and influence the trade-off between accuracy and overhead. Simulations and experiments show a significant increase in estimation accuracy, and efficiency of a protocol using the estimates, compared to today’s current approaches. This service is integrated in various protocol stacks providing different kinds of network metric estimates. The pro-active reconfiguration method reconfigures in response to predefined run-time detectable events that may cause the network QoS to change signifi- cantly. While the re-active method is generally applicable and independent of the application scenario, the, complementary, pro-active method exploits any a-priori knowledge of the application scenario to adapt more efficiently. A simple example is that as soon as a person with a body sensor node starts walking we know that several aspects, including the network topology, will change. To avoid degradation of network QoS, we pro-actively adapt parameters, in this case, for instance, the frequency of updating the set of neighbouring nodes, as soon as we observe that a person starts to walk. At design time, different modes of operation are selected to be distinguished at run-time. Analysis techniques, such as simulations, are used to determine a suitable configuration for each of these modes. At run time, the approach ensures that nodes can detect the mode in which they should operate. We describe the integration of the pro-active method for two practical monitoring applications. Simulations and experiments show the feasibility of an implementa- tion on resource constrained nodes. The pro-active reconfiguration allows for an efficient QoS provisioning in combination with the re-active approach

A Novel Approach to Transmission Power, Lifetime and Connectivity Optimization in Asymmetric Networks

This thesis deals with the problem of proper power management over asymmetric networks represented by weighted directed graphs (digraphs) in the presence of various constraints. Three different problems are investigated in this study. First, the problem of total transmission power optimization and connectivity control over the network is examined. The notion of generalized algebraic connectivity (GAC), used as a network connectivity measure, is formulated as an implicit function of the nodes' transmission powers. An optimization problem is then presented to minimize the total transmission power of the network while considering constraints on the values of the GAC and the individual transmission power levels. The problem of network lifetime maximization and connectivity control is investigated afterwards. Each node is assumed to deplete its battery linearly with respect to the transmission powers used for communication, and the network lifetime is defined as the minimum lifetime over all nodes. Finally, it is desired to maximize the connectivity level of the network with constraints on the total transmission power of the network and the individual transmission powers. The interior point and the mixed interior point-exterior point methods are utilized to transform these constrained optimization problems into sequential optimization problems. Given the new formulation, each subproblem is then solved numerically via the subgradient method with backtracking line search. A distributed version of the algorithm, taking into account the estimation of global quantities, is provided. The asymptotic convergence of the proposed centralized and distributed algorithms is demonstrated analytically, and their effectiveness is verified by simulations