Relevant bibliographies by topics / Wireless sensor networks Quality control

Academic literature on the topic 'Wireless sensor networks Quality control'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Wireless sensor networks Quality control"

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Singh, Kamred Udham, Ankit Kumar, Linesh Raja, Vikas Kumar, Alok Kumar Singh kushwaha, Neeraj Vashney, and Manoj Chhetri. "An Artificial Neural Network-Based Pest Identification and Control in Smart Agriculture Using Wireless Sensor Networks." Journal of Food Quality 2022 (May 17, 2022): 1–12. http://dx.doi.org/10.1155/2022/5801206.

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Despite living in a rural country, farmers in India face several challenges. Every year, they suffer significant losses due to agricultural insect infestation. These losses are primarily the result of inadequate field surveillance, crop diseases, and ineffective pesticide management. We need cutting-edge technology that is constantly evolving to maintain control over such major concerns responsible for output reductions year after year. Wireless sensor networks address all of these issues; in fact, wireless sensor network technology is quickly becoming the backbone of modern precision agriculture. We propose a strategy for pest monitoring using wireless sensor networks in this study by simply recognizing insect behaviour using various sensors. We proposed a rapid and accurate insect detection and categorization approach based on five important crops and associated insect pests. This method examines insect behaviour by collecting data from sensors placed in the field. The results show that the proposed work improves the accuracy of the existing work by 3.9 percent.
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Bok, Kyoungsoo, Eunkyung Ryu, Junho Park, Jaijin Jung, and Jaesoo Yoo. "Multimedia congestion control in wireless sensor networks." Computer Science and Information Systems 12, no. 2 (2015): 801–21. http://dx.doi.org/10.2298/csis141009027b.

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In this paper, we propose a new congestion control scheme to minimize data loss and maintain data quality in wireless multimedia sensor networks. The proposed scheme extracts and transfers dynamic regions by considering monitoring characteristics over multimedia sensor network environments to reduce the transferred data. Furthermore, it can reduce the packet size by deleting and transferring low-priority bit data by considering multimedia data characteristics during congestion situations to minimize packet loss. To show the superiority of the proposed scheme, we compare it with the existing congestion control schemes through simulation.
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Bruneo, D., A. Puliafito, and M. Scarpa. "Energy control in dependable wireless sensor networks: a modelling perspective." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 225, no. 4 (July 20, 2011): 424–34. http://dx.doi.org/10.1177/1748006x10397845.

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Wireless sensor networks (WSN) are composed of a large number of tiny sensor nodes randomly distributed over a geographical region. In order to reduce power consumption, battery-operated sensors undergo cycles of sleeping–active periods that reduce their ability to send/receive data. Starting from the Markov reward model theory, this paper presents a dependability model to analyse the reliability of a sensor node. Also, a new dependability parameter is introduced, referred to as producibility, which is able to capture the capability of a sensor to accomplish its mission. Two different model solution techniques are proposed, one based on the evaluation of the accumulated reward distribution and the other based on an equivalent model based on non-Markovian stochastic Petri nets. The obtained results are used to investigate the dependability of a whole WSN taking into account the presence of redundant nodes. Topological aspects are taken into account, providing a quantitative comparison among three typical network topologies: star, tree, and mesh. Numerical results are provided in order to highlight the advantages of the proposed technique and to demonstrate the equivalence of the proposed approaches.
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Tati, Reza, Fariborz Ahmadi, Farhad Jafari, and Mostafa Tofighi. "Quality of Service Support in Wireless Sensor Networks." Key Engineering Materials 467-469 (February 2011): 2078–84. http://dx.doi.org/10.4028/www.scientific.net/kem.467-469.2078.

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All of middlewares of modern wireless sensor networks has this weakness that many of these middlewares have the ability to simultaneous support from limit amounts of quality of service parameters. Our aim is simultaneous and dynamic support from several quality of service measure in middleware layer with obtained weight coefficients. In this paper, we add a layer of Quality of service management to middleware, in which this layer has duty of service of Quality of service management and control. This layer answers demanded Quality of service improvement from application by wireless sensor network.
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Shiltagh, Nadia, and Zainab Faisal. "Traffic Management in Wireless Sensor Network Based on Modified Neural Networks." Iraqi Journal for Computers and Informatics 41, no. 1 (December 31, 2014): 4–8. http://dx.doi.org/10.25195/ijci.v41i1.90.

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Wireless Sensor Networks (WSNs) are event-driven network systems consist of many sensors node which aredensely deployed and wirelessly interconnected that allow retrieving of monitoring data. In Wireless sensor network,whenever an event is detected, the data related to the event need to be sent to the sink node (data collection node). Sink nodeis the bottleneck of network there may be chance for congestion due to heavy data traffic. Due to congestion, it leads to dataloss; it may be important data also. To achieve this objective, soft computing based on Neural Networks (NNs) CongestionController approach is proposed. The NN is activated using wavelet activation function that is used to control the traffic ofthe WSN. The proposed approach which is called as Modified Neural Network Wavelet Congestion Control (MNNWCC), hasthree main activities: the first one is detecting the congestion as congestion level indications; the second one is estimated thetraffic rate that the upstream traffic rate is adjusted to avoid congestion in next time, the last activates of the proposedapproach is improved the Quality of Services (QoS), by enhancement the Packet Loss Ratio (PLR), Throughput (TP), BufferUtilization (BU) and Network Energy (NE) . The simulation results show that the proposed approach can avoid the networkcongestion and improve the QoS of network.
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Jin, Yong, Jian Cai, Huan Dai, Kaijian Xia, and Ping Xu. "Lightweight QoE Driven and Invulnerability Guarantee Opportunistic Control Scheme for Wireless Sensor Networks." International Journal of Online Engineering (iJOE) 12, no. 08 (August 30, 2016): 19. http://dx.doi.org/10.3991/ijoe.v12i08.5726.

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This paper proposed the lightweight QoE driven adaptive invulnerability wireless communication control method, including the wireless communication terminal equipment with invulnerability antenna. According to the quality of wireless network channel quality, the lightweight QoE driven scheme was developed. According to user needs, the quality of the network, survivable ability of wireless communication terminal and wireless communication survivability requirements, we proposed three matching rules by considering the wireless hop number, data size and life cycle. The experiments demonstrated that the proposed scheme can optimize wireless communication terminal equipment and wireless opportunistic communication network construction, guarantee the user experience quality and improve wireless communication network survivability.
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P.Barde, Vaishali. "A PERUSAL STUDY OF METHODS FOR ENERGY EFFICIENT MULTI OBJECT TRACKING IN WIRELESS SENSOR NETWORKS." International Research Journal of Computer Science 8, no. 12 (December 31, 2021): 279–82. http://dx.doi.org/10.26562/irjcs.2021.v0812.002.

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Wireless sensor networks (WSNs) has various applications in different areas such as object detection and target tracking, industrial process monitoring, environmental monitoring, wildlife monitoring, Robot control and security applications for buildings. In WSNs, Energy efficiency is one of the important research issues, as it determines the lifetime of the sensor network deployed for the specific applications. Object tracking is one of the dominant applications of wireless sensor networks and many energy-efficient multi object tracking algorithms are used for precise or exact object tracking. The main focus this paper is the perusal study of all different energy-efficient object tracking methods and algorithms for Wireless Sensor Network.
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Li, Xiaomin, Lixue Zhu, Xuan Chu, and Han Fu. "Edge Computing-Enabled Wireless Sensor Networks for Multiple Data Collection Tasks in Smart Agriculture." Journal of Sensors 2020 (February 25, 2020): 1–9. http://dx.doi.org/10.1155/2020/4398061.

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At present, precision agriculture and smart agriculture are the hot topics, which are based on the efficient data collection by using wireless sensor networks (WSNs). However, agricultural WSNs are still facing many challenges such as multitasks, data quality, and latency. In this paper, we propose an efficient solution for multiple data collection tasks exploiting edge computing-enabled wireless sensor networks in smart agriculture. First, a novel data collection framework is presented by merging WSN and edge computing. Second, the data collection process is modeled, including a plurality of sensors and tasks. Next, according to each specific task and correlation between task and sensors, on the edge computing server, a double selecting strategy is established to determine the best node and sensor network that fulfills quality of data and data collection time constraints of tasks. Furthermore, a data collection algorithm is designed, based on set values for quality of data. Finally, a simulation environment is constructed where the proposed strategy is applied, and results are analyzed and compared to the traditional methods. According to the comparison results, the proposal outperforms the traditional methods in metrics.
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Shakir, Mustafa, Obaid Ur Rehman, Zeeshan Abbas, Abdullah Masood, and Wajeeha Shahid. "Evaluation of Video Quality in Wireless Multimedia Sensor Networks." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 1 (February 1, 2016): 223. http://dx.doi.org/10.11591/ijece.v6i1.7573.

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<p class="Default">Simulating wireless sensor networks; there implementation and evaluation, require the use of a discrete event simulator. Omnet++ is quite a powerful simulator which supports concise and easy modeling of wired as well as wireless sensors environment. Scenarios involving multimedia transmissions with characteristics of video quality control and evaluation must be computed on the basis of Quality of Experience which relies on user’s perception to maintain the video quality. For the multimedia growth and awareness of future WMSNs, it is quite necessary that the performance should be tested for different types of radio models. So varying the radio parameters may allow for the optimization and improvement of the video quality. In this paper we have provided a test bench for the easy evaluation and optimization of the performance of WMSNs using different radio models. The performance is evaluated based on the QoE metrics; i.e. PSNR(Peak Signal-to-Noise ratio) and MoS(Mean Opinion Score), which depend on user’s perception to maintain the video quality.</p>
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Shakir, Mustafa, Obaid Ur Rehman, Zeeshan Abbas, Abdullah Masood, and Wajeeha Shahid. "Evaluation of Video Quality in Wireless Multimedia Sensor Networks." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 1 (February 1, 2016): 223. http://dx.doi.org/10.11591/ijece.v6i1.pp223-234.

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<p class="Default">Simulating wireless sensor networks; there implementation and evaluation, require the use of a discrete event simulator. Omnet++ is quite a powerful simulator which supports concise and easy modeling of wired as well as wireless sensors environment. Scenarios involving multimedia transmissions with characteristics of video quality control and evaluation must be computed on the basis of Quality of Experience which relies on user’s perception to maintain the video quality. For the multimedia growth and awareness of future WMSNs, it is quite necessary that the performance should be tested for different types of radio models. So varying the radio parameters may allow for the optimization and improvement of the video quality. In this paper we have provided a test bench for the easy evaluation and optimization of the performance of WMSNs using different radio models. The performance is evaluated based on the QoE metrics; i.e. PSNR(Peak Signal-to-Noise ratio) and MoS(Mean Opinion Score), which depend on user’s perception to maintain the video quality.</p>
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Dissertations / Theses on the topic "Wireless sensor networks Quality control"

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Bildea, Ana. "Link Quality in Wireless Sensor Networks." Thesis, Grenoble, 2013. http://www.theses.fr/2013GRENM054/document.

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L'objectif de la thèse est d'étudier la variation temporelle de la qualité des liens dans les réseaux de capteurs sans fil à grande échelle, de concevoir des estimateurs permettant la différenciation, à court terme et long terme, entre liens de qualité hétérogène. Tout d'abord, nous étudions les caractéristiques de deux paramètres de la couche physique: RSSI (l'indicateur de puissance du signal reçu) et LQI (l'indicateur de la qualité de liaison) sur SensLab, une plateforme expérimentale de réseau de capteurs à grande échelle situé à l'intérieur de bâtiments. Nous observons que le RSSI et le LQI permettent de discriminer des liens de différentes qualités. Ensuite, pour obtenir un estimateur de PRR, nous avons approximé le diagramme de dispersion de la moyenne et de l'écart-type du LQI et RSSI par une fonction Fermi-Dirac. La fonction nous permet de trouver le PRR à partir d'un niveau donné de LQI. Nous avons évalué l'estimateur en calculant le PRR sur des fenêtres de tailles variables et en le comparant aux valeurs obtenues avec l'estimateur. Par ailleurs, nous montrons en utilisant le modèle de Gilbert-Elliot (chaîne de Markov à deux états) que la corrélation des pertes de paquets dépend de la catégorie de lien. Le modèle permet de distinguer avec précision les différentes qualités des liens, en se basant sur les probabilités de transition dérivées de la moyenne et de l'écart-type du LQI. Enfin, nous proposons un modèle de routage basé sur la qualité de lien déduite de la fonction de Fermi-Dirac approximant le PRR et du modèle Markov Gilbert-Elliot à deux états. Notre modèle est capable de distinguer avec précision les différentes catégories de liens ainsi que les liens fortement variables
The goal of the thesis is to investigate the issues related to the temporal link quality variation in large scale WSN environments, to design energy efficient link quality estimators able to distinguish among links with different quality on a short and a long term. First, we investigate the characteristics of two physical layer metrics: RSSI (Received Signal Strength Indication) and LQI (Link Quality Indication) on SensLAB, an indoor large scale wireless sensor network testbed. We observe that RSSI and LQI have distinct values that can discriminate the quality of links. Second, to obtain an estimator of PRR, we have fitted a Fermi-Dirac function to the scatter diagram of the average and standard variation of LQI and RSSI. The function enables us to find PRR for a given level of LQI. We evaluate the estimator by computing PRR over a varying size window of transmissions and comparing with the estimator. Furthermore, we show using the Gilbert-Elliot two-state Markov model that the correlation of packet losses and successful receptions depend on the link category. The model allows to accurately distinguish among strongly varying intermediate links based on transition probabilities derived from the average and the standard variation of LQI. Finally, we propose a link quality routing model driven from the F-D fitting functions and the Markov model able to discriminate accurately link categories as well as high variable links
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LI, I.-HUNG. "Phase and Rate Control for Improving Information Quality in 802.15.4 Wireless Sensor." OpenSIUC, 2010. https://opensiuc.lib.siu.edu/theses/396.

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High information quality is a paramount requirement for wireless sensor network monitoring applications. However, it is challenging to achieve a cost effective information quality solution due to unpredictable environment noise and events, unreliable wireless channel and network bandwidth, and resource and energy constraints. Specifically, the dynamic and unreliable nature of WSNs make it difficult to pre-determine optimum sensor rates and predict packet loss. To address this problem, we use information quality metrics presented by [26, 11] which characterize information quality based on the sampling frequency of sensor nodes and the packet loss rate during network transmission. These fundamental quality metrics are based on signal-to-noise ratio and are therefore application independent. Based on these metrics, a quality-aware scheduling system (QSS) is developed, which exploits cross-layer control of sensor nodes to effectively schedule data sensing and forwarding. Particularly, we develop and evaluate several QSS scheduling mechanisms: passive, reactive and perceptive. These mechanisms can adapt to environment noise, bandwidth variation and wireless channel collisions by dynamically controlling sensor rates and sensor phase. Our software and hardware experimental results indicate that our QSS is a novel and effective approach to improve information quality for WSNs.
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Nkwogu, Daniel Nnaemeka. "Quality of service optimization and adaptive learning in wireless sensor actuator networks for control applications." Thesis, University of Aberdeen, 2014. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=215699.

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Wireless sensor actuator networks (WSANs) are becoming a solution for the implementation of control applications. Sensors and actuators can be deployed forming a large or dense network to monitor and control physical parameters or systems. However, this comes with challenges. Reliable data transmission and real-time communication constraints are the most significant challenges in WSANs for control applications because wireless networks are characterised by harsh transmission conditions. The use of WSANs for critical control applications has not gained sufficient progress as wireless networks are perceived to be totally unreliable and hence unsuitable. This makes reliable data transmission a priority in this research. Control applications will have a number of quality of service (QoS) requirements, such as requiring a very low packet-loss rate (PLR), minimum delay and guaranteed packet delivery. The overall goal of this research is to develop a framework that ensures reliable and real-time communication within the sensor network. A totally reliable network design involves ensuring reliability in areas such as the medium access control, connectivity, scalability, lifetime, clustering and routing with trade-offs such as energy consumption, system throughput and computational complexity. In this thesis, we introduce a unique method of improving reliability and real-time communication for control applications using a link quality routing mechanism which is tied into the ZigBee addressing scheme. ZigBee routing protocols do not consider link quality when making routing decisions. The results based on common network test conditions give a clear indication of the impact on network performance for various path loss models. The proposed link quality aware routing (LQAR) showed a highly significant 20.5% improvement in network delays against the ZigBee hierarchical tree routing (HTR) protocol. There is also a 17% improvement in the PLR. We also investigate variable sampling to mitigate the effects of delay in WSANs using a neural network delay predictor and observer based control system model. Our focus on variable sampling is to determine the appropriate neural network topology for delay prediction and the impact of additional neural network inputs such as PLR and throughput. The major contribution of this work is the use of typical obtainable delay series for training the neural network. Most studies have used random generated numbers which are not a correct representation of delays actually experienced in a wireless network. In addition, results show that the use of network packet loss information improves the prediction accuracy of delay. Our results show that adequate prediction of the time-delay series using the observer based variable sampling model influences the performance of the control system model under the assumptions and stated conditions.
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Hughes, Jack Bryan. "Real-time link quality estimation and holistic transmission power control for wireless sensor networks." Thesis, University of Huddersfield, 2018. http://eprints.hud.ac.uk/id/eprint/34661/.

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Wireless sensor networks (WSNs) are becoming widely adopted across multiple industries to implement sensor and non-critical control applications. These networks of smart sensors and actuators require energy efficient and reliable operation to meet application requirements. Regulatory body restrictions, hardware resource constraints and an increasingly crowded network space makes realising these requirements a significant challenge. Transmission power control (TPC) protocols are poised for wide spread adoption in WSNs to address energy constraints and prolong the lifetime of the networked devices. The complex and dynamic nature of the transmission medium; the processing and memory hardware resource constraints and the low channel throughput makes identifying the optimum transmission power a significant challenge. TPC protocols for WSNs are not well developed and previously published works suffer from a number of common deficiencies such as; having poor tuning agility, not being practical to implement on the resource constrained hardware and not accounting for the energy consumed by packet retransmissions. This has resulted in several WSN standards featuring support for TPC but no formal definition being given for its implementation. Addressing the deficiencies associated with current works is required to increase the adoption of TPC protocols in WSNs. In this thesis a novel holistic TPC protocol with the primary objective of increasing the energy efficiency of communication activities in WSNs is proposed, implemented and evaluated. Firstly, the opportunities for TPC protocols in WSN applications were evaluated through developing a mathematical model that compares transmission power against communication reliability and energy consumption. Applying this model to state-of-the-art (SoA) radio hardware and parameter values from current WSN standards, the maximum energy savings were quantified at up to 80% for links that belong to the connected region and up to 66% for links that belong to the transitional and disconnected regions. Applying the results from this study, previous assumptions that protocols and mechanisms, such as TPC, not being able to achieve significant energy savings at short communications distances are contested. This study showed that the greatest energy savings are achieved at short communication distances and under ideal channel conditions. An empirical characterisation of wireless link quality in typical WSN environments was conducted to identify and quantify the spatial and temporal factors which affect radio and link dynamics. The study found that wireless link quality exhibits complex, unique and dynamic tendencies which cannot be captured by simplistic theoretical models. Link quality must therefore be estimated online, in real-time, using resources internal to the network. An empirical characterisation of raw link quality metrics for evaluating channel quality, packet delivery and channel stability properties of a communication link was conducted. Using the recommendations from this study, a novel holistic TPC protocol (HTPC) which operates on a per-packet basis and features a dynamic algorithm is proposed. The optimal TP is estimated through combining channel quality and packet delivery properties to provide a real-time estimation of the minimum channel gain, and using the channel stability properties to implement an adaptive fade margin. Practical evaluations show that HTPC is adaptive to link quality changes and outperforms current TPC protocols by achieving higher energy efficiency without detrimentally affecting the communication reliability. When subjected to several common temporal variations, links implemented with HTPC consumed 38% less than the current practise of using a fixed maximum TP and between 18-39% less than current SoA TPC protocols. Through offline computations, HTPC was found to closely match the performance of the optimal link performance, with links implemented with HTPC only consuming 7.8% more energy than when the optimal TP is considered. On top of this, real-world implementations of HTPC show that it is practical to implement on the resource constrained hardware as a result of implementing simplistic metric evaluation techniques and requiring minimal numbers of samples. Comparing the performance and characteristics of HTPC against previous works, HTPC addresses the common deficiencies associated with current solutions and therefore presents an incremental improvement on SoA TPC protocols.
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Sharif, Atif. "Reliable, congestion aware transport layer protocol for heterogeneous wireless sensor networks." Thesis, Curtin University, 2011. http://hdl.handle.net/20.500.11937/87.

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Energy is the biggest concern for any heterogeneous WSNs and achieving high energy efficiency is of paramount importance for the longevity of a heterogeneous WSNs. Communicating in- formation from the sensing region to the sink is a critical task in the entire operation of a heterogeneous WSNs. Such information needs to be reliably communicated, while avoiding any network congestion, from source to sink in order to ensure that application-specific Quality of Service objectives are met for any given scenario. This thesis developed several transport layer protocols to address the issues of congestion control, reliability assurance, simultaneously supporting heterogeneous traffic environment and energy efficiency for a heterogeneous WSNs.The first aim of the proposed research is to develop a congestion control scheme for a heterogeneous WSNs. The envisaged congestion control scheme has dual functionality. Firstly, it should be capable of handling the traffic heterogeneity and secondly, it intelligently assigns the source transmission rates and channel bandwidth for avoiding congested scenarios within the network, thereby avoiding any unnecessary packet retransmissions, due to packet drops caused by congestion. This produces high network good throughput, effective use of channel bandwidth, minimum E-2-E data packet latency etc. All the proposed transport layer protocol schemes e.g. End-to-End Reliable and Congestion Aware Transport Layer Protocol (ERCTP), Lightweight Congestion Aware Reliable Transport protocol (LCART) and Lightweight Congestion Aware Reliable Transport Protocol-implicit (LCARTi) are designed with this aim in mind.The second aim of the proposed research is to develop an intelligent reliability ensuring scheme capable of handling bidirectional reliability issues associated with data and control information flow within the heterogeneous WSNs. The design takes into account the variable nature of reliability assurance based on the nature of the traffic. For instance, multimedia flow is given a high reliability measure in comparison to scalar and non-event information flow, since the multimedia has a high retransmission cost. All the proposed transport layer protocol schemes such as ERCTP, LCART and LCARTi are designed in order to achieve this objective.The third aim of the proposed research is to develop a scheme that simultaneously handles the heterogeneous traffic flows within the same network. The proposed scheme has the intelligence to determine the nature of traffic and to allocate different bandwidth based on this nature in order to meet the stringent requirements as imposed by the application-specific QoS constraints like E-2-E data packet latency, high good throughput etc. All the proposed transport layer protocol schemes such as ERCTP, LCART and LCARTi are designed with this objective in mind.The fourth and final aim of the proposed research is to create a mechanism that merges the common functionalities of different layers of the WSNs communication stack in order to maximise energy efficiency. This involves finding the relationship between the transport and the lower MAC and wireless-physical layers of the WSNs communication stack. This merging will result in better utilization of network resources such as bandwidth, storage etc. and helps to achieve the objective of energy efficiency. Only the LCART and LCARTi designs achieve this proposed research aim.
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Boubrima, Ahmed. "Deployment and scheduling of wireless sensor networks for air pollution monitoring." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSEI018.

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Les réseaux de capteurs sans fil (RCSF) sont largement utilisés dans les applications environnementales où l’objectif est de détecter un phénomène physique tel que la température, l’humidité, la pollution de l’air, etc. Dans ce contexte d’application, l’utilisation de RCSF permet de comprendre les variations du phénomène et donc être en mesure de prendre des décisions appropriées concernant son impact. En raison des limitations de ses méthodes de suivi traditionnelles et de sa grande variabilité spatiale et temporelle, la pollution de l'air est considérée comme l'un des principaux phénomènes physiques qui restent à étudier et à caractériser. Dans cette thèse, nous considérons trois applications concernant l’utilisation de RCSF pour le suivi de la pollution de l’air : la cartographie en temps réel de la qualité de l’air, la détection de dépassements de seuils des polluants et la correction de modèles physiques qui simulent le phénomène de dispersion de la pollution. Toutes ces applications nécessitent de déployer et d’ordonnancer minutieusement les capteurs afin de mieux comprendre la pollution atmosphérique tout en garantissant un coût de déploiement minimal et en maximisant la durée de vie du réseau. Notre objectif est de résoudre les problèmes de déploiement et d'ordonnancement tout en tenant compte des caractéristiques spécifiques du phénomène de la pollution de l’air. Nous proposons pour chaque cas d'application une approche efficace pour le déploiement de noeuds capteurs et puits. Nous proposons également une approche d’ordonnancement adaptée au cas de la correction de modèles physiques. Nos approches d'optimisation prennent en compte la nature physique de la pollution atmosphérique et intègrent les données réelles fournies par les plateformes existantes de suivi de la qualité de l’air. Dans chacune de nos approches d’optimisation, nous utilisons la programmation linéaire en nombres entiers pour concevoir des modèles d’optimisation adaptés à la résolution de petites et moyennes instances. Pour traiter les grandes instances, nous proposons des heuristiques en utilisant des techniques de relaxation linéaire. Outre nos travaux théoriques sur le suivi de la pollution atmosphérique, nous avons conçu et déployé dans la ville de Lyon un réseau de capteurs de pollution économe en énergie. Sur la base des caractéristiques de notre système et des jeux de données de la pollution atmosphérique, nous avons évalué l’efficacité de nos approches de déploiement et d’ordonnancement. Nous présentons et discutons dans cette thèse les résultats d'évaluation de performances ainsi que des lignes directrices pour la conception de systèmes de suivi de la pollution de l’air. Parmi nos principales conclusions, nous soulignons le fait que la taille optimale du réseau de capteurs dépend du degré de variation des concentrations de pollution dans la région de déploiement
Wireless sensor networks (WSN) are widely used in environmental applications where the aim is to sense a physical phenomenon such as temperature, humidity, air pollution, etc. In this context of application, the use of WSN allows to understand the variations of the phenomenon over the monitoring region and therefore be able to take adequate decisions regarding the impact of the phenomenon. Due to the limitations of its traditional costly monitoring methods in addition to its high spatial and temporal variability, air pollution is considered as one of the main physical phenomena that still need to be studied and characterized. In this thesis, we consider three main applications regarding the use of WSN for air pollution monitoring: 1) the construction of real time air quality maps using sensor measurements; 2) the detection of pollution threshold crossings; and 3) the correction of physical models that simulate the pollution dispersion phenomenon. All these applications need careful deployment and scheduling of sensors in order to get a better knowledge of air pollution while ensuring a minimal deployment cost and a maximal lifetime of the deployed sensor network. Our aim is to tackle the problems of WSN deployment and scheduling while considering the specific characteristics of the air pollution phenomenon. We propose for each application case a new efficient approach for the deployment of sensor and sink nodes. We also propose a WSN scheduling approach that is adapted to the case of physical models’ correction. Our optimization approaches take into account the physical nature of air pollution dispersion and incorporate real data provided by the existing pollution sensing platforms. As part of each approach, we use integer linear programming to derive optimization models that are well adapted to solving small and medium instances. To deal with large instances, we propose heuristic algorithms while using linear relaxation techniques. Besides our theoretical works on air pollution monitoring, we design from scratch and deploy in the Lyon city a cost-effective energy-efficient air pollution sensor network. Based on the characteristics of our monitoring system in addition to real world air pollution datasets, we evaluate the effectiveness of our deployment and scheduling approaches and provide engineering insights for the design of WSN-based air pollution monitoring systems. Among our conclusions, we highlight the fact that the size of the optimal sensor network depends on the degree of the variations of pollution concentrations within the monitoring region
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Speer, Ngoc Anh Phan. "Design and Analysis of Adaptive Fault Tolerant QoS Control Algorithms for Query Processing in Wireless Sensor Networks." Diss., Virginia Tech, 2008. http://hdl.handle.net/10919/27221.

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Data sensing and retrieval in WSNs have a great applicability in military, environmental, medical, home and commercial applications. In query-based WSNs, a user would issue a query with QoS requirements in terms of reliability and timeliness, and expect a correct response to be returned within the deadline. Satisfying these QoS requirements requires that fault tolerance mechanisms through redundancy be used, which may cause the energy of the system to deplete quickly. This dissertation presents the design and validation of adaptive fault tolerant QoS control algorithms with the objective to achieve the desired quality of service (QoS) requirements and maximize the system lifetime in query-based WSNs. We analyze the effect of redundancy on the mean time to failure (MTTF) of query-based cluster-structured WSNs and show that an optimal redundancy level exists such that the MTTF of the system is maximized. We develop a hop-by-hop data delivery (HHDD) mechanism and an Adaptive Fault Tolerant Quality of Service Control (AFTQC) algorithm in which we utilize "source" and "path" redundancy with the goal to satisfy application QoS requirements while maximizing the lifetime of WSNs. To deal with network dynamics, we investigate proactive and reactive methods to dynamically collect channel and delay conditions to determine the optimal redundancy level at runtime. AFTQC can adapt to network dynamics that cause changes to the node density, residual energy, sensor failure probability, and radio range due to energy consumption, node failures, and change of node connectivity. Further, AFTQC can deal with software faults, concurrent query processing with distinct QoS requirements, and data aggregation. We compare our design with a baseline design without redundancy based on acknowledgement for data transmission and geographical routing for relaying packets to demonstrate the feasibility. We validate analytical results with extensive simulation studies. When given QoS requirements of queries in terms of reliability and timeliness, our AFTQC design allows optimal â sourceâ and â pathâ redundancies to be identified and applied dynamically in response to network dynamics such that not only query QoS requirements are satisfied, as long as adequate resources are available, but also the lifetime of the system is prolonged.
Ph. D.
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Dargie, Waltenegus. "Impact of Random Deployment on Operation and Data Quality of Sensor Networks." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2010. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-32911.

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Several applications have been proposed for wireless sensor networks, including habitat monitoring, structural health monitoring, pipeline monitoring, and precision agriculture. Among the desirable features of wireless sensor networks, one is the ease of deployment. Since the nodes are capable of self-organization, they can be placed easily in areas that are otherwise inaccessible to or impractical for other types of sensing systems. In fact, some have proposed the deployment of wireless sensor networks by dropping nodes from a plane, delivering them in an artillery shell, or launching them via a catapult from onboard a ship. There are also reports of actual aerial deployments, for example the one carried out using an unmanned aerial vehicle (UAV) at a Marine Corps combat centre in California -- the nodes were able to establish a time-synchronized, multi-hop communication network for tracking vehicles that passed along a dirt road. While this has a practical relevance for some civil applications (such as rescue operations), a more realistic deployment involves the careful planning and placement of sensors. Even then, nodes may not be placed optimally to ensure that the network is fully connected and high-quality data pertaining to the phenomena being monitored can be extracted from the network. This work aims to address the problem of random deployment through two complementary approaches: The first approach aims to address the problem of random deployment from a communication perspective. It begins by establishing a comprehensive mathematical model to quantify the energy cost of various concerns of a fully operational wireless sensor network. Based on the analytic model, an energy-efficient topology control protocol is developed. The protocol sets eligibility metric to establish and maintain a multi-hop communication path and to ensure that all nodes exhaust their energy in a uniform manner. The second approach focuses on addressing the problem of imperfect sensing from a signal processing perspective. It investigates the impact of deployment errors (calibration, placement, and orientation errors) on the quality of the sensed data and attempts to identify robust and error-agnostic features. If random placement is unavoidable and dense deployment cannot be supported, robust and error-agnostic features enable one to recognize interesting events from erroneous or imperfect data.
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Stucki, Eric Thomas. "Medium Access Control and Networking Protocols for the Intra-Body Network." Diss., CLICK HERE for online access, 2006. http://contentdm.lib.byu.edu/ETD/image/etd1182.pdf.

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Souil, Marion. "Contribution à la qualité de service dans les réseaux de capteurs sans fil." Phd thesis, Université de Technologie de Compiègne, 2013. http://tel.archives-ouvertes.fr/tel-00919777.

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L'apparition récente de petits capteurs peu couteux fonctionnant sur batteries, capables de traiter les données acquises et de les transmettre par ondes radio ont le potentiel de révolutionner les applications de surveillance traditionnelles. Les réseaux sans fils composés de nœuds capteurs autonomes proches de la cible à surveiller permettent des tâches de surveillance précises allant du contrôle de la température dans des bâtiments jusqu'a la détection de feux de forêt. Récemment, de nouvelles applications de réseaux de capteurs sans fil telles que des applications multimédia ou dans le domaine de la santé ont émergé. Les réseaux sous-jacents déployés pour ces applications sont souvent compos'es de nœuds hétérogènes comportant différents capteurs et doivent fournir un niveau de service conforme aux exigences des différents types de trafic en s'adaptant à la charge variable. Cependant, concevoir des protocoles efficaces adaptés à ces applications tout en s'accommodant des ressources limitées des réseaux de capteurs est une tâche difficile. Dans cette thèse, nous nous focalisons sur le support de la qualité de service au niveau de la couche MAC, car cette couche conditionne et détermine largement les performances du réseau étant donné qu'elle est responsable de l'organisation de l'accès au canal. Dans un premier temps, nous étudions les contraintes spécifiques des applications ayant des exigences fortes ainsi que des applications hétérogènes et nous examinons les travaux proposés dans la littérature. Etant donné l'inadéquation des solutions existantes en présence d'un trafic important, nous proposons AMPH, un protocole MAC adaptatif avec qualité de service pour les réseaux de capteurs sans fil hétérogènes. Notre solution consiste en une méthode d'accès au canal hybride basée sur le multiplexage temporel, dans laquelle tous les nœuds peuvent accéder au canal à chaque division de temps en utilisant un nouveau mécanisme de compétition qui favorise le trafic prioritaire. Grâce à ces techniques, AMPH utilise efficacement le canal quelque soit la charge de trafic et assure une latence faible au trafic temps réel. Nous vérifions les performances d'AMPH à l'aide de simulations et d'un modèle mathématique.
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Books on the topic "Wireless sensor networks Quality control"

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Consorzio Nazionale Interuniversitario per le Telecomunicazioni, IEEE South and Central Italy Section, IEEE Communications Society, and Tirrenia International Workshop on Digital Communications (18th : 2007 : University of Padova, Italy), eds. Wireless Communications: 2007 CNIT Thyrrenian Symposium. New York: Springer Science + Business Media, 2008.

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Can, Vuran Mehmet, ed. Wireless sensor networks. Chichester, West Sussex, U.K: Wiley, 2010.

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1979-, Gschwender Adam, ed. ZigBee wireless sensor and control network. Upper Saddle River, NJ: Prentice Hall, 2010.

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Elahi, Ata. ZigBee wireless sensor and control network. Upper Saddle River, NJ: Prentice Hall, 2010.

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Elahi, Ata. ZigBee wireless sensor and control network. Upper Saddle River, NJ: Prentice Hall, 2010.

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Santi, Paolo. Topology Control in Wireless Ad Hoc and Sensor Networks. New York: John Wiley & Sons, Ltd., 2005.

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Santi, Paolo. Topology Control in Wireless Ad Hoc and Sensor Networks. Chichester, UK: John Wiley & Sons, Ltd, 2005. http://dx.doi.org/10.1002/0470094559.

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Topology control in wireless ad hoc and sensor networks. Chichester, UK: John Wiley & Sons, 2004.

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Liu, Jilei. Topology control in wireless sensor and mobile ad hoc networks. Ottawa: National Library of Canada, 2002.

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Al-Kashoash, Hayder. Congestion Control for 6LoWPAN Wireless Sensor Networks: Toward the Internet of Things. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-17732-4.

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Book chapters on the topic "Wireless sensor networks Quality control"

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Seelam, Koteswararao, Kathala Krishna Chaitanya Rao, Komal Vyas, and Thanuku Aishwarya. "A Novel Contention Resolution Protocol for Wireless Sensor Networks." In ICICCT 2019 – System Reliability, Quality Control, Safety, Maintenance and Management, 449–56. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8461-5_50.

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Spyrou, Evangelos D., and Dimitrios K. Mitrakos. "Optimising Wireless Sensor Network Link Quality Through Power Control with Non-convex Utilities Using Game Theory." In Ad-hoc, Mobile, and Wireless Networks, 255–61. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67910-5_21.

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Anil Kumar, Kakelli, Addepalli V. N. Krishna, and K. Shahu Chatrapati. "Congestion Control in Heterogeneous Wireless Sensor Networks for High-Quality Data Transmission." In Proceedings of the International Congress on Information and Communication Technology, 429–37. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0755-2_46.

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Dudin, Alexander, Chesoong Kim, and Sergey Dudin. "Optimal Control by the Queue with Rate and Quality of Service Depending on the Amount of Harvested Energy as a Model of the Node of Wireless Sensor Network." In Distributed Computer and Communication Networks, 165–78. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-36614-8_13.

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Priyadarshini, Sushree Bibhuprada B. "Concentric Quadrivial Scalar Premier Selection Scheme Based on Sensing Region Segregation (CQSPS-SRS): An Innovative Marching Towards Optimum Camera Actuation and Enhanced Event Coverage in Wireless Multimedia Sensor Networks." In ICICCT 2019 – System Reliability, Quality Control, Safety, Maintenance and Management, 494–501. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8461-5_56.

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Selmic, Rastko R., Vir V. Phoha, and Abdul Serwadda. "Quality of Service." In Wireless Sensor Networks, 179–96. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46769-6_7.

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Chai, Senchun, Zhaoyang Wang, Baihai Zhang, Lingguo Cui, and Runqi Chai. "Coverage Control in Wireless Sensor Networks." In Wireless Networks, 143–87. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5757-6_4.

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Challen, Geoffrey, and Matt Welsh. "Volcano Monitoring: Addressing Data Quality Through Iterative Deployment." In Wireless Sensor Networks, 71–113. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-5834-1_4.

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Huseth, Steve, and Soumitri Kolavennu. "Localization in Wireless Sensor Networks." In Wireless Networking Based Control, 153–74. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-7393-1_7.

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Mester, Gyula, Istvan Matijevics, Tamas Szepe, and Janos Simon. "Wireless Sensor-Based Robot Control." In Computer Communications and Networks, 275–77. London: Springer London, 2010. http://dx.doi.org/10.1007/978-1-84996-510-1_16.

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Conference papers on the topic "Wireless sensor networks Quality control"

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Kaur, Harminder, and Sharvan Kumar Pahuja. "MAC Protocols for Wireless Body Sensor Network." In International Conference on Women Researchers in Electronics and Computing. AIJR Publisher, 2021. http://dx.doi.org/10.21467/proceedings.114.33.

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Wireless Body Area Networks, also known as the Wireless Body Sensor Networks, provides the monitoring of the health parameters in remote areas and where the medical facility is not available. Wireless Body Sensor Networks contains the body or placement of the sensors on body for measuring the medical and non-medical parameters. These networks share the wireless medium for the transmission of the data from one place to another. So the design of Medium Access Control is a challenging task for the WBSNs due to wireless media for less energy consumption and mobility. Various MAC protocols are designed to provide less energy consumption and improve the network lifetime. This paper presents the study of these existing MAC layer protocols based on different QoS parameters that define the network quality.
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Sundararajan, V., Andrew Redfern, Michael Schneider, Paul Wright, and James Evans. "Wireless Sensor Networks for Machinery Monitoring." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-82224.

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Wireless sensor networks (WSNs) are currently been actively investigated in the research community on account of their unprecedented spatial density of sensors, local computational plus storage capacity, and potential for distributed and fault-tolerant monitoring. Today, they are mainly deployed for environmental monitoring - e.g. for “smart building” control, water quality monitoring, and botanical studies. In the future, it is clear they have a huge potential for industrial applications such as machinery monitoring, shop instrumentation, and process control. Wireless sensor nodes can be mounted on various parts of machinery and plant to promote early fault detection and analysis. Their small size and autonomy enables their placement in locations that are usually difficult to access. In addition, it is also possible, with minimal changes to the machine configuration, to deploy sensors on the machinery after it has been installed. The sensor nodes cannot only monitor their own output but also collaborate with neighboring nodes to determine the health of the overall machines and provide early warnings of potential failure. We study, in this paper, the benefits of using wireless sensor networks in machine tools and plant equipment. We discuss the uses of these networks and the issues that must be addressed in order for these implementations to be successful. We also present two case studies for machinery and machine too monitoring.
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Onur, E., C. Ersoy, and H. Delic. "On the quality of deployment in wireless sensor networks." In 2005 Proceedings of the 8th International Conference on Telecommunications. IEEE, 2005. http://dx.doi.org/10.1109/contel.2005.185950.

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Xu, Hongli, Liusheng Huang, Junmin Wu, Gang Wang, and Wang Liu. "Delay-Constraint Topology Control in Wireless Sensor Networks Format." In 5th International ICST Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness. ICST, 2008. http://dx.doi.org/10.4108/icst.qshine2008.3815.

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Biao Song, Wendong Xiao, and Zhaohui Zhang. "Quality of estimation guaranteed energy efficient sensor selection in wireless sensor networks." In 2014 11th World Congress on Intelligent Control and Automation (WCICA). IEEE, 2014. http://dx.doi.org/10.1109/wcica.2014.7052962.

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Prathiba, B., K. Jaya Sankar, and V. Sumalatha. "Enhancing the data quality in wireless sensor networks — A review." In 2016 International Conference on Automatic Control and Dynamic Optimization Techniques (ICACDOT). IEEE, 2016. http://dx.doi.org/10.1109/icacdot.2016.7877626.

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Lei Chen, Boleslaw K. Szymanski, and Joel W. Branch. "Quality-driven congestion control for target tracking in wireless sensor networks." In 2008 5th IEEE International Conference on Mobile Ad Hoc and Sensor Systems (MASS). IEEE, 2008. http://dx.doi.org/10.1109/mahss.2008.4660115.

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He, Liang, Boyang Yu, and Jingdong Xu. "LQATC: Link Quality Assured Topology Control Algorithm in Sensor Networks." In 2010 6th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). IEEE, 2010. http://dx.doi.org/10.1109/wicom.2010.5601387.

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Chen, Ing-Ray, Anh Phan Speer, and Mohamed Eltoweissy. "Dynamic adaptive redundancy for quality-of-service control in wireless sensor networks." In Distributed Processing (IPDPS). IEEE, 2009. http://dx.doi.org/10.1109/ipdps.2009.5161181.

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Huang, Pei, Chen Wang, Li Xiao, and Hongyang Chen. "RC-MAC: A receiver-centric medium access control protocol for wireless sensor networks." In 2010 IEEE 18th International Workshop on Quality of Service (IWQoS). IEEE, 2010. http://dx.doi.org/10.1109/iwqos.2010.5542740.

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Reports on the topic "Wireless sensor networks Quality control"

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Aman Behal, Sunil Kumar, and Goodarz Ahmadi. Intelligent Control via Wireless Sensor Networks for Advanced Coal Combustion Systems. Office of Scientific and Technical Information (OSTI), August 2007. http://dx.doi.org/10.2172/934579.

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Hansen, Jeffrey, Scott Hissam, B. C. Meyers, Ed Morris, Daniel Plakosh, Soumya Simanta, and Lutz Wrage. Adaptive Flow Control for Enabling Quality of Service in Tactical Ad Hoc Wireless Networks. Fort Belvoir, VA: Defense Technical Information Center, December 2010. http://dx.doi.org/10.21236/ada536719.

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