Journal articles on the topic 'Distributed sensors networks'
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Bao, Xi Rong, Yue Huang, and Shi Zhang. "A Distributed Motion Algorithm for Mobile Sensor in Hybrid Wireless Sensor Networks." Applied Mechanics and Materials 719-720 (January 2015): 812–17. http://dx.doi.org/10.4028/www.scientific.net/amm.719-720.812.
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Constructing a hybrid wireless sensor networks comprising a mix of static sensors and mobile sensors can achieve a balance between improving coverage and reducing the cost of the network. In order to achieve high network coverage, mobile sensor move from a small to a big size of coverage hole in the hybrid wireless sensor networks. Due to the energy of the mobile sensor is limited, how to reduce the moving distance of the mobile sensor and reduce the energy consumption in the process of moving is a very important issue. This paper proposes a distributed minimum cost matching algorithm (DMMA) to redeploy mobile sensor, which can make the level of network coverage to meet the requirement of the environment, while effectively reducing the number of sensors. In our method, static sensors detect coverage hole by Voronoi diagrams, coverage holing sensors and mobile sensors by using DMMA to excellently heal the large coverage holes. Simulation results show that our method can effectively improve the coverage rate of the WSNs, while save the energy of mobile sensors.
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Patan, Maciej. "Distributed scheduling of sensor networks for identification of spatio-temporal processes." International Journal of Applied Mathematics and Computer Science 22, no. 2 (June 1, 2012): 299–311. http://dx.doi.org/10.2478/v10006-012-0022-9.
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Distributed scheduling of sensor networks for identification of spatio-temporal processesAn approach to determine a scheduling policy for a sensor network monitoring some spatial domain in order to identify unknown parameters of a distributed system is discussed. Given a finite number of possible sites at which sensors are located, the activation schedule for scanning sensors is provided so as to maximize a criterion defined on the Fisher information matrix associated with the estimated parameters. The related combinatorial problem is relaxed through operating on the density of sensors in lieu of individual sensor positions. Then, based on the adaptation of pairwise communication algorithms and the idea of running consensus, a numerical scheme is developed which distributes the computational burden between the network nodes. As a result, a simple exchange algorithm is outlined to solve the design problem in a decentralized fashion.
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Singh, Mitali, and Viktor K. Prasanna. "A HIERARCHICAL MODEL FOR DISTRIBUTED COLLABORATIVE COMPUTATION IN WIRELESS SENSOR NETWORKS." International Journal of Foundations of Computer Science 15, no. 03 (June 2004): 485–506. http://dx.doi.org/10.1142/s012905410400256x.
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In-network collaborative computation is essential for implementation of a large number of sensor applications. We approach the problem of computation in sensor networks from a parallel and distributed system's perspective. We define COSMOS, the Cluster-based, heterOgeneouSMOdel for Sensor networks. The model abstracts the key features of the class of cluster-based sensor applications. It assumes a hierarchical network architecture comprising of a large number of low cost sensors with limited computation capability, and fewer number of powerful clusterheads, uniformly distributed in a two dimensional terrain. The sensors are organized into single hop clusters, each managed by a distinct clusterhead. The clusterheads are organized in a mesh-like topology. All sensors in a cluster are time synchronized, whereas the clusterheads communicate asynchronously. The sensors are assumed to have multiple power states and a wakeup mechanism to facilitate power management. To illustrate algorithm design using our model, we discuss implementation of algorithms for sorting and summing in sensor networks.
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Veeravalli, Venugopal V., and Pramod K. Varshney. "Distributed inference in wireless sensor networks." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 370, no. 1958 (January 13, 2012): 100–117. http://dx.doi.org/10.1098/rsta.2011.0194.
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Statistical inference is a mature research area, but distributed inference problems that arise in the context of modern wireless sensor networks (WSNs) have new and unique features that have revitalized research in this area in recent years. The goal of this paper is to introduce the readers to these novel features and to summarize recent research developments in this area. In particular, results on distributed detection, parameter estimation and tracking in WSNs will be discussed, with a special emphasis on solutions to these inference problems that take into account the communication network connecting the sensors and the resource constraints at the sensors.
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Zareei, Mahdi, Cesar Vargas-Rosales, Mohammad Hossein Anisi, Leila Musavian, Rafaela Villalpando-Hernandez, Shidrokh Goudarzi, and Ehab Mahmoud Mohamed. "Enhancing the Performance of Energy Harvesting Sensor Networks for Environmental Monitoring Applications." Energies 12, no. 14 (July 20, 2019): 2794. http://dx.doi.org/10.3390/en12142794.
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Fast development in hardware miniaturization and massive production of sensors make them cost efficient and vastly available to be used in various applications in our daily life more specially in environment monitoring applications. However, energy consumption is still one of the barriers slowing down the development of several applications. Slow development in battery technology, makes energy harvesting (EH) as a prime candidate to eliminate the sensor’s energy barrier. EH sensors can be the solution to enabling future applications that would be extremely costly using conventional battery-powered sensors. In this paper, we analyze the performance improvement and evaluation of EH sensors in various situations. A network model is developed to allow us to examine different scenarios. We borrow a clustering concept, as a proven method to improve energy efficiency in conventional sensor network and brought it to EH sensor networks to study its effect on the performance of the network in different scenarios. Moreover, a dynamic and distributed transmission power management for sensors is proposed and evaluated in both networks, with and without clustering, to study the effect of power balancing on the network end-to-end performance. The simulation results indicate that, by using clustering and transmission power adjustment, the power consumption can be distributed in the network more efficiently, which result in improving the network performance in terms of a packet delivery ratio by 20%, 10% higher network lifetime by having more alive nodes and also achieving lower delay by reducing the hop-count.
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Ramezani, Tayebeh, and Tahereh Ramezani. "A Distributed Method to Reconstruct Connection in Wireless Sensor Networks by Using Genetic Algorithm." Modern Applied Science 10, no. 6 (April 10, 2016): 50. http://dx.doi.org/10.5539/mas.v10n6p50.
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In recent years most of the research in the field of sensor networks is allocated to the wireless sensor and actor networks due to their complicacy and vastness of research area. This type of network is a group of sensors and actors wirelessly linked to each other. Sensors gather information of physical world while actors take appropriate decisions on the basis of gathered information and then perform proper actions upon the environment. In wireless sensor and actor networks, it is very important to maintain the connection between actors. Failure of one or more actors can break up the network into separated parts and this failure acts as a barrier to the network to perform its duties. The purpose of the present paper was to provide a genetic algorithm in wireless sensor and actor networks, to improve evaluation and to maintain the connection between actors’ networks. In order to evaluate strong points and weaknesses of the recommended approach, the OMNet++ simulation was used and the outcomes of the simulation were indicative of the recommended approach’s validity.
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Shin, Huicheol, Yongjae Kim, Seungjae Baek, and Yujae Song. "Distributed Learning for Dynamic Channel Access in Underwater Sensor Networks." Entropy 22, no. 9 (September 7, 2020): 992. http://dx.doi.org/10.3390/e22090992.
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In this study, the problem of dynamic channel access in distributed underwater acoustic sensor networks (UASNs) is considered. First, we formulate the dynamic channel access problem in UASNs as a multi-agent Markov decision process, wherein each underwater sensor is considered an agent whose objective is to maximize the total network throughput without coordinating with or exchanging messages among different underwater sensors. We then propose a distributed deep Q-learning-based algorithm that enables each underwater sensor to learn not only the behaviors (i.e., actions) of other sensors, but also the physical features (e.g., channel error probability) of its available acoustic channels, in order to maximize the network throughput. We conduct extensive numerical evaluations and verify that the performance of the proposed algorithm is similar to or even better than the performance of baseline algorithms, even when implemented in a distributed manner.
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Aerts, Sam, Günter Vermeeren, Matthias Van den Bossche, Reza Aminzadeh, Leen Verloock, Arno Thielens, Philip Leroux, et al. "Lessons Learned from a Distributed RF-EMF Sensor Network." Sensors 22, no. 5 (February 22, 2022): 1715. http://dx.doi.org/10.3390/s22051715.
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In an increasingly wireless world, spatiotemporal monitoring of the exposure to environmental radiofrequency (RF) electromagnetic fields (EMF) is crucial to appease public uncertainty and anxiety about RF-EMF. However, although the advent of smart city infrastructures allows for dense networks of distributed sensors, the costs of accurate RF sensors remain high, and dedicated RF monitoring networks remain rare. This paper describes a comprehensive study comprising the design of a low-cost RF-EMF sensor node capable of monitoring four frequency bands used by wireless telecommunications with an unparalleled temporal resolution, its application in a small-scale distributed sensor network consisting of both fixed (on building façades) and mobile sensor nodes (on postal vans), and the subsequent analysis of over a year of data between January 2019 and May 2020, during which slightly less than 10 million samples were collected. From the fixed nodes’ results, the potential errors were determined that are induced when sampling at lower speeds (e.g., one sample per 15 min) and measuring for shorter periods of time (e.g., a few weeks), as well as an adequate resolution (30 min) for diurnal and weekly temporal profiles which sufficiently preserves short-term variations. Furthermore, based on the correlation between the sensors, an adequate density of 100 sensor nodes per km2 was deduced for future networks. Finally, the mobile sensor nodes were used to identify potential RF-EMF exposure hotspots in a previously unattainable area of more than 60 km2. In summary, through the analysis of a small number of RF-EMF sensor nodes (both fixed and mobile) in an urban area, this study offers invaluable insights applicable to future designs and deployments of distributed RF-EMF sensor networks.
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Zhao, Bingya, and Ya Zhang. "Transmission rate conditions for distributed filtering in sensor networks against eavesdropper." Transactions of the Institute of Measurement and Control 43, no. 12 (April 25, 2021): 2757–67. http://dx.doi.org/10.1177/01423312211005607.
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This paper studies the distributed secure estimation problem of sensor networks (SNs) in the presence of eavesdroppers. In an SN, sensors communicate with each other through digital communication channels, and the eavesdropper overhears the messages transmitted by the sensors over fading wiretap channels. The increasing transmission rate plays a positive role in the detectability of the network while playing a negative role in the secrecy. Two types of SNs under two cooperative filtering algorithms are considered. For networks with collectively observable nodes and the Kalman filtering algorithm, by studying the topological entropy of sensing measurements, a sufficient condition of distributed detectability and secrecy, under which there exists a code–decode strategy such that the sensors’ estimation errors are bounded while the eavesdropper’s error grows unbounded, is given. For collectively observable SNs under the consensus Kalman filtering algorithm, by studying the topological entropy of the sensors’ covariance matrices, a necessary condition of distributed detectability and secrecy is provided. A simulation example is given to illustrate the results.
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WANG, BANG. "SENSOR PLACEMENT FOR COMPLETE INFORMATION COVERAGE IN DISTRIBUTED SENSOR NETWORKS." Journal of Circuits, Systems and Computers 17, no. 04 (August 2008): 627–36. http://dx.doi.org/10.1142/s0218126608004575.
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The sensor placement problem for complete information coverage in a distributed sensor network is studied. Sensors are assumed to be placed on the grid points of a grid in the sensor field and complete information coverage is claimed if all the grid points are information covered. This sensor placement problem is formulated as a constrained optimization problem where the objective is to minimize the total cost while guaranteeing certain coverage requirement. We propose a greedy algorithm to solve this problem. Computational results show that the proposed algorithm can efficiently obtain a good quality solution with greatly reduced computation complexity and the number of sensors can be greatly reduced for information coverage.
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Dessart, Nathalie, Hacène Fouchal, and Philippe Hunel. "Distributed diagnosis over wireless sensors networks." Concurrency and Computation: Practice and Experience 22, no. 10 (June 15, 2010): 1240–51. http://dx.doi.org/10.1002/cpe.1583.
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Vino, T., S. S. Sivaraju, R. V. V. Krishna, T. Karthikeyan, Yogesh kumar Sharma, K. G. S. Venkatesan, G. Manikandan, R. Selvameena, and Mebratu Markos. "Multicluster Analysis and Design of Hybrid Wireless Sensor Networks Using Solar Energy." International Journal of Photoenergy 2022 (October 11, 2022): 1–8. http://dx.doi.org/10.1155/2022/1164613.
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A wireless touch network is a distributed, self-organizing network of multiple sensors and actuators in combination with multiple sensors and a radio channel. Also, the security area of such a network can be several meters to several meters. The main difference between wireless sensor networks from traditional computer and telephone networks is the lack of a fixed infrastructure owned by a specific operator or provider. Each user terminal in a touch network is capable of acting as a terminal device only. Despite the long history of sensor networks, the concept of building a sensor network is not finally imposed and expressed in some software and hardware (platform) solutions. In this paper, the design and analysis of multicluster model of the sensor nodes in wireless sensor network with the help of solar energy. This proposed model provides the required energy to transmit the information between two end nodes in different cluster. The communication between the end to end clusters was increased based on this design. The implementation of sensory networks at the current stage depends largely on the specific needs of the industrial problem. The architecture, software, and hardware implementation technology is at an intensive development stage, attracting the attention of developers looking for a technological niche of future makers.
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Liu, Guiyun, Yonggui Liu, Jing Yao, Hongbin Chen, and Dong Tang. "Repeated Game for Distributed Estimation in Autonomous Clustered Wireless Sensor Networks." International Journal of Distributed Sensor Networks 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/806456.
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A commonly encountered problem in wireless sensor networks (WSNs) applications is to reconstruct the state of nature, that is, distributed estimation of a parameter of interest through WSNs’ observations. However, the distributed estimation in autonomous clustered WSNs faces a vital problem of sensors’ selfishness. Each sensor autonomously decides whether or not to transmit its observations to the fusion center (FC) and not be controlled by the fusion center (FC) any more. Thus, to encourage cooperation within selfish sensors, infinitely and finitely repeated games are firstly modeled to depict sensors’ behaviors. Then, the existences of Nash equilibriums for infinitely and finitely repeated games are discussed. Finally, simulation results show that the proposed Nash equilibrium strategies are effective.
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Al-Asadi, Hamid Ali Abed. "A Novel and Enhanced Distributed Clustering Methodology for Large Scale Wireless Sensor Network Fields." Journal of Computational and Theoretical Nanoscience 16, no. 2 (February 1, 2019): 633–38. http://dx.doi.org/10.1166/jctn.2019.7782.
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Wireless sensor network (WSN) is a grid of sensors possessing processor unit and trivial memory unit implanted on them. Trustworthy packet forwarding from nodes to sink seems to be the most substantial purpose of this sensor network. The customary routing algorithms could not be employed at this juncture since the sensor battery power is limited. To provide energy proficiency, sensors are normally grouped as non-overlapping groups. This research work provides a transitory summary on clustering procedures in sensor networks. An energy-efficient distributed clustering approach for impenetrable sensor networks, the Weight based clustering Low Energy Adaptive Clustering Hierarchy (WC-LEACH) is proposed and the outcomes are assessed in contradiction with the prevailing Low Energy Adaptive Clustering Hierarchy (LEACH) and Hybrid Energy Efficient Distributed Clustering (HEED) methodologies. Simulation results obviously display an exceptional enhancement in packet delivery ratio, reduced packet loss, reduced energy consumption, increased throughput and increased lifetime for WSNs.
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Li, Zhu Guo, Bing Wen Wang, and Li Zhu Feng. "EDMC: An Energy-Efficient Distributed Multi-Hop Clustering Approach for Wireless Sensor Networks." Applied Mechanics and Materials 198-199 (September 2012): 1668–71. http://dx.doi.org/10.4028/www.scientific.net/amm.198-199.1668.
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The past few years have witnessed increasing focus on the potential applications of wireless sensor networks. Sensors in these networks are expected to be remotely dispersed in large number and to operate autonomously and unattended. Clustering is a widely used technique that can enhance scalability and decrease energy consumption over sensor networks. We present an energy-efficient distributed multi-hop clustering approach for sensor networks, which combined multi-hop transmission with clustering method, aiming to balance the energy dissipation and prolong the whole network lifetime. Simulations showed that the protocol proposed worked nearly 100% more efficient compared with LEACH and HEED.
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Wang, Jing, In Soo Ahn, Yufeng Lu, Tianyu Yang, and Gennady Staskevich. "A Distributed Least-Squares Algorithm in Wireless Sensor Networks With Unknown and Limited Communications." International Journal of Handheld Computing Research 8, no. 3 (July 2017): 15–36. http://dx.doi.org/10.4018/ijhcr.2017070102.
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In this article, the authors propose a new distributed least-squares algorithm to address the sensor fusion problem in using wireless sensor networks (WSN) to monitor the behaviors of large-scale multiagent systems. Under a mild assumption on network observability, that is, each sensor can take the measurements of a limited number of agents but the complete multiagent systems are covered under the union of all sensors in the network, the proposed algorithm achieves the estimation consensus if local information exchange can be performed among sensors. The proposed distributed least-squares algorithm can handle the directed communication network by explicitly estimating the left eigenvector corresponding to the largest eigenvalue of the sensing/communication matrix. The convergence of the proposed algorithm is analyzed, and simulation results are provided to further illustrate its effectiveness.
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Hardman, David, Thomas George Thuruthel, Antonia Georgopoulou, Frank Clemens, and Fumiya Iida. "3D Printable Soft Sensory Fiber Networks for Robust and Complex Tactile Sensing." Micromachines 13, no. 9 (September 17, 2022): 1540. http://dx.doi.org/10.3390/mi13091540.
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The human tactile system is composed of multi-functional mechanoreceptors distributed in an optimized manner. Having the ability to design and optimize multi-modal soft sensory systems can further enhance the capabilities of current soft robotic systems. This work presents a complete framework for the fabrication of soft sensory fiber networks for contact localization, using pellet-based 3D printing of piezoresistive elastomers to manufacture flexible sensory networks with precise and repeatable performances. Given a desirable soft sensor property, our methodology can design and fabricate optimized sensor morphologies without human intervention. Extensive simulation and experimental studies are performed on two printed networks, comparing a baseline network to one optimized via an existing information theory based approach. Machine learning is used for contact localization based on the sensor responses. The sensor responses match simulations with tunable performances and good localization accuracy, even in the presence of damage and nonlinear material properties. The potential of the networks to function as capacitive sensors is also demonstrated.
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Jia, Jie, Guiyuan Zhang, Xingwei Wang, and Jian Chen. "On Distributed Localization for Road Sensor Networks: A Game Theoretic Approach." Mathematical Problems in Engineering 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/640391.
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Road sensor network is an important part of vehicle networks system and is critical for many intelligent automobile scenarios, such as vehicle safety monitoring and transportation efficiency supporting. Localization of sensors is an active and crucial issue to most applications of road sensor network. Generally, given some anchor nodes’ positions and certain pairwise distance measurements, estimating the positions of all nonanchor nodes embodies a nonconvex optimization problem. However, due to the small number of anchor nodes and low sensor node connectivity degree in road sensor networks, the existing localization solutions are ineffective. In order to tackle this problem, a novel distributed localization method based on game theory for road sensor networks is proposed in this paper. Formally, we demonstrate that our proposed localization game is a potential game. Furthermore, we present several techniques to accelerate the convergence to the optimal solution. Simulation results demonstrate the effectiveness of our proposed algorithm.
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Ransom, Elliot, Xiyuan Chen, and Fu-Kuo Chang. "Design of a Robust Tool for Deploying Large-Area Stretchable Sensor Networks from Microscale to Macroscale." Sensors 22, no. 13 (June 27, 2022): 4856. http://dx.doi.org/10.3390/s22134856.
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An investigation was conducted to develop an effective automated tool to deploy micro-fabricated stretchable networks of distributed sensors onto the surface of large structures at macroscale to create “smart” structures with embedded distributed sensor networks. Integrating a large network of distributed sensors with structures has been a major challenge in the design of so-called smart structures or devices for cyber-physical applications where a large amount of usage data from structures or devices can be generated for artificial intelligence applications. Indeed, many “island-and-serpentine”-type distributed sensor networks, while promising, remain difficult to deploy. This study aims to enable such networks to be deployed in a safe, automated, and efficient way. To this end, a scissor-hinge controlled system was proposed as the basis for a deployment mechanism for such stretchable sensor networks (SSNs). A model based on a kinematic scissor-hinge mechanism was developed to simulate and design the proposed system to automatically stretch a micro-scaled square network with uniformly distributed sensor nodes. A prototype of an automatic scissor-hinge stretchable tool was constructed during the study with an array of four scissor-hinge mechanisms, each belt-driven by a single stepper motor. Two micro-fabricated SSNs from a 100 mm wafer were fabricated at the Stanford Nanofabrication Facility for this deployment study. The networks were designed to be able to cover an area 100 times their manufacturing size (from a 100 mm diameter wafer to a 1 m2 active area) once stretched. It was demonstrated that the proposed deployment tool could place sensor nodes in prescribed locations efficiently within a drastically shorter time than in current labor-intensive manual deployment methods.
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Chaczko, Zenon, Christopher Chiu, Shahrzad Aslanzadeh, and Toby Dune. "Sensor-Actor Network Solution for Scalable Ad-hoc Sensor Networks." International Journal of Electronics and Telecommunications 58, no. 1 (March 1, 2012): 55–62. http://dx.doi.org/10.2478/v10177-012-0008-4.
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Sensor-Actor Network Solution for Scalable Ad-hoc Sensor NetworksArchitects of ad-hoc wireless Sensor-Actor Networks (SANETS) face various problems and challenges. The main limitations relate to aspects such as the number of sensor nodes involved, low bandwidth, management of resources and issues related to energy management. In order for these networks to be functionally proficient, the underlying software system must be able to effectively handle unreliable and dynamic distributed communication, power constraints of wireless devices, failure of hardware devices in hostile environments and the remote allocation of distributed processing tasks throughout the wireless network. The solution must be solved in a highly scalable manner. This paper provides the requirements analysis and presents the design of a software system middleware that provides a scalable solution for ad-hoc sensor network infrastructure made of both stationary and mobile sensors and actuators.
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Saihi, Marwa, Ahmed Zouinkhi, Boumedyen Boussaid, Mohamed Naceur Abdelkarim, and Guillaume Andrieux. "Hidden Gaussian Markov model for distributed fault detection in wireless sensor networks." Transactions of the Institute of Measurement and Control 40, no. 6 (March 15, 2017): 1788–98. http://dx.doi.org/10.1177/0142331217691334.
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Wireless sensor networks are based on a large number of sensor nodes used to measure information like temperature, acceleration, displacement, or pressure. The measurements are used to estimate the state of the monitored system or area. However, the quality of the measurements must be guaranteed to ensure the reliability of the estimated state of the system. Actually, sensors can be used in a hostile environment such as, on a battle field in the presence of fires, floods, earthquakes. In these environments as well as in normal operation, sensors can fail. The failure of sensor nodes can also be caused by other factors like: the failure of a module (such as the sensing module) due to the fabrication process models, loss of battery power and so on. A wireless sensor network must be able to identify faulty nodes. Therefore, we propose a probabilistic approach based on the Hidden Markov Model to identify faulty sensor nodes. Our proposed approach predicts the future state of each node from its actual state, so the fault could be detected before it occurs. We use an aided judgment of neighbour sensor nodes in the network. The algorithm analyses the correlation of the sensors’ data with respect to its neighbourhood. A systematic approach to divide a network on cliques is proposed to fully draw the neighbourhood of each node in the network. After drawing the neighbourhood of each node (cliques), damaged cliques are identified using the Gaussian distribution theorem. Finally, we use the Hidden Markov Model to identify faulty nodes in the identified damaged cliques by calculating the probability of each node to stay in its normal state. Simulation results demonstrate our algorithm is efficient even for a huge wireless sensor network unlike previous approaches.
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Alaerjan, Alaa. "Towards Sustainable Distributed Sensor Networks: An Approach for Addressing Power Limitation Issues in WSNs." Sensors 23, no. 2 (January 14, 2023): 975. http://dx.doi.org/10.3390/s23020975.
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Distributed wireless sensor networks (WSNs) have been implemented in multiple applications. Those networks are intended to support the quality of operations and enhance applications’ productivity and safety. WSNs are constructed of a large amount of sensor nodes that are battery powered. Typically, wireless sensors are deployed in complex terrain which makes battery replacement extremely difficult. Therefore, it is critical to adopt an energy sustainability approach to enhance the lifetime of each sensor node since each node contributes to the lifetime of the entire WSN. In this work, we propose an approach to reduce power consumption in wireless sensors. The approach addresses power reduction in a sensor node at the sensing level, as well as the communication level. First, we propose configuring the microcontroller of the sensor to conserve energy based on the performed tasks. Then, we implement an interface to reduce consumed power by the radio module. Based on the approach, we carried out field experiments and we measure the improvement of power-consumption reduction. The results show that the approach contributes to saving up to 50% of the wasted energy at the sensor node and it improves communication reliability especially when the number of sensors in a network scales.
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Semnani, Samaneh Hosseini, and Otman A. Basir. "Multi-Target Engagement in Complex Mobile Surveillance Sensor Networks." Unmanned Systems 05, no. 01 (January 2017): 31–43. http://dx.doi.org/10.1142/s2301385017500030.
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Efficient use of the network’s resources to collect information about objects (events) in a given volume of interest (VOI) is a key challenge in large-scale sensor networks. Multi-sensor multi-target tracking in surveillance applications is an example where the network’s success in tracking targets, efficiently and effectively, hinges significantly on the network’s ability to allocate the right set of sensors to the right set of targets so as to achieve optimal performance which minimizes the number of uncovered targets. This task can be even more complicated when both the sensors and the targets are mobile. To ensure timely tracking of mobile targets, the surveillance sensor network needs to perform the following tasks in real-time: (i) target-to-sensor allocation; (ii) sensor mobility control and coordination. The computational complexity of these two tasks presents a challenge, particularly in large scale dynamic network applications. This paper proposes a formulation based on the Semi-flocking algorithm and the distributed constraint optimization problem (DCOP). The semi-flocking algorithm performs multi-target motion control and coordination, a DCOP modeling algorithm performs the target engagement task. As will be demonstrated experimentally in the paper, this algorithmic combination provides an effective approach to the multi-sensor/multi-target engagement problem, delivering optimal target coverage as well as maximum sensors utilization.
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Qu, Ming Zhe. "Research on the Applications and Characteristics of the Wireless Sensor Network." Applied Mechanics and Materials 538 (April 2014): 498–501. http://dx.doi.org/10.4028/www.scientific.net/amm.538.498.
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A wireless sensor network (WSN) consists of spatially distributed autonomous sensors to monitor physical or environmental conditions, such as temperature, sound, pressure, etc. and to cooperatively pass their data through the network to a main location. The more modern networks are bi-directional, also enabling control of sensor activity. The development of wireless sensor networks was motivated by military applications such as battlefield surveillance; today such networks are used in many industrial and consumer applications, such as industrial process monitoring and control, machine health monitoring, and so on. The WSN is built of "nodes" – from a few to several hundreds or even thousands, where each node is connected to one (or sometimes several) sensors. Each such sensor network node has typically several parts: a radio transceiver with an internal antenna or connection to an external antenna, a microcontroller, an electronic circuit for interfacing with the sensors and an energy source, usually a battery or an embedded form of energy harvesting.
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Huang, Jiyan, Peng Wang, and Qun Wan. "Collaborative Beamforming for Wireless Sensor Networks with Arbitrary Distributed Sensors." IEEE Communications Letters 16, no. 7 (July 2012): 1118–20. http://dx.doi.org/10.1109/lcomm.2012.050912.120370.
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Ermis, Erhan Baki, and Venkatesh Saligrama. "Distributed Detection in Sensor Networks With Limited Range Multimodal Sensors." IEEE Transactions on Signal Processing 58, no. 2 (February 2010): 843–58. http://dx.doi.org/10.1109/tsp.2009.2033300.
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Bordim, Jacir Luiz, Koji Nakano, and Hong Shen. "Sorting on Single-Channel Wireless Sensor Networks." International Journal of Foundations of Computer Science 14, no. 03 (June 2003): 391–403. http://dx.doi.org/10.1142/s0129054103001807.
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A Wireless Sensor Network (WSN) is a distributed system consisting of a large number of wireless sensing devices and a base station. Due to their compactness and low-cost, sensor networks can be distributed at a fraction of the cost of conventional wired sensors and actuator systems. The physical world generates an unlimited amount of data that can be observed and monitored. Hence, designing protocols to coordinate WSNs with hundreds, or even thousands, of sensors will face many challenges. In this work we focus on the design of protocols that enable the sensor nodes to coordinate among themselves to achieve a larger task. From this standpoint, we present a sorting protocol for wireless sensor networks. We show that in a WSN consisting of n sensor nodes, where each sensor stores an element and has a fixed transmission range r. sorting can be performed in [Formula: see text] time slots when [Formula: see text]. We also reason that future applications of wireless sensor networks are very likely to employ short-range radio communications (i.e., r less than 100 meters). If this is the case, the time complexity of our sorting protocol is optimal.
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Barcelo-Ordinas, Jose M., Pau Ferrer-Cid, Jorge Garcia-Vidal, Anna Ripoll, and Mar Viana. "Distributed Multi-Scale Calibration of Low-Cost Ozone Sensors in Wireless Sensor Networks." Sensors 19, no. 11 (May 31, 2019): 2503. http://dx.doi.org/10.3390/s19112503.
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New advances in sensor technologies and communications in wireless sensor networks have favored the introduction of low-cost sensors for monitoring air quality applications. In this article, we present the results of the European project H2020 CAPTOR, where three testbeds with sensors were deployed to capture tropospheric ozone concentrations. One of the biggest challenges was the calibration of the sensors, as the manufacturer provides them without calibrating. Throughout the paper, we show how short-term calibration using multiple linear regression produces good calibrated data, but instead produces biases in the calculated long-term concentrations. To mitigate the bias, we propose a linear correction based on Kriging estimation of the mean and standard deviation of the long-term ozone concentrations, thus correcting the bias presented by the sensors.
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Movaghati, Sahar, and Masoud Ardakani. "Distributed Binary Quantization of a Noisy Source in Wireless Sensor Networks." Journal of Sensors 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/368643.
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In distributed (decentralized) estimation in wireless sensor networks, an unknown parameter must be estimated from some noisy measurements collected at different sensors. Due to limited communication resources, these measurements are typically quantized before being sent to a fusion center, where an estimation of the unknown parameter is calculated. In the most stringent condition, each measurement is converted to a single bit. In this study, we propose a distributed quantization scheme which is based on single-bit quantized data from each sensor and achieves high estimation accuracy at the fusion centre. We do this by designing some local binary quantizers which define a multithreshold quantization rule for each sensor. These local binary quantizers are initially designed so that together they mimic the functionality of a multilevel quantizer. Later, their design is improved to include some error-correcting capability, which further improves the estimation accuracy from the sensors’ binary data. The distributed quantization formed by such local binary quantizers along with the proper estimator proposed in this work achieves better performance, compared to the existing distributed binary quantization methods, specially when fewer sensors with low measurement noise are available.
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HUANG, CHI-FU, YU-CHEE TSENG, and LI-CHU LO. "THE COVERAGE PROBLEM IN THREE-DIMENSIONAL WIRELESS SENSOR NETWORKS." Journal of Interconnection Networks 08, no. 03 (September 2007): 209–27. http://dx.doi.org/10.1142/s0219265907001990.
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One of the fundamental issues in sensor networks is the coverage problem, which reflect-show well a sensor network is monitored or tracked by sensors. In this paper, we formulate this problem as a decision problem, whose goal is to determine whether every point in the servicearea of the sensor network is covered by at least α sensors, where ff is a given parameter andthe sensing regions of sensors are modeled by balls (not necessarily of the same radius). This problem in a 2D space is solved in [10] with an efficient polynomial-time algorithm (in termsof the number of sensors). In this paper, we show that tackling this problem in a 3D space is still feasible within polynomial time. Further, the proposed solution can be easily translated intoan efficient polynomial-time distributed protocol. We demonstrate an application of the derived result by proposing an energy-conserving scheduling protocol.
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HAENGGI, MARTIN. "DISTRIBUTED SENSOR NETWORKS: A CELLULAR NONLINEAR NETWORK PERSPECTIVE." International Journal of Neural Systems 13, no. 06 (December 2003): 405–14. http://dx.doi.org/10.1142/s0129065703001686.
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Large-scale networks of integrated wireless sensors become increasingly tractable. Advances in hardware technology and engineering design have led to dramatic reductions in size, power consumption, and cost for digital circuitry, and wireless communications. Networking, self-organization, and distributed operation are crucial ingredients to harness the sensing, computing, and computational capabilities of the nodes into a complete system. This article shows that those networks can be considered as cellular nonlinear networks (CNNs), and that their analysis and design may greatly benefit from the rich theoretical results available for CNNs.
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Cota-Ruiz, Juan, Rafael Gonzalez-Landaeta, Jose David Diaz-Roman, Boris Mederos-Madrazo, and Ernesto Sifuentes. "A weighted and distributed algorithm for multi-hop localization." International Journal of Distributed Sensor Networks 15, no. 7 (July 2019): 155014771986041. http://dx.doi.org/10.1177/1550147719860412.
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Multi-hop wireless sensor networks are widely used in many location-dependent applications. Most applications assume the knowledge of geographic location of sensor nodes; however, in practical scenarios, the high accuracy on position estimates of sensor nodes is still a great challenge. In this research, we propose a hop-weighted scheme that can be useful in distance-based distributed multi-hop localization. The hop-weighted localization approach generates spatial locations around position estimates of unknown sensors and computes local functions that minimize distance errors among hop-weighted and static neighboring sensors. The iterative process of each unknown sensor to re-estimate its own location allows a significant reduction of initial position estimates. Simulations demonstrate that this weighted localization approach, when compared with other schemes, can be suitable to be used as a refinement stage to improve localization in both isotropic and anisotropic networks. Also, under rough initial position estimates, the proposed algorithm achieves root mean square error values less than the radio range of unknown sensors, in average, with only a few iterations.
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Shahbazian, Reza, and Seyed Ali Ghorashi. "Localization of Distributed Wireless Sensor Networks using Two Sage SDP Optimization." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 3 (June 1, 2017): 1255. http://dx.doi.org/10.11591/ijece.v7i3.pp1255-1261.
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<span class="fontstyle0">A wireless sensor network (WSN) may comprise a large distributed set of low cost, low power sensing nodes. In many applications, the location of sensors is a necessity to evaluate the sensed data and it is not energy and cost efficient to equip all sensors with global positioning systems such as GPS. In this paper, we focus on the localization of sensors in a WSN by solving an optimization problem. In WSN localization, some sensors (called anchors) are aware of their location. Then, the distance measurements between sensors and anchors locations are used to localize the whole sensors in the network. WSN localization is a non-convex optimization problem, however, relaxation techniques such as semi-definite programming (SDP) are used to relax the optimization. To solve the optimization problem, all constraints should be considered simultaneously and the solution complexity order is O(n2) </span><span class="fontstyle0">where </span><span class="fontstyle2">n </span><span class="fontstyle0">is the number of sensors. The complexity of SDP prevents solving large size problems. Therefore, it would be beneficial to reduce the problem size in large and distributed WSNs. In this paper, we propose a two stage optimization to reduce the solution time, while provide better accuracy compared with original SDP method. We first select some sensors that have the maximum connection with anchors and perform the SDP localization. Then, we select some of these sensors as virtual anchors. By adding the virtual anchors, we add more reference points and decrease the number of constraints. We propose an algorithm to select and add virtual anchors so that the total solution complexity and time decrease considerably, while improving the localization accuracy.</span>
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Zárraga-Rodríguez, Marta, Xabier Insausti, and Jesús Gutiérrez-Gutiérrez. "On the topology design of large wireless sensor networks for distributed consensus with low power consumption." International Journal of Distributed Sensor Networks 15, no. 12 (December 2019): 155014771989674. http://dx.doi.org/10.1177/1550147719896742.
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Sensor-based structural health monitoring systems are commonly used to provide real-time information and detect damage in complex structures. In particular, wireless structural health monitoring systems are of low cost but, since wireless sensors are powered with batteries, a low power consumption is critical. A common approach for wireless structural health monitoring is to use a distributed computation strategy, which is usually based on consensus algorithms. Power consumption in such wireless consensus networks depends on the number of connections of the network. If sensors are randomly connected, there is no control on the power consumption. In this article, we present a novel strategy to connect a large number of wireless sensors for distributed consensus with low power consumption by combining small networks with basic topologies using the Kronecker product.
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Steiner, Steffen, Abdulrahman Dayo Aminu, and Volker Kuehn. "Distributed Quantization for Partially Cooperating Sensors Using the Information Bottleneck Method." Entropy 24, no. 4 (March 22, 2022): 438. http://dx.doi.org/10.3390/e24040438.
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This paper addresses the optimization of distributed compression in a sensor network with partial cooperation among sensors. The widely known Chief Executive Officer (CEO) problem, where each sensor has to compress its measurements locally in order to forward them over capacity limited links to a common receiver is extended by allowing sensors to mutually communicate. This extension comes along with modified statistical dependencies among involved random variables compared to the original CEO problem, such that well-known outer and inner bounds do not hold anymore. Three different inter-sensor communication protocols are investigated. The successive broadcast approach allows each sensor to exploit instantaneous side-information of all previously transmitting sensors. As this leads to dimensionality problems for larger networks, a sequential point-to-point communication scheme is considered forwarding instantaneous side-information to only one successor. Thirdly, a two-phase transmission protocol separates the information exchange between sensors and the communication with the common receiver. Inspired by algorithmic solutions for the original CEO problem, the sensors are optimized in a greedy manner. It turns out that partial communication among sensors improves the performance significantly. In particular, the two-phase transmission can reach the performance of a fully cooperative CEO scenario, where each sensor has access to all measurements and the knowledge about all channel conditions. Moreover, exchanging instantaneous side-information increases the robustness against bad Wyner–Ziv coding strategies, which can lead to significant performance losses in the original CEO problem.
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Havedanloo, Saeed, and Hamid Reza Karimi. "Improving the Performance Metric of Wireless Sensor Networks with Clustering Markov Chain Model and Multilevel Fusion." Mathematical Problems in Engineering 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/783543.
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The paper proposes a performance metric evaluation for a distributed detection wireless sensor network with respect to IEEE 802.15.4 standard. A distributed detection scheme is considered with presence of the fusion node and organized sensors into the clustering and non-clustering networks. Sensors are distributed in clusters uniformly and nonuniformly and network has multilevel fusion centers. Fusion centers act as heads of clusters for decision making based on majority-like received signal strength (RSS) with comparison the optimized value of the common threshold. IEEE 802.15.4 Markov chain model derived the performance metric of proposed network architecture with MAC, PHY cross-layer parameters, and Channel State Information (CSI) specifications while it is including Path-loss, Modulation, Channel coding and Rayleigh fading. Simulation results represent significant enhancement on performance of network in terms of reliability, packet failure, average delay, power consumption, and throughput.
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Li, Wenchao, Yonggui Yuan, Jun Yang, and Libo Yuan. "Review of Optical Fiber Sensor Network Technology Based on White Light Interferometry." Photonic Sensors 11, no. 1 (January 22, 2021): 31–44. http://dx.doi.org/10.1007/s13320-021-0613-x.
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AbstractOptical fiber sensor networks (OFSNs) provide powerful tools for large-scale buildings or long-distance sensing, and they can realize distributed or quasi-distributed measurement of temperature, strain, and other physical quantities. This article provides some optical fiber sensor network technologies based on the white light interference technology. We discuss the key issues in the fiber white light interference network, including the topology structure of white light interferometric fiber sensor network, the node connection components, and evaluation of the maximum number of sensors in the network. A final comment about further development prospects of fiber sensor network is presented.
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Schäfer, Klaus, Kristian Lande, Hans Grimm, Guido Jenniskens, Roel Gijsbers, Volker Ziegler, Marcus Hank, and Matthias Budde. "High-Resolution Assessment of Air Quality in Urban Areas—A Business Model Perspective." Atmosphere 12, no. 5 (May 3, 2021): 595. http://dx.doi.org/10.3390/atmos12050595.
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The increasing availability of low-cost air quality sensors has led to novel sensing approaches. Distributed networks of low-cost sensors, together with data fusion and analytics, have enabled unprecedented, spatiotemporal resolution when observing the urban atmosphere. Several projects have demonstrated the potential of different approaches for high-resolution measurement networks ranging from static, low-cost sensor networks over vehicular and airborne sensing to crowdsourced measurements as well as ranging from a research-based operation to citizen science. Yet, sustaining the operation of such low-cost air quality sensor networks remains challenging because of the lack of regulatory support and the lack of an organizational framework linking these measurements to the official air quality network. This paper discusses the logical inclusion of lower-cost air quality sensors into the existing air quality network via a dynamic field calibration process, the resulting sustainable business models, and how this expansion can be self-funded.
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Zhu, Rongbo. "Efficient Fault-Tolerant Event Query Algorithm in Distributed Wireless Sensor Networks." International Journal of Distributed Sensor Networks 6, no. 1 (January 1, 2010): 593849. http://dx.doi.org/10.1155/2010/593849.
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To overcome the faulty data query problem to improve the accuracy of data query, an efficient fault-tolerant event query algorithm (FTEQ) is proposed, which takes the short-term and long-term spatial and temporal similarities between sensors and environment into considerations. An imprecise and missing data correction algorithm based on Kalman filter is proposed to correct fault sensing data, and a score rank algorithm also is proposed to assign each sensor an appropriate value to reflect the importance of sensors. FTEQ performs self-evaluation and cooperative evaluation schemes with its trustful r neighbor nodes to filter fault data query with the importance of sensor. Simulation results prove that FTEQ performs extremely well in terms of faulty detection rate and data query cost.
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Khezri, Shirin, Karim Faez, and Amjad Osmani. "An Intelligent Sensor Placement Method to Reach a High Coverage in Wireless Sensor Networks." International Journal of Grid and High Performance Computing 3, no. 3 (July 2011): 54–68. http://dx.doi.org/10.4018/jghpc.2011070105.
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Adequate coverage is one of the main problems for Sensor Networks. The effectiveness of distributed wireless sensor networks highly depends on the sensor deployment scheme. Optimizing the sensor deployment provides sufficient sensor coverage and saves cost of sensors for locating in grid points. This article applies the modified binary particle swarm optimization algorithm for solving the sensor placement in distributed sensor networks. PSO is an inherent continuous algorithm, and the discrete PSO is proposed to be adapted to discrete binary space. In the distributed sensor networks, the sensor placement is an NP-complete problem for arbitrary sensor fields. One of the most important issues in the research fields, the proposed algorithms will solve this problem by considering two factors: the complete coverage and the minimum costs. The proposed method on sensors surrounding is examined in different area. The results not only confirm the successes of using the new method in sensor placement, also they show that the new method is more efficiently compared to other methods like Simulated Annealing(SA), PBIL and LAEDA.
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Sujihelen, L., Rajasekhar Boddu, S. Murugaveni, Ms Arnika, Anandakumar Haldorai, Pundru Chandra Shaker Reddy, Suili Feng, and Jiayin Qin. "Node Replication Attack Detection in Distributed Wireless Sensor Networks." Wireless Communications and Mobile Computing 2022 (May 31, 2022): 1–11. http://dx.doi.org/10.1155/2022/7252791.
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Wireless sensor network (WSN) is an emerging technology used in emergency scenarios. There are a number of possible threats to WSNs because they use unsupervised IP addresses. Securing networks with unattended sensors is a real challenge nowadays. Sensor nodes lack power and storage, making them incompatible with normal security checks. It will be vital to make advancements in sensor network architecture and protocol design. There will be more vulnerability to attack if there is a lack of security. Especially, one key attack is node replication which induces the sensor node to acts as an original node, collecting data from the network and sending it to the attacker. In dynamic WSN, detecting an assault is difficult to find replica nodes. Therefore, this paper proposes a Strategic Security System (SSS) to discover replica nodes in static and dynamic distributed WSNs. It is mainly focused on enhancing detection accuracy, time delay, and communication overhead. The present system includes Single Stage Memory Random Walk with Network Division (SSRWND) and a Random-walk-based approach to detect clone attacks (RAWL). The proposed system has less memory and better detection accuracy.
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Al-Jarrah, Mohammad A., and Mohammad M. Al-Ibrahim. "Receiver Diversity for Distributed Detection in Wireless Sensor Networks." International Journal of Wireless Networks and Broadband Technologies 2, no. 1 (January 2012): 1–15. http://dx.doi.org/10.4018/ijwnbt.2012010101.
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In this paper, parallel distributed detection in wireless sensor network (WSN) is considered where the sensors process the observations to make local decisions and send these decisions to a central device called fusion center. Receiver diversity technique is proposed here for the distributed detection system in order to enhance the system reliability by improving the detection performance. The fusion center is assumed to be multiple antennas device in order to imply the idea of receiver diversity. Different combining schemes at the fusion center side are used to reduce the fading effects in the case of receiver diversity. Transmitter diversity is also considered in this paper. Cooperative sensors are assumed in order to obtain Alamouti space time block codes. Optimal and sub-optimal fusion rules are derived for each case study. Simulation results show the performance improvement obtained as compared to the conventional distributed detection system in which no diversity is used.
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Kim, Du Yong, and Moongu Jeon. "Robust Distributed Kalman Filter for Wireless Sensor Networks with Uncertain Communication Channels." Mathematical Problems in Engineering 2012 (2012): 1–12. http://dx.doi.org/10.1155/2012/238597.
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We address a state estimation problem over a large-scale sensor network with uncertain communication channel. Consensus protocol is usually used to adapt a large-scale sensor network. However, when certain parts of communication channels are broken down, the accuracy performance is seriously degraded. Specifically, outliers in the channel or temporal disconnection are avoided via proposed method for the practical implementation of the distributed estimation over large-scale sensor networks. We handle this practical challenge by using adaptive channel status estimator and robust L1-norm Kalman filter in design of the processor of the individual sensor node. Then, they are incorporated into the consensus algorithm in order to achieve the robust distributed state estimation. The robust property of the proposed algorithm enables the sensor network to selectively weight sensors of normal conditions so that the filter can be practically useful.
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Song, Cheng, Lu Liu, and Gang Feng. "Coverage Control for Mobile Sensor Networks with Input Saturation." Unmanned Systems 04, no. 01 (January 2016): 15–21. http://dx.doi.org/10.1142/s2301385016400021.
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This paper addresses the coverage control problem for a network of mobile sensors with first-order discrete-time dynamics, where the goal is to minimize a coverage cost function which is defined as the largest distance between any point on a circle and its nearest sensor. Since in practice sensors’ moving speed is always upper bounded, there exist saturation constraints on the control inputs of the mobile sensors. In this paper, distributed coverage control laws with input saturation are developed to drive the sensors to the final configuration such that the coverage cost function is minimized. It is also shown that the spatial order of the mobile sensors is preserved throughout the network’s evolution. As a result, collision avoidance between mobile sensors is always guaranteed.
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Mahdi Azooz, Salam, Jaber H. Majeed, Raed Khalid Ibrahim, and Adnan Hussein Ali. "Implementation of energy-efficent routing protocol within real time clustering wireless sensor networks." Bulletin of Electrical Engineering and Informatics 11, no. 4 (August 1, 2022): 2062–70. http://dx.doi.org/10.11591/eei.v11i4.3916.
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Wireless sensor networks (WSNs) are characterized by huge sensors that are having a limited amount of energy and specifying their behavior. Sensor networks combine distributed sensing, processing, and communication capabilities to create a powerful system. There are issues with the length of sensors connected to the network since features inside the sensors frequently require energy, which is likely to limit WSN performance. In creating WSN application architectures, extending network longevity, scalability, and load balancing are important factors. Using clustering techniques, the challenge of prolonging overall network lifetime and increasing the first dead node duration in the network may be tackled. Clustering is a valuable approach for breaking a network into parts known as clusters and giving solutions for energy consumption concerns including data collection, aggregating, and routing to sink nodes by cluster heads (CHs). In this paper, we suggest optimum clustering in multi-path and multi-hop protocols as a feasible option for reducing energy consumption and extending the lifetime of wireless sensor networks. In compared to the low energy adaptive clustering hierarchy (LEACH) clustering method, simulation results show that the new technique, optimal real time clustering (ORTC), is promising in terms of extending network lifetime.
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Ponmagal, R. S. "Architecting Service Based Sensor Networks for the Intelligent Assimilation." Chinese Journal of Engineering 2014 (January 9, 2014): 1–8. http://dx.doi.org/10.1155/2014/701829.
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The aim of this paper is to propose an architectural model for assimilating distributed sensor networks through cloud paradigm. This strategy can be applied to monitor and control the physical parameters such as temperature, pressure, and level. It is proposed to consider the use of service oriented architecture to program and deploy the sensed parameters. The service oriented architecture for sensor network has been implemented in such a way that, for every specific requirement of the monitor center, the assimilation agent invokes the services of the sensors through a registry and the specific changes in the sensed parameters are also notified as auditable event using push interaction pattern of SOA. The assimilation agent serves as an intelligent component by providing authentication services. This SOA is extended to integrate different types of sensor networks through cloud environment. Hence several sensors can be networked together to monitor different process parameters and they have been assimilated with Internet by registering them as services, hence a complete distributed assimilation environment is exploited.
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Madhushri, Priyanka, and Emil Jovanov. "Long-Term Synchronization of Hybrid Sensors Networks." International Journal of Embedded and Real-Time Communication Systems 9, no. 2 (July 2018): 32–46. http://dx.doi.org/10.4018/ijertcs.2018070103.
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This article presents synchronization of a hybrid distributed sensor network with wired and wireless sensors. Authors present an implementation of a sleep monitoring system as a hybrid sensor network that combines wireless inertial sensors controlled by a custom smartphone application as an extension of the polysomnographic (PSG) monitor to improve user's comfort. The authors developed an original method of synchronization of wireless sensor data with the PSG records using an auxiliary audio synchronization signal generated by the smartphone. The timestamps on the smartphone are synchronized with the timestamps from inertial sensors, and time of generated synchronization pulses recorded by the PSG. The individual data streams were synchronized using the Dynamic Time Warping (DTW) mechanism. Authors present the system organization and the results of analysis of the whole night monitoring, including the analysis of channel reliability and clock drift. Clock drift has been reduced from 10-30 seconds to 5.1± 3 milliseconds which is with an improved accuracy as compare to existing methods.
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Patra, Chiranjib, Anjan Guha Roy, Samiran Chattopadhyay, and Parama Bhaumik. "Designing Energy-Efficient Topologies for Wireless Sensor Network: Neural Approach." International Journal of Distributed Sensor Networks 6, no. 1 (January 1, 2010): 216716. http://dx.doi.org/10.1155/2010/216716.
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Preserving energy or battery power of wireless sensor network is of major concern. As such type of network, the sensors are deployed in an ad hoc manner, without any deterministic way. This paper is concerned with applying standard routing protocols into wireless sensor network by using topology modified by neural network which proves to be energy efficient as compared with unmodified topology. Neural network has been proved to be a powerful tool in the distributed environment. Here, to capture the true distributed nature of the Wireless Sensor Network (WSN), neural network's Self-Organizing Feature Map (SOFM) is used.
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Abosata, Nasr, Saba Al-Rubaye, and Gokhan Inalhan. "Lightweight Payload Encryption-Based Authentication Scheme for Advanced Metering Infrastructure Sensor Networks." Sensors 22, no. 2 (January 11, 2022): 534. http://dx.doi.org/10.3390/s22020534.
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The Internet of Things (IoT) connects billions of sensors to share and collect data at any time and place. The Advanced Metering Infrastructure (AMI) is one of the most important IoT applications. IoT supports AMI to collect data from smart sensors, analyse and measure abnormalities in the energy consumption pattern of sensors. However, two-way communication in distributed sensors is sensitive and tends towards security and privacy issues. Before deploying distributed sensors, data confidentiality and privacy and message authentication for sensor devices and control messages are the major security requirements. Several authentications and encryption protocols have been developed to provide confidentiality and integrity. However, many sensors in distributed systems, resource constraint smart sensors, and adaptability of IoT communication protocols in sensors necessitate designing an efficient and lightweight security authentication scheme. This paper proposes a Payload Encryption-based Optimisation Scheme for lightweight authentication (PEOS) on distributed sensors. The PEOS integrates and optimises important features of Datagram Transport Layer Security (DTLS) in Constrained Application Protocol (CoAP) architecture instead of implementing the DTLS in a separate channel. The proposed work designs a payload encryption scheme and an Optimised Advanced Encryption Standard (OP-AES). The PEOS modifies the DTLS handshaking and retransmission processes in PEOS using payload encryption and NACK messages, respectively. It also removes the duplicate features of the protocol version and sequence number without impacting the performance of CoAP. Moreover, the PEOS attempts to improve the CoAP over distributed sensors in the aspect of optimised AES operations, such as parallel execution of S-boxes in SubBytes and delayed Mixcolumns. The efficiency of PEOS authentication is evaluated on Conitki OS using the Cooja simulator for lightweight security and authentication. The proposed scheme attains better throughput while minimising the message size overhead by 9% and 23% than the existing payload-based mutual authentication PbMA and basic DTLS/CoAP scheme in random network topologies with less than 50 nodes.
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Stankovic, Milos, Srdjan Stankovic, and Karl Johansson. "A consensus-based distributed calibration algorithm for sensor networks." Serbian Journal of Electrical Engineering 13, no. 1 (2016): 111–32. http://dx.doi.org/10.2298/sjee1601111s.
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In this paper a novel distributed algorithm for blind macro-calibration in sensor networks based on consensus is proposed. The algorithm is formulated as a set of gradient-type recursions for estimating parameters of sensor calibration functions, starting from local criteria defined as weighted sums of mean square differences between the outputs of neighboring sensors. It is proved that the algorithm achieves asymptotic agreement for sensor gains and offsets in the mean square sense and with probability one. In the case of additive measurement noise, additive inter-agent communication noise and communication outages, a modification of the original algorithm is proposed. It is proved using stochastic approximation arguments that the modified algorithm achieves asymptotic consensus for sensor gains and offsets in the mean square sense and with probability one. Special attention is paid to the situation when one sensor is selected as a reference. Illustrative simulation examples are provided.