Relevant bibliographies by topics / Distributed Sensor Network

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Distributed Sensor Network'

Author: Grafiati
Published: 4 June 2021
Last updated: 10 February 2022

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Journal articles on the topic "Distributed Sensor Network"

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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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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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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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B, Venkateswarulu Naik, and Dr S. Rama Krishna. "An Energy-aware Distributed Clustering Protocol in Wireless Sensor Network." International Journal of Trend in Scientific Research and Development Volume-1, Issue-6 (October 31, 2017): 1130–38. http://dx.doi.org/10.31142/ijtsrd5798.

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Wang, Hong Wei, Chun Lei Zhang, Xiao Ming Ni, Zhi Gang Gao, Wen Kai Zhang, Xiao Ni Wang, Zhi Tian Hao, and Ming Hui Wang. "Distributed Temperature Sensor Network System." Applied Mechanics and Materials 190-191 (July 2012): 968–71. http://dx.doi.org/10.4028/www.scientific.net/amm.190-191.968.

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The wireless sensor network (WSN) is the development trend of the technology of sensor. This paper, based on the nRF905 wireless module, introduces a wireless temperature gathering and transmitting system. From RF modules and master control module, the hardware platform has been designed, beyond that, the paper introduces the temperature sensor network software design. The test show that the system is stable, and datas are reliable.
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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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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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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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Lenzen, Christoph, and Roger Wattenhofer. "Distributed algorithms for sensor networks." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 370, no. 1958 (January 13, 2012): 11–26. http://dx.doi.org/10.1098/rsta.2011.0212.

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Distributed algorithms are an established tool for designing protocols for sensor networks. In this paper, we discuss the relation between distributed computing theory and sensor network applications. We also present a few basic and illustrative distributed algorithms.
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Dissertations / Theses on the topic "Distributed Sensor Network"

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Karaaslan, Ibrahim. "Anti-sensor Network: Distortion-based Distributed Attack In Wireless Sensor Networks." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/3/12609276/index.pdf.

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In this thesis, a novel anti-sensor network paradigm is introduced against wireless sensor networks (WSN). Anti-sensor network (ASN) aims to destroy application reliability by adaptively and anonymously introducing adequate level of artificial distortion into the communication of the event features transported from the sensor nodes (SN) to the sink. ASN is composed of anti-sensor nodes (aSN) randomly distributed over the sensor network field. aSNs pretend to be SNs tomaintain anonymity and so improve resiliency against attack detection and prevention mechanisms. Performance evaluations via mathematical analysis and simulation experiments show that ASN can effectively reduce the application reliability of WSN.
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Jingjing, Hao. "Distributed sensor fault detection and isolation over wireless sensor network." Doctoral thesis, Universite Libre de Bruxelles, 2017. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/254423.

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Wireless sensor networks (WSNs) can provide new methods for information gathering for a variety of applications. In order to ensure the network quality of service, the quality of the measurements has to be guaranteed. Distributed fault detection and isolation schemes are preferred to centralized solutions to diagnose faulty sensors in WSNs. Indeed the first approach avoids the need for a central node that collects information from every sensor node, and hence it limits complexity and energy cost while improving reliability.In the case of state estimation over distributed architectures, the sensor faults can be propagated in the network during the information exchanging process. To build a reliable state estimate one has to make sure that the measurements issued by the different sensors are fault free. That is one of the motivations to build a distributed fault detection and isolation (FDI) system that generates an alarm as soon as a measurement is subject to a fault (has drift, cdots ). In order to diagnose faults with small magnitude in wireless sensor networks, a systematic methodology to design and implement a distributed FDI system is proposed. It resorts to distinguishability measures to indicate the performance of the FDI system and to select the most suitable node(s) for information exchange in the network with a view to FDI. It allows one to determine the minimum amount of data to be exchanged between the different nodes for a given FDI performance. In this way, the specifications for FDI can be achieved while the communication and computation cost are kept as small as possible. The distributed FDI systems are designed both in deterministic and stochastic frameworks. They are based on the parity space approach that exploits spacial redundancy as well as temporal redundancy in the context of distributed schemes. The decision systems with the deterministic method and the stochastic method are designed not only to detect a fault but also to distinguish which fault is occurring in the network. A case study with a WSN is conducted to verify the proposed method. The network is used to monitor the temperature and humidity in a computer room. The distributed FDI system is validated both with simulated data and recorded data.
Doctorat en Sciences de l'ingénieur et technologie
info:eu-repo/semantics/nonPublished
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Murukesvan, Abhinash. "Distributed Overlays in Wireless Sensor Networks." Thesis, KTH, Kommunikationssystem, CoS, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-92202.

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This thesis investigates two architectures and compares their suitability for selective application and user differentiation in sensor networks. A hierarchical architecture consisting of more capable cluster heads surrounded by weaker nodes is compared to a flat architecture of equally powerful nodes. In both architectures there exists a logical overlay network that connects the nodes, depending on the application and user. Furthermore, a broadcast encryption scheme is proposed to aid in distributing keys to nodes for secure communication and to maintain these restricted groups.
applikation och användar differentiering i trådlösa sensor nätverk. En hierarkisk arkitekturbestående av kraftfullare sensor noder omgiven av mindre kraftfulla sensor noder jämförsmed en platt arkitektur bestående av lika kraftfulla sensor noder. I båda arkitekturer existerarett logiskt lager ovanpå stacken som kopplar noder beroende på applikation och användare,helt oberoende av geografisk placering. Utöver det, bör en nyckel management schema användas till att distribuera nycklar tillnoderna för säker kommunikation och att bibehålla dessa slutna grupper.
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Luh, William. "Distributed secrecy for information theoretic sensor network models." [College Station, Tex. : Texas A&M University, 2008. http://hdl.handle.net/1969.1/ETD-TAMU-2949.

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Jabeen, Farhana. "Distributed spatial analysis in wireless sensor networks." Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/distributed-spatial-analysis-in-wireless-sensor-networks(f8a1f71a-81b0-4dc7-b520-b90a2393a61e).html.

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Wireless sensor networks (WSNs) allow us to instrument the physical world in novel ways, providing detailed insight that has not been possible hitherto. Since WSNs provide an interface to the physical world, each sensor node has a location in physical space, thereby enabling us to associate spatial properties with data. Since WSNs can perform periodic sensing tasks, we can also associate temporal markers with data. In the environmental sciences, in particular, WSNs are on the way to becoming an important tool for the modelling of spatially and temporally extended physical phenomena. However, support for high-level and expressive spatial-analytic tasks that can be executed inside WSNs is still incipient. By spatial analysis we mean the ability to explore relationships between spatially-referenced entities (e.g., a vineyard, or a weather front) and to derive representations grounded on such relationships (e.g., the geometrical extent of that part of a vineyard that is covered by mist as the intersection of the geometries that characterize the vineyard and the weather front, respectively). The motivation for this endeavour stems primarily from applications where important decisions hinge on the detection of an event of interest (e.g., the presence, and spatio-temporal progression, of mist over a cultivated field may trigger a particular action) that can be characterized by an event-defining predicate (e.g., humidity greater than 98 and temperature less than 10). At present, in-network spatial analysis in WSN is not catered for by a comprehensive, expressive, well-founded framework. While there has been work on WSN event boundary detection and, in particular, on detecting topological change of WSN-represented spatial entities, this work has tended to be comparatively narrow in scope and aims. The contributions made in this research are constrained to WSNs where every node is tethered to one location in physical space. The research contributions reported here include (a) the definition of a framework for representing geometries; (b) the detailed characterization of an algebra of spatial operators closely inspired, in its scope and structure, by the Schneider-Guting ROSE algebra (i.e., one that is based on a discrete underlying geometry) over the geometries representable by the framework above; (c) distributed in-network algorithms for the operations in the spatial algebra over the representable geometries, thereby enabling (i) new geometries to be derived from induced and asserted ones, and (ii)topological relationships between geometries to be identified; (d) an algorithmic strategy for the evaluation of complex algebraic expressions that is divided into logically-cohesive components; (e) the development of a task processing system that each node is equipped with, thereby with allowing users to evaluate tasks on nodes; and (f) an empirical performance study of the resulting system.
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Pothiawala, Javed. "Analysis of a two-sensor tandem distributed detection network." Thesis, Massachusetts Institute of Technology, 1989. http://hdl.handle.net/1721.1/14418.

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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1989.
Includes bibliographical references.
Support provided by the Office of Naval Research. N00014-84-K-0519 (NR 649-003)
by Javed Pothiawala.
M.S.
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Li, Junlin. "Distributed estimation in resource-constrained wireless sensor networks." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/26633.

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Thesis (Ph.D)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009.
Committee Chair: Ghassan AlRegib; Committee Member: Elliot Moore; Committee Member: Monson H. Hayes; Committee Member: Paul A. Work; Committee Member: Ying Zhang. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Kulathumani, Vinodkrishnan. "Network Abstractions for Designing Reliable Applications Using Wireless Sensor Networks." The Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=osu1211560039.

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Wu, Wenbin. "Delay-tolerant data delivery in a distributed sensor network testbed." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-174071.

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Sensei-UU testbed is an inexpensive, expandable, relocatable testbed, which is designed by CoRe group in Uppsala University. It provides wireless sensor network (WSN) experiments with repeatable mobility. However, end nodes are always deployed in extreme environments where connectivity is not able to be guaranteed and Sensei-UU testbed lacks the ability to deal with this case. Reliable data delivery, therefore, is an important feature of delay tolerant network and it will extend the usage of Sensei-UU testbed. This thesis work investigates Sensei-UU testbed and improves it to support delay-tolerant data delivery. The thesis report  starts with an introduction of related background concepts regarding wireless sensor network, Sensei-UU testbed and delay tolerant network. Then a detailed technical solution of delivering delay-tolerant data in Sensei-UU testbed is presented in terms of system analysis, design and implementation.
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Askgaard, Jens Martin Breivik. "Sea Cage Gateway - A Distributed Sensor Management Network in ActorFrame." Thesis, Norwegian University of Science and Technology, Department of Telematics, 2006. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-10139.

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This master thesis has been written in connection with the ongoing Sea Cage Gateway (SCG) project, a project investigating the possibility of remotely administering fish farming facilities. These facilities consist of sea cages placed offshore and connected to the mainland through wireless communication technologies. The sea cages all contain a number of sensors optimizing production and increasing safety. Not only must this sensor data be read, it must also be transported, collected, interpreted, handled, saved and retrieved. In addition, it is necessary to provide backup communication links in case of failures in the main communication systems. The system should be as autonomous as possible, allowing it to be unmanned for longer periods of time. This thesis has further investigated the possibility of remotely controlling and administering a fish farm through distributed nodes over wireless communication links. As a basis for this thesis domain descriptions from previous master theses written in connection with the SCG-project have been used. This thesis has also aimed to collect inspiration from other domains and concepts which have similarities with the SCG-project. With the increasing numbers of nodes and communication links present at the fish farm installations, areas such as grid computing and sensor networks have many applicable principles for the SCG-system. These principles have been integrated into the system design to give the basis for further such functionality in the SCG-domain. In addition to the areas of grid computing and sensor networks, the current and latest wireless communication technologies available for providing the services required by the SCG-system have been presented. The communication links also influence the system design since their connection types must be handled by the SCG-system elements. The SCG-system proposed has been designed and implemented with ActorFrame. The implemented system has functioned as a demonstrator for the main principles presented in the design. It has incorporated a GPS-receiver and a GPRS-modem to represent a sensor on a sea cage and a redundant communication link. The system implemented reports GPS-data to a central unit and issues alerts upon sensor data deviations (sea cage out of position). Furthermore, the demonstrator can detect a failed communication link and switch to the backup GPRS-modem, generate alarms, and continue to provide basic services. All elements and their status are reported and registered in a database and are presented through a dynamic web interface. The demonstrator has shown that ActorFrame can be utilized to provide the necessary functionality the SCG-domain requires. A few improvements are proposed for the framework to increase the flexibility and performance of the system, especially in the area of handling the distribution of actors on independent nodes and how the heterogeneous network technologies present in SCG-system require a higher-level of network-awareness on behalf of the application. This thesis has also suggested several possible extensions and future areas of work.

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Books on the topic "Distributed Sensor Network"

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P, Rolim José D., and SpringerLink (Online service), eds. Theoretical Aspects of Distributed Computing in Sensor Networks. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.

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Distributed sensor networks. 2nd ed. Boca Raton: Chapman and Hall/CRC, 2013.

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Lesser, Victor, Charles L. Ortiz, and Milind Tambe, eds. Distributed Sensor Networks. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0363-7.

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Bhanu, Bir, Chinya V. Ravishankar, Amit K. Roy-Chowdhury, Hamid Aghajan, and Demetri Terzopoulos, eds. Distributed Video Sensor Networks. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-127-1.

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Distributed video sensor networks-research challenges and future directions workshop (2009 : Riverside, Calif.), ed. Distributed video sensor networks. London: Springer, 2011.

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Distributed sensor networks: Sensor networking and applications. 2nd ed. Boca Raton: Chapman & Hall/CRC, 2013.

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Lesser, Victor. Distributed Sensor Networks: A Multiagent Perspective. Boston, MA: Springer US, 2003.

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name, No. Distributed sensor networks: A multiagent perspective. Boston, MA: Kluwer Academic Publishers, 2003.

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Iyengar, Sitharama S., Kianoosh G. Boroojeni, and N. Balakrishnan. Mathematical Theories of Distributed Sensor Networks. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4419-8420-3.

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Abrardo, Andrea, Mauro Barni, Kassem Kallas, and Benedetta Tondi. Information Fusion in Distributed Sensor Networks with Byzantines. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-32-9001-3.

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Book chapters on the topic "Distributed Sensor Network"

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Kumar, Nitin, Dimitrios Gunopulos, and Vana Kalogeraki. "Sensor Network Coverage Restoration." In Distributed Computing in Sensor Systems, 409. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11502593_41.

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Majumder, Aditi. "Ubiquitous Displays: A Distributed Network of Active Displays." In Distributed Video Sensor Networks, 215–30. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-127-1_15.

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Kulathumani, Vinod, Srikanth Parupati, Arun Ross, and Raghavender Jillela. "Collaborative Face Recognition Using a Network of Embedded Cameras." In Distributed Video Sensor Networks, 373–87. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-127-1_25.

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Dong, Hongli, Zidong Wang, and Nan Hou. "Distributed Estimation over Sensor Network." In Networked Nonlinear Stochastic Time-Varying Systems, 119–58. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003189497-6.

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Song, Bi, Chong Ding, Amit Roy-Chowdhury, and Jay Farrell. "Persistent Observation of Dynamic Scenes in an Active Camera Network." In Distributed Video Sensor Networks, 259–71. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-127-1_18.

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Nguyen, Hoang Thanh, and Bir Bhanu. "VideoWeb: Optimizing a Wireless Camera Network for Real-time Surveillance." In Distributed Video Sensor Networks, 321–34. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-127-1_22.

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Li, Yiming, and Bir Bhanu. "A Comparison of Techniques for Camera Selection and Hand-Off in a Video Network." In Distributed Video Sensor Networks, 69–83. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-127-1_5.

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van der Lee, Tim, Georgios Exarchakos, and Sonia Heemstra de Groot. "In-network Hebbian Plasticity for Wireless Sensor Networks." In Internet and Distributed Computing Systems, 79–88. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-34914-1_8.

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Angluin, Dana, James Aspnes, Melody Chan, Michael J. Fischer, Hong Jiang, and René Peralta. "Stably Computable Properties of Network Graphs." In Distributed Computing in Sensor Systems, 63–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11502593_8.

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Hohlt, Barbara, and Eric Brewer. "Network Power Scheduling for TinyOS Applications." In Distributed Computing in Sensor Systems, 443–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11776178_27.

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Conference papers on the topic "Distributed Sensor Network"

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Ran Xu and Shuang-Hua Yang. "Distributed Federated Sensor Network." In 2010 13th International Conference on Information Fusion (FUSION 2010). IEEE, 2010. http://dx.doi.org/10.1109/icif.2010.5711974.

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Mari, P., F. P. Font, M. A. Dom, and S. Otero. "Application-Oriented Distributed Sensor Network." In 2008 Third International Conference on Systems ICONS. IEEE, 2008. http://dx.doi.org/10.1109/icons.2008.64.

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Kim, Hyung-Sin, Jin-Seok Han, Jae-Seok Bang, and Yong-Hwan Lee. "Distributed Scalable Network Association in Wireless Sensor Networks." In 2012 IEEE International Conference on Green Computing and Communications (GreenCom). IEEE, 2012. http://dx.doi.org/10.1109/greencom.2012.36.

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Viet, Nguyen Hoang, Ngo Anh Vien, SeungGwan Lee, and TaeChoong Chung. "Efficient Distributed Sensor Dispatch in Mobile Sensor Network." In 22nd International Conference on Advanced Information Networking and Applications - Workshops (aina workshops 2008). IEEE, 2008. http://dx.doi.org/10.1109/waina.2008.62.

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Patrikalakis, Nicholas M., Joshua Leighton, Georgios Papadopoulos, Gabriel Weymouth, Hanna Kurniawati, Pablo Valdivia y Alvarado, Tawfiq Taher, and Rubaina Khan. "Modeling and Inspection Applications of a Coastal Distributed Autonomous Sensor Network." In ASME 2012 31st International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/omae2012-83812.

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Real time in-situ measurements are essential for monitoring and understanding physical and biochemical changes within ocean environments. Phenomena of interest usually display spatial and temporal dynamics that span different scales. As a result, a combination of different vehicles, sensors, and advanced control algorithms are required in oceanographic monitoring systems. In this study our group presents the design of a distributed heterogeneous autonomous sensor network that combines underwater, surface, and aerial robotic vehicles along with advanced sensor payloads, planning algorithms and learning principles to successfully operate across the scales and constraints found in coastal environments. Examples where the robotic sensor network is used to localize algal blooms and collect modeling data in the coastal regions of the island nation of Singapore and to construct 3D models of marine structures for inspection and harbor navigation are presented. The system was successfully tested in seawater environments around Singapore where the water current is around 1–2m/s.
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Chache, Frederick M., Sean Maxon, Ram M. Narayanan, and Ramesh Bharadwaj. "Distributed network communication using B.A.T.M.A.N. algorithm over LoRa." In Radar Sensor Technology XXV, edited by Ann M. Raynal and Kenneth I. Ranney. SPIE, 2021. http://dx.doi.org/10.1117/12.2588317.

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Valdivia y Alvarado, P., T. Taher, H. Kurniawati, G. Weymouth, R. R. Khan, J. Leighton, G. Papadopoulos, G. Barbastathis, and N. Patrikalakis. "A coastal distributed autonomous sensor network." In OCEANS 2011. IEEE, 2011. http://dx.doi.org/10.23919/oceans.2011.6106998.

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Wang, Xuezhi, Rob Evans, and Jonathan Legg. "Distributed sensor fusion with network constraints." In Defense and Security, edited by Ivan Kadar. SPIE, 2004. http://dx.doi.org/10.1117/12.541954.

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Kulchin, Yuri N., Oleg B. Vitrik, Oleg V. Kirichenko, and Yuri S. Petrov. "Fiber optic distributed sensor tomography network." In Optical Tools for Manufacturing and Advanced Automation, edited by Alan D. Kersey and John P. Dakin. SPIE, 1993. http://dx.doi.org/10.1117/12.165916.

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Wonge-ammat, Panitan, Muhammed Mas-ud Hussain, Goce Trajcevski, Besim Avci, and Ashfaq Khokhar. "Distributed In-Network Processing of k-MaxRS in Wireless Sensor Networks." In 6th International Conference on Sensor Networks. SCITEPRESS - Science and Technology Publications, 2017. http://dx.doi.org/10.5220/0006210701080117.

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Reports on the topic "Distributed Sensor Network"

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Brennan, Sean M. Distributed Sensor Network Software Development Testing through Simulation. Office of Scientific and Technical Information (OSTI), December 2003. http://dx.doi.org/10.2172/833222.

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Kadambe, Shubha, and Cindy Daniell. Theoretic Based Performance Analysis of Distributed Sensor Network. Fort Belvoir, VA: Defense Technical Information Center, October 2003. http://dx.doi.org/10.21236/ada419203.

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Miyamoto, Robert, David W. Krout, and Jack McLaughlin. Distributed Environmentally-Adaptive Detection, Classification, and Localization Using a Cooperative Sensor Network. Fort Belvoir, VA: Defense Technical Information Center, September 2010. http://dx.doi.org/10.21236/ada538746.

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Tsvetkov, Pavel, Bryan Dickerson, Joseph French, Donald McEachern, and Abderrafi Ougouag. A Distributed Fiber Optic Sensor Network for Online 3-D Temperature and Neutron Fluence Mapping in a VHTR Environment. Office of Scientific and Technical Information (OSTI), April 2014. http://dx.doi.org/10.2172/1150754.

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Lacoss, Richard T. Distributed Sensor Networks. Fort Belvoir, VA: Defense Technical Information Center, September 1986. http://dx.doi.org/10.21236/ada204719.

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Lacoss, Richard T. Distributed Sensor Networks. Fort Belvoir, VA: Defense Technical Information Center, September 1985. http://dx.doi.org/10.21236/ada163866.

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Lacoss, Richard T. Distributed Sensor Networks. Fort Belvoir, VA: Defense Technical Information Center, March 1986. http://dx.doi.org/10.21236/ada176132.

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Lee, A. P., C. F. McConaghy, J. N. Simon, W. Benett, L. Jones, and J. Trevino. Sensor modules for wireless distributed sensor networks. Office of Scientific and Technical Information (OSTI), February 1999. http://dx.doi.org/10.2172/15005723.

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Park, Vincent D., and Joseph P. Macker. Protocol Considerations for Distributed Sensor Networks. Fort Belvoir, VA: Defense Technical Information Center, December 2000. http://dx.doi.org/10.21236/ada389300.

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Raghavendra, Cauligi S., and Viktor K. Prasanna. Distributed Signal Processing in Wireless Sensor Networks. Fort Belvoir, VA: Defense Technical Information Center, August 2005. http://dx.doi.org/10.21236/ada437824.

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