Relevant bibliographies by topics / Wireless data networks

Academic literature on the topic 'Wireless data networks'

Author: Grafiati
Published: 10 December 2022
Last updated: 30 January 2023

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Journal articles on the topic "Wireless data networks"

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Prathap, Jomma, and Ramavath Janu. "All Data Aggregation in Wireless Sensor Networks." International Journal of Innovative Research in Engineering & Management 4, no. 6 (November 2017): 757–60. http://dx.doi.org/10.21276/ijirem.2017.4.6.2.

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Hadi, Teeb Hussein. "Types of Attacks in Wireless Communication Networks." Webology 19, no. 1 (January 20, 2022): 718–28. http://dx.doi.org/10.14704/web/v19i1/web19051.

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One of the most important types that used to transfer data between nodes without using wires is a “wireless communication network”, where the transmission of data is censored remotely by using electromagnetic waves such as radio waves that usually implemented in the physical layer of the network. Continuous improvements in wireless network technology have reduced the security and speed differences between types of networks (wired and wireless), but in turn, increased security threats to wirelessly transmitted data. Wireless networks are weak in terms of "privacy protection" because anyone who is within the coverage area of a wireless network can attempt to break into that network. Hacking incidents have been reported frequently in places with shared free networks, and it has been observed that the places of open distributed networks of the Internet are most at risk of complete penetration of your phone or PC data. To solve this problem, several programs have been developed that provide protection for wireless networks that differ in terms of security. Some of them did not provide sufficient protection for wireless networks, such as Wired Equivalent Privacy (WEP), and others made progress in preventing intrusions compared to their predecessors, such as Wi-Fi Protected Access (WPA).
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Dohare, Anand, Tulika, and Mallikarjuna B. "Data Collection in Wireless Sensor Networks Using Prediction Method." Journal of Advanced Research in Dynamical and Control Systems 11, no. 0009-SPECIAL ISSUE (September 25, 2019): 815–20. http://dx.doi.org/10.5373/jardcs/v11/20192637.

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Liu, Wei, Qin Sheng Du, and Le Le Wang. "Study of Data Fusion Mechanism Based on the WSN." Applied Mechanics and Materials 321-324 (June 2013): 600–603. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.600.

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Wireless sensor networks integrated four technologies including sensor, embedded computing, network technology and wireless communication. It is a new type of non-infrastructure wireless network. In this paper, a data fusion method has been brought forward based on wireless sensor networks, and through an algorithm simulation test, It is proved that the algorithm is effective to reduce the energy consumption of the network, and extend the lifetime of the network.
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Ma, Lili, Jiangping Liu, and Jidong Luo. "Method of Wireless Sensor Network Data Fusion." International Journal of Online Engineering (iJOE) 13, no. 09 (September 22, 2017): 114. http://dx.doi.org/10.3991/ijoe.v13i09.7589.

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<p style="margin: 1em 0px;"><span lang="EN-US"><span style="font-family: 宋体; font-size: medium;">In order to better deal with large data information in computer networks, a large data fusion method based on wireless sensor networks is designed. Based on the analysis of the structure and learning algorithm of RBF neural networks, a heterogeneous RBF neural network information fusion algorithm in wireless sensor networks is presented. The effectiveness of information fusion processing methods is tested by RBF information fusion algorithm. The proposed algorithm is applied to heterogeneous information fusion of cluster heads or sink nodes in wireless sensor networks. The simulation results show the effectiveness of the proposed algorithm. Based on the above finding, it is concluded that the RBF neural network has good real-time performance and small network delay. In addition, this method can reduce the amount of information transmission and the network conflicts and congestion.</span></span></p>
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Zhao, Ying, Ru Kun Li, and Kun Le Xu. "The Design of Wireless Sensor Networks and Data Analysis in Smart Grids." Advanced Materials Research 978 (June 2014): 257–60. http://dx.doi.org/10.4028/www.scientific.net/amr.978.257.

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Smart grids have a close relationship to advanced sensing technology and communication technology and also have provided a new application platform for wireless sensor networks. From wireless sensor networks research development and characteristics, combined with current status of wireless sensor networks applications in power system, this paper describes its key technologies of wireless sensor networks, then analyze applications and data analysis of the wireless sensor network in the smart grids.
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Firooz, Mohammad Hamed, and Sumit Roy. "Data Dissemination in Wireless Networks with Network Coding." IEEE Communications Letters 17, no. 5 (May 2013): 944–47. http://dx.doi.org/10.1109/lcomm.2013.031313.121994.

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Qiu, X., K. Chawla, J. C. I. Chuang, and N. Sollenberger. "Network-assisted resource management for wireless data networks." IEEE Journal on Selected Areas in Communications 19, no. 7 (July 2001): 1222–34. http://dx.doi.org/10.1109/49.932691.

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Luo, Li. "Data Aggregation in Wireless Sensor Networks." International Journal of Online Engineering (iJOE) 12, no. 11 (November 24, 2016): 28. http://dx.doi.org/10.3991/ijoe.v12i11.6233.

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In order to solve the problem of low efficiency and high energy consumption in data processing, In this paper, for reducing the communication overhead of data aggregation, we put forward a cluster division based data aggregation scheme for wireless sensor networks in which the cluster is divided into three subareas and some report nodes are assigned to each subarea. Simulation results show that, compared with LEACH algorithm, BP neural network and PSO-BP algorithm, more than 50% lower compression error is decreased and the simplicity of the improved algorithm makes it suitable for massive and the long term environmental monitoring network.
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Kumar, N. B. S. Vijay, D. Venkatesh D. Venkatesh, and K. Ramesh K. Ramesh. "Rapid Data Collection in Wireless Sensor Networks Organized as Trees." International Journal of Scientific Research 2, no. 5 (June 1, 2012): 223–26. http://dx.doi.org/10.15373/22778179/may2013/74.

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Dissertations / Theses on the topic "Wireless data networks"

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Cui, Jin. "Data aggregation in wireless sensor networks." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSEI065/document.

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Depuis plusieurs années, l’agrégation de données sont considérés comme un domaine émergent et prometteur tant dans le milieu universitaire que dans l’industrie. L’énergie et la capacité du réseau seront donc économisées car il y aura moins de transmissions de données. Le travail de cette thèse s’intéresse principalement aux fonctions d’agrégation Nous faisons quatre contributions principales. Tout d’abord, nous proposons deux nouvelles métriques pour évaluer les performances des fonctions d’agrégations vue au niveau réseau : le taux d’agrégation et le facteur d’accroissement de la taille des paquets. Le taux d’agrégation est utilisé pour mesurer le gain de paquets non transmis grâce à l’agrégation tandis que le facteur d’accroissement de la taille des paquets permet d’évaluer la variation de la taille des paquets en fonction des politiques d’agrégation. Ces métriques permettent de quantifier l’apport de l’agrégation dans l’économie d’énergie et de la capacité utilisée en fonction du protocole de routage considéré et de la couche MAC retenue. Deuxièmement, pour réduire l’impact des données brutes collectées par les capteurs, nous proposons une méthode d’agrégation de données indépendante de la mesure physique et basée sur les tendances d’évolution des données. Nous montrons que cette méthode permet de faire une agrégation spatiale efficace tout en améliorant la fidélité des données agrégées. En troisième lieu, et parce que dans la plupart des travaux de la littérature, une hypothèse sur le comportement de l’application et/ou la topologie du réseau est toujours sous-entendue, nous proposons une nouvelle fonction d’agrégation agnostique de l’application et des données devant être collectées. Cette fonction est capable de s’adapter aux données mesurées et à leurs évolutions dynamiques. Enfin, nous nous intéressons aux outils pour proposer une classification des fonctions d’agrégation. Autrement dit, considérant une application donnée et une précision cible, comment choisir les meilleures fonctions d’agrégations en termes de performances. Les métriques, que nous avons proposé, sont utilisées pour mesurer la performance de la fonction, et un processus de décision markovien est utilisé pour les mesurer. Comment caractériser un ensemble de données est également discuté. Une classification est proposée dans un cadre précis
Wireless Sensor Networks (WSNs) have been regarded as an emerging and promising field in both academia and industry. Currently, such networks are deployed due to their unique properties, such as self-organization and ease of deployment. However, there are still some technical challenges needed to be addressed, such as energy and network capacity constraints. Data aggregation, as a fundamental solution, processes information at sensor level as a useful digest, and only transmits the digest to the sink. The energy and capacity consumptions are reduced due to less data packets transmission. As a key category of data aggregation, aggregation function, solving how to aggregate information at sensor level, is investigated in this thesis. We make four main contributions: firstly, we propose two new networking-oriented metrics to evaluate the performance of aggregation function: aggregation ratio and packet size coefficient. Aggregation ratio is used to measure the energy saving by data aggregation, and packet size coefficient allows to evaluate the network capacity change due to data aggregation. Using these metrics, we confirm that data aggregation saves energy and capacity whatever the routing or MAC protocol is used. Secondly, to reduce the impact of sensitive raw data, we propose a data-independent aggregation method which benefits from similar data evolution and achieves better recovered fidelity. Thirdly, a property-independent aggregation function is proposed to adapt the dynamic data variations. Comparing to other functions, our proposal can fit the latest raw data better and achieve real adaptability without assumption about the application and the network topology. Finally, considering a given application, a target accuracy, we classify the forecasting aggregation functions by their performances. The networking-oriented metrics are used to measure the function performance, and a Markov Decision Process is used to compute them. Dataset characterization and classification framework are also presented to guide researcher and engineer to select an appropriate functions under specific requirements
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Huang, Wen, and 黄文. "Opportunistic scheduling in wireless data networks." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B45895235.

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Bolia, Nomesh Kulkarni Vidyadhar G. "Scheduling in wireless cellular data networks." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2009. http://dc.lib.unc.edu/u?/etd,2780.

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Thesis (Ph. D.)--University of North Carolina at Chapel Hill, 2009.
Title from electronic title page (viewed Mar. 10, 2010). "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Statistics and Operations Research Operations Research." Discipline: Statistics and Operations Research; Department/School: Statistics and Operations Research.
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Xu, Ji. "Data caching in wireless mobile networks /." View abstract or full-text, 2004. http://library.ust.hk/cgi/db/thesis.pl?COMP%202004%20XU.

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Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2004.
Includes bibliographical references (leaves 57-60). Also available in electronic version. Access restricted to campus users.
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Rasul, Aram Mohammed. "Data collection in wireless sensor networks." Thesis, University of Leicester, 2016. http://hdl.handle.net/2381/37606.

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This thesis is principally concerned with effcient energy consumption in wireless sensor networks from two distinct aspects from a theoretical point of view. The thesis addresses the issue of reducing idle listening states in a restricted tree topology to minimise energy consumption by proposing an optimisation technique: the extra-bit technique. This thesis also focuses on showing lower bounds on the optimal schedule length, which are derived for some special cases of the tree, such as a single chain, balanced chains, imbalanced chains, three and four level k-ary trees and Rhizome trees. Then, we propose an algorithm which can exactly match the lower bound for a single chain, balanced chains and Rhizome trees individually and which is a few steps away from the optimal solution for imbalanced chains. Finally, we propose the use of two frequencies to further save energy and minimize latency. Recent research has shown that significant energy improvements can be achieved in WSNs by exploiting a mobile sink for data collection via single hop communications. A mobile sink approaches the transmission range of sensors to receive their data and deposit the data at the base station. The thesis, as a second problem, focuses on the design issues of an energy efficient restricted tour construction for sink mobility. We propose two different techniques. The first one is heuristic and uses a criterion based on maximum coverage and minimum energy consumption called the "max-ratio". Although its time complexity is polynomial, this heuristic algorithm cannot always produce a good solution. As a result, we propose the sec- ond algorithm. Despite the time complexity of the second algorithm being pseudo polynomial, the optimal solution can be found if one exists. For each algorithm men- tioned, two scenarios are taken into account with regard to the transmission. In the first scenario, one assumes that there is no upper bound on the transmission range while in the second setting the nodes can adjust their transmission range between 0 and the maximum range. The algorithms have been implemented and simulated in Matlab.
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Ostovari, Pouya. "Priority-Based Data Transmission in Wireless Networks using Network Coding." Diss., Temple University Libraries, 2015. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/360800.

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Computer and Information Science
Ph.D.
With the rapid development of mobile devices technology, they are becoming very popular and a part of our everyday lives. These devices, which are equipped with wireless radios, such as cellular and WiFi radios, affect almost every aspect of our lives. People use smartphone and tablets to access the Internet, watch videos, chat with their friends, and etc. The wireless connections that these devices provide is more convenient than the wired connections. However, there are two main challenges in wireless networks: error-prone wireless links and network resources limitation. Network coding is widely used to provide reliable data transmission and to use the network resources efficiently. Network coding is a technique in which the original packets are mixed together using algebraic operations. In this dissertation, we study the applications of network coding in making the wireless transmissions robust against transmission errors and in efficient resource management. In many types of data, the importance of different parts of the data are different. For instance, in the case of numeric data, the importance of the data decreases from the most significant to the least significant bit. Also, in multi-layer videos, the importance of the packets in different layers of the videos are not the same. We propose novel data transmission methods in wireless networks that considers the unequal importance of the different parts of the data. In order to provide robust data transmissions and use the limited resources efficiently, we use random linear network coding technique, which is a type of network coding. In the first part of this dissertation, we study the application of network coding in resource management. In order to use the the limited storage of cache nodes efficiently, we propose to use triangular network coding for content distribution. We also design a scalable video-on-demand system, which uses helper nodes and network coding to provide users with their desired video quality. In the second part, we investigate the application of network coding in providing robust wireless transmissions. We propose symbol-level network coding, in which each packet is partitioned to symbols with different importance. We also propose a method that uses network coding to make multi-layer videos robust against transmission errors.
Temple University--Theses
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Collins, Diarmuid. "Wireless Data Acquisition in Flight Test Networks." International Foundation for Telemetering, 2015. http://hdl.handle.net/10150/596417.

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ITC/USA 2015 Conference Proceedings / The Fifty-First Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2015 / Bally's Hotel & Convention Center, Las Vegas, NV
The use of wireless data networks is ubiquitous in the consumer world. They have gained significant traction due to advantages afforded by the lack of wires. These same advantages can prove valuable in Flight Test for data acquisition. Sensor nodes are ideal candidates for low bandwidth wireless networks. Located in remote, hard to reach and hostile environments, wirelessly acquiring data from such sensor can solve a number of existing issues for FTI engineers. Implementing such wireless communication introduces a number of challenges such as guaranteeing reliable transfer of the sensor data and time synchronization of the remote nodes. This paper addresses wireless sensor acquisition, the associated challenges and discusses approaches and solutions to these problems.
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Yazar, Dogan. "RESTful Wireless Sensor Networks." Thesis, Uppsala University, Department of Information Technology, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-110353.

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Sensor networks have diverse structures and generally employ proprietary protocols to gather useful information about the physical world. This diversity generates problems to interact with these sensors since custom APIs are needed which are tedious, error prone and have steep learning curve. In this thesis, I present RESThing, a lightweight REST framework for wireless sensor networks to ease the process of interacting with these sensors by making them accessible over the Web. I evaluate the system and show that it is feasible to support widely used and standard Web protocols in wireless sensor networks. Being able to integrate these tiny devices seamlessly into the global information medium, we can achieve the Web of Things.

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Velayutham, Aravind Murugesan. "Transport Protocols for Next Generation Wireless Data Networks." Thesis, Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/6957.

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Emerging wireless networks are characterized by increased heterogeneity in wireless access technologies as well as increased peer-to-peer communication among wireless hosts. The heterogeneity among wireless access interfaces mainly exists because of the fact that different wireless technologies deliver different performance trade-offs. Further, more and more infrastructure-less wireless networks such as ad-hoc networks are emerging to address several application scenarios including military and disaster recovery. These infrastructure-less wireless networks are characterized by the peer-to-peer communication model. In this thesis, we propose transport protocols that tackle the challenges that arise due to the above-mentioned properties of state-of-the-art wireless data networks. The main contributions of this work are as follows: 1. We determine the ideal nature and granularity of transport adaptation for efficient operation in heterogeneous wireless data networks by performing comprehensive experimental analysis. We then design and implement a runtime adaptive transport framework, *TP, which accommodates the capabilities of the ideal transport adaptation solution. 2. We prove that conversational transport protocols are not efficient under peer-to-peer wireless data networks. We then design and implement NCTP which is a non-conversational transport protocol.
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Hsieh, Hung-Yun. "Addressing Network Heterogeneity and Bandwidth Scarcity in Future Wireless Data Networks." Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/5063.

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To provide mobile hosts with seamless and broadband wireless Internet access, two fundamental problems that need to be tackled in wireless networking are transparently supporting host mobility and effectively utilizing wireless bandwidth. The increasing heterogeneity of wireless networks and the proliferation of wireless devices, however, severely expose the limitations of the paradigms adopted by existing solutions. In this work, we explore new research directions for addressing network heterogeneity and bandwidth scarcity in future wireless data networks. In addressing network heterogeneity, we motivate a transport layer solution for transparent mobility support across heterogeneous wireless networks. We establish parallelism and transpositionality as two fundamental principles to be incorporated in designing such a transport layer solution. In addressing bandwidth scarcity, we motivate a cooperative wireless network model for scalable bandwidth utilization with wireless user population. We establish base station assistance and multi-homed peer relay as two fundamental principles to be incorporated in designing such a cooperative wireless network model. We present instantiations based on the established principles respectively, and demonstrate their performance and functionality gains through theoretic analysis, packet simulation, and testbed emulation.
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Books on the topic "Wireless data networks"

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Gao, Yue, and Zhijin Qin. Data-Driven Wireless Networks. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-00290-9.

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Wireless and mobile data networks. Hoboken, NJ: John Wiley & Sons, 2005.

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Ahmad, Aftab. Wireless and Mobile Data Networks. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471729221.

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Ahmad, Aftab. Wireless and Mobile Data Networks. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471729221.

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Afzal, Muhammad Khalil, Muhammad Ateeq, and Sung Won Kim. Data-Driven Intelligence in Wireless Networks. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003216971.

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Held, Gilbert. Data over wireless networks: Bluetooth, WAP, and wireless LANS. New York, NY: McGraw-Hill, 2001.

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H, Levesque Allan, ed. Wireless information networks. New York: Wiley, 1995.

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Mobile data and wireless LAN technologies. Upper Saddle River, NJ: Prentice Hall PTR, 1997.

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Data communication principles: For fixed and wireless networks. Boston: Kluwer Academic Publishers, 2003.

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Caro, Dick. Wireless networks for industrial automation. Research Triangle Park, NC: ISA, 2014.

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Book chapters on the topic "Wireless data networks"

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Cheng, Xiang, Luoyang Fang, Liuqing Yang, and Shuguang Cui. "Mobile Big Data." In Wireless Networks, 1–11. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-96116-3_1.

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Lu, Rongxing. "Privacy-Preserving Data Aggregation with Data Integrity and Fault Tolerance." In Wireless Networks, 153–77. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32899-7_8.

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Zeng, Deze, Lin Gu, and Song Guo. "Cost Minimization for Big Data Processing in Geo-Distributed Data Centers." In Wireless Networks, 59–78. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24720-5_4.

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Lu, Rongxing. "Privacy-Preserving Multidimensional Data Aggregation." In Wireless Networks, 41–60. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32899-7_3.

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Lu, Rongxing. "Privacy-Preserving Subset Data Aggregation." In Wireless Networks, 61–84. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32899-7_4.

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Lu, Rongxing. "Privacy-Preserving Multifunctional Data Aggregation." In Wireless Networks, 85–110. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32899-7_5.

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Zhang, Kuan, and Xuemin Shen. "Privacy-Preserving Health Data Processing." In Wireless Networks, 81–98. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24717-5_5.

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Zhang, Kuan, and Xuemin Shen. "Secure Health Data Collection in MHN." In Wireless Networks, 21–45. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24717-5_3.

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Zhang, Kuan, and Xuemin Shen. "Health Data Sharing with Misbehavior Detection." In Wireless Networks, 47–80. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24717-5_4.

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Du, Jun, and Chunxiao Jiang. "Cooperative Data Transaction in Mobile Networks." In Wireless Networks, 351–87. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-7648-3_15.

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Conference papers on the topic "Wireless data networks"

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QasMarrogy, Ghassan. "Practical Analysis of IEEE 802.11ax Wireless Protocol in Wi-Fi Boosters Environments." In 3rd International Conference of Mathematics and its Applications. Salahaddin University-Erbil, 2020. http://dx.doi.org/10.31972/ticma22.04.

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All the world now is depending on networks to share information between the users, where different data types are transferred wirelessly from network to network. Using wireless LANs are important to connect the users and share the data, these Wireless LANs have different types of obstacles that affect the data sharing or the wireless signal, such as, compatibility wireless protocol types, range coverage, walls penetration, moving devices, different routing protocols, data transferred types, weak signal, and many more. In this paper a practical analysis will be made to the latest IEEE 802.11ax wireless protocol to be compared with two types of Wi-Fi booster’s networks, Mesh and Extender Wi-Fi, while transferring 4k video size data rate, inside a room and on different rooms for wall penetration analysis, while measuring the throughput, delay, and signal strength metrics. The main importance of this paper is to give a more practical understanding and avoid the main problems of using the wireless protocol 802.11ax in different network types.
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Monroy, Idelfonso Tafur. "Photonic Techniques for Sub-Terahertz Wireless Data Transmission." In Photonic Networks and Devices. Washington, D.C.: OSA, 2015. http://dx.doi.org/10.1364/networks.2015.net1d.1.

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Jahedi, Zahra, and Thomas Kunz. "Virtual Network Function Embedding in Multi-hop Wireless Networks." In International Conference on Data Communication Networking. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0006887400330041.

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Jahedi, Zahra, and Thomas Kunz. "Virtual Network Function Embedding in Multi-hop Wireless Networks." In International Conference on Data Communication Networking. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0006887401990207.

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Stattner, Erick, Martine Collard, Philippe Hunel, and Nicolas Vidot. "Wireless sensor networks for social network data collection." In 2011 IEEE 36th Conference on Local Computer Networks (LCN 2011). IEEE, 2011. http://dx.doi.org/10.1109/lcn.2011.6115565.

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Cosar, Emre I., Maurizio Bocca, and Lasse M. Eriksson. "High Speed Portable Wireless Data Acquisition System for High Data Rate Applications." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-86459.

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Communication between a sink node and a PC can constitute a bottleneck for high data rate applications of wireless sensor networks (WSNs) including, but not limited to, structural health monitoring, condition monitoring, wireless surveillance and patient health monitoring. In this paper, we evaluate four different data acquisition alternatives for data-intensive WSN applications. We will concentrate especially on optimizing UART (universal asynchronous receiver transmitter) communication in conjunction with WSN applications. Furthermore, we propose a new method for sink node to PC communication, which is based on using a USB-connected data acquisition (DAQ) board that samples the node external I/O. This method can provide an efficient solution to transfer data from the sink node to PC at a reasonable cost. Wireless sink node converts the data received from the network into analog signal levels, which are sampled through the DAQ board connected to a PC, and the original data is reconstructed offline. Tests on a wooden bridge built to scale with six wireless sensor nodes and a sink node show that with the proposed method it is possible to collect the data from the network and transfer them onto the PC significantly faster than with the 115.2 kbps UART communication regularly used in WSN applications.
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Lee, Wang-Chien, and Yingqi Xu. "Location-Aware Wireless Sensor Networks." In 2007 International Conference on Mobile Data Management. Conference and Custom Publishing, 2007. http://dx.doi.org/10.1109/mdm.2007.44.

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Paavola, Jarkko, Tuomo Rautava, Juhani Hallio, Juha Kalliovaara, and Tero Jokela. "Use of wireless communication networks in digitalization of factory environments." In CARPE Conference 2019: Horizon Europe and beyond. Valencia: Universitat Politècnica València, 2019. http://dx.doi.org/10.4995/carpe2019.2019.10050.

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Wireless communications are rapidly taking an important role in factory environment. The current Wi-Fi technologies struggle to meet the requirements of industrial factories, for example with regard to latency and security. The emerging 5G communication networks are the first networks expected to meet such requirements. Private networks are owned by the factories themselves. Private networks can utilize 5G technologies to tailor the networks to meet the exact demands within the factory environment and guarantee that the factories can use the whole bandwidth for their own use. This concurrently increases the data security as the data does not need to be deliveved over public networks. This paper describes the latest developments in 5G with regard to private networks and Industry 4.0, which is the name given to the digitalization, automatization and data exchange trend currently ongoing in factory environments. In this paper we describe a private cellular network we have installed inside a factory building. This network has been trialed with wireless pyrometer measurement data transmission and environmental surveillance of a measurement laboratory. This paper analyses the suitability of private networks for these use cases and discusses in general which applications would benefit the most from private wireless networks.
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Dazhi Zhang and Donggang Liu. "DataGuard: Dynamic data attestation in wireless sensor networks." In Networks (DSN). IEEE, 2010. http://dx.doi.org/10.1109/dsn.2010.5544307.

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Abdullahi, Muhammad Bello. "Appraisal of OFDM for multi-carrier, high-speed data rate wireless communication networks." In The 19th International Conference on Modelling and Applied Simulation. CAL-TEK srl, 2019. http://dx.doi.org/10.46354/i3m.2019.mas.002.

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Orthogonal Frequency Division Multiplexing (OFDM) is used to achieve multi-carrier signals and high- Speed data rate in free space. OFDM-based systems operate in the hostile multipath radio environment, which allows efficient sharing of limited resources. This research work was designed, developed and simulated an OFDM System using the basic blocks of Simulink in MATLAB/Simulink software, to support multi-carrier, high-speed data rates. This was achieved in backing of collection and review of high-quality research papers, which reported the latest research developments in OFDM communications networks, and its applications in future wireless systems. The research work significantly increases the speed of data rate signals, and many critical problems associated with the applications of OFDM technologies in future wireless systems are still looking for efficient solutions. This would overcome the global issues and challenges facing the limited bandwidth in wireless communication network.
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Reports on the topic "Wireless data networks"

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Cooper, Jason, Manish Karir, and John S. Baras. Data Dependent Keying for Wireless Networks. Fort Belvoir, VA: Defense Technical Information Center, January 2003. http://dx.doi.org/10.21236/ada440782.

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TORGERSON, MARK D., and BRIAN P. VAN LEEUWEN. Routing Data Authentication in Wireless Networks. Office of Scientific and Technical Information (OSTI), October 2001. http://dx.doi.org/10.2172/787792.

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He, Tian, Brian M. Blum, John A. Stankovic, and Tarek Abdelzaher. AIDA: Adaptive Application Independent Data Aggregation in Wireless Sensor Networks. Fort Belvoir, VA: Defense Technical Information Center, January 2005. http://dx.doi.org/10.21236/ada436798.

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Wieselthier, Jeffrey E., Craig M. Barnhart, and Anthony Ephremides. Novel Techniques for the Analysis of Wireless Integrated Voice/Data Networks. Fort Belvoir, VA: Defense Technical Information Center, July 1995. http://dx.doi.org/10.21236/ada297071.

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Wicker, Steven B. Self-Configuring Wireless Transmission and Decentralized Data Processing for Generic Sensor Networks. Fort Belvoir, VA: Defense Technical Information Center, July 2004. http://dx.doi.org/10.21236/ada425425.

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Mahdavi, Rod, and William Tschudi. Wireless Sensor Network for Improving the Energy Efficiency of Data Centers. Office of Scientific and Technical Information (OSTI), March 2012. http://dx.doi.org/10.2172/1171531.

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Nidal, Jodeh M. Optimal UAS Assignments and Trajectories for Persistent Surveillance and Data Collection from a Wireless Sensor Network. Fort Belvoir, VA: Defense Technical Information Center, December 2015. http://dx.doi.org/10.21236/ad1003575.

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Larkin, Lance, Thomas Carlson, William D’Andrea, Andrew Johnson, and Natalie Myers. Network development and autonomous vehicles : a smart transportation testbed at Fort Carson : project report summary and recommendations. Engineer Research and Development Center (U.S.), November 2022. http://dx.doi.org/10.21079/11681/45941.

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In this work, a smart transportation testbed was utilized at Fort Carson to demonstrate three use cases for the primary purpose to plan, develop, demonstrate, and employ autonomous vehicle technologies at military installations and within the surrounding communities to evaluate commercially available Connected and Automated Vehicles and the potential to reduce base operating costs, improve safety and quality of life for military service members and their families, and deliver services more efficiently and effectively. To meet this purpose, an automated vehicle shuttle, an unmanned aerial system, and a wireless network were used and tested during the project. Results for the automated shuttle indicated that despite the quantity of data generated by operations, the contractors may not be ready to share information in a readily usable format. Additionally, successful use by the public is predicated on both knowing their mobility pat-terns and staff members promoting trust in the technology to prospective riders. Results for the unmanned aerial system showed successful identification of foreign object debris and runway cracks at the airfield. The wireless network is now operational and is used for additional work which utilizes the installed traffic cameras.
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Cowles, Timothy J. Real-time Integration of Biological, Optical and Physical Oceanographic Data from Multiple Vessels and Nearshore Sites using a Wireless Network. Fort Belvoir, VA: Defense Technical Information Center, September 1997. http://dx.doi.org/10.21236/ada627905.

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Building Profitable and Sustainable Community Owned Connectivity Networks. Academy of Science of South Africa (ASSAf), 2021. http://dx.doi.org/10.17159/assaf.2019/0065.

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The IID seminar titled “Building Profitable and Sustainable Community Owned Connectivity Networks”, was hosted on 31 August 2020 on Zoom Webinar. The 2019 White Paper on science, technology and innovation (STI) recognise the pivotal enabling role of information and communication technologies (ICTs) in realising an inclusive and prosperous information society and knowledge economy. One of the Department of Science and Innovation (DSI)’s key role is to catalyse the digital ecosystem and develop scalable models for community owned connectivity networks to replicate in other areas. Rural areas provide challenging environment to implement communication infrastructure for data and Internet based services, including high cost of network implementation and lack of customer base, low-income streams, highly scattered and low population density. The DSI has thus partnered with the University of Western Cape (UWC), the Mankosi Village community, with support from the Technology Innovation Agency (TIA) to scaleup the Zenzeleni Community Owned Connectivity Networks (COCN). The Zenzeleni COCN has been in existence since 2012 and provides timely, reliable and affordable Wi-Fi connectivity to the remote rural areas of Mankosi and Zithulele in Mthatha. The webinar, facilitated by Ms Ellen Fischat from Story Room aimed to look at how rural and township wireless connectivity models, including Zenzeleni COCN can be scaled-up to increase the number of people connected in the rural settings, more so in light of the COVID-19 crisis. It is evident from the proceedings the need for community networks to provide access to connectivity and also more importantly, what connectivity enables. Subsequent discussions would need to focus on the users and owners of these community networks to understand how their lives have improved through the deployment of the technology. This will shed light of the financial feasibility and benefit.
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