Relevant bibliographies by topics / Wireless sensor networks

Contents

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

Academic literature on the topic 'Wireless sensor networks'

Author: Grafiati
Published: 4 June 2021
Last updated: 31 July 2024

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Journal articles on the topic "Wireless sensor networks"

1

Navya, B., and M. Ankitha. "Wireless Sensor Networks." International Journal of Research Publication and Reviews 5, no. 3 (March 9, 2024): 3875–77. http://dx.doi.org/10.55248/gengpi.5.0324.0767.

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Chan, Tung Jung, Ching Mu Chen, and Tsair Rong Chen. "A Forwarding Station Integrated with Optimal Cluster Number Selection in Wireless Sensor Networks." Applied Mechanics and Materials 201-202 (October 2012): 745–48. http://dx.doi.org/10.4028/www.scientific.net/amm.201-202.745.

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In wireless sensor networks, power consumption is the most important issue. That is wireless sensors are normally deployed into unattended places where power of sensors is hard to be charged. Indeed, the network lifetime of wireless sensor networks equipped with city power or deployed into attended place is much longer than those wireless sensors equipped with batteries. In general, wireless sensor nodes are connected together and become a network after deployed into certain places. With the certain range places that wireless senor nodes deployed into, finding the optimal clusters can increase the entire network lifetime. Also, adding the forwarding station extends the network lifetime. Therefore, this paper proposes the integration of both the forwarding station and optimal clusters in ad-hoc wireless sensor networks. Simulation results show that the entire network lifetime proposed is extended in this paper compared to both optimal cluster number selection and normal forwarding station.
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Habibi, Payman, Goran Hassanifard, Abdulbaghi Ghaderzadeh, and Arez Nosratpour. "Offering a Demand-Based Charging Method Using the GBO Algorithm and Fuzzy Logic in the WRSN for Wireless Power Transfer by UAV." Journal of Sensors 2023 (May 2, 2023): 1–19. http://dx.doi.org/10.1155/2023/6326423.

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An extremely high number of geographically dispersed, energy-limited sensor nodes make up wireless sensor networks. One of the critical difficulties with these networks is their network lifetime. Wirelessly charging the sensors continuously is one technique to lengthen the network’s lifespan. In order to compensate for the sensor nodes’ energy through a wireless medium, a mobile charger (MC) is employed in wireless sensor networks (WRSN). Designing a charging scheme that best extends the network’s lifetime in such a situation is difficult. In this paper, a demand-based charging method using unmanned aerial vehicles (UAVs) is provided for wireless rechargeable sensor networks. In this regard, first, sensors are grouped according to their geographic position using the K-means clustering technique. Then, with the aid of a fuzzy logic system, these clusters are ranked in order of priority based on the parameters of the average percentage of battery life left in the sensor nodes’ batteries, the number of sensors, and critical sensors that must be charged, and the distance between each cluster’s center and the MC charging station. It then displays the positions of the UAV to choose the crucial sensor nodes using a routing algorithm based on the shortest and most vital path in each cluster. Notably, the gradient-based optimization (GBO) algorithm has been applied in this work for intracluster routing. A case study for a wireless rechargeable sensor network has been carried out in MATLAB to assess the performance of the suggested design. The outcomes of the simulation show that the suggested technique was successful in extending the network’s lifetime. Based on the simulation results, compared to the genetic algorithm, the proposed algorithm has been able to reduce total energy consumption, total distance during the tour, and total travel delay by 26%, 17.2%, and 25.4%, respectively.
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Chen, Bowen. "Wireless Communication Chip Designs: analysis of the Wireless Integrated Network Sensors." Highlights in Science, Engineering and Technology 70 (November 15, 2023): 580–87. http://dx.doi.org/10.54097/hset.v70i.13989.

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With the development of wireless technology, wireless integrated network sensor is a new form of sensor network. It enables highly efficient data acquisition and transmission by connecting the sensor nodes wirelessly. The purpose of this study is to investigate the basic principles and techniques of wireless integrated network sensors, analyze their application fields, and conduct experimental studies to verify their performance. This study first introduces the basic principles of wireless integrated network sensors, including wireless communication, sensor nodes, and network topology. Then, related technologies, including energy management, routing protocols and network security, are studied to improve the performance and stability of wireless integrated network sensors. Wireless integrated network sensors have wide application prospects in environmental monitoring, intelligent transportation and agriculture. Meanwhile, the energy utilization efficiency and network stability of the sensor network can be improved by adopting the new energy management mechanism and routing protocol. This study reveals the potential and value in practical applications through the exploration and research of wireless integrated network sensors. In future studies, the energy management and routing mechanisms of sensor networks can be further optimized to improve their performance and reliability. In addition, more application scenarios suitable for wireless integrated network sensors can be explored to provide solutions for practical problems.
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THATIPAMULA RAJU, THATIPAMULA RAJU, and D. DEEPIKA RANI D. DEEPIKA RANI. "Achieving Network Level Privacy in Wireless Sensor Networks." International Journal of Scientific Research 2, no. 8 (June 1, 2012): 183–87. http://dx.doi.org/10.15373/22778179/aug2013/61.

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Chen, Tzung-Shi, Jen-Jee Chen, Xiang-You Gao, and Tzung-Cheng Chen. "Mobile Charging Strategy for Wireless Rechargeable Sensor Networks." Sensors 22, no. 1 (January 4, 2022): 359. http://dx.doi.org/10.3390/s22010359.

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In a wireless sensor network, the sensing and data transmission for sensors will cause energy depletion, which will lead to the inability to complete the tasks. To solve this problem, wireless rechargeable sensor networks (WRSNs) have been developed to extend the lifetime of the entire network. In WRSNs, a mobile charging robot (MR) is responsible for wireless charging each sensor battery and collecting sensory data from the sensor simultaneously. Thereby, MR needs to traverse along a designed path for all sensors in the WRSNs. In this paper, dual-side charging strategies are proposed for MR traversal planning, which minimize the MR traversal path length, energy consumption, and completion time. Based on MR dual-side charging, neighboring sensors in both sides of a designated path can be wirelessly charged by MR and sensory data sent to MR simultaneously. The constructed path is based on the power diagram according to the remaining power of sensors and distances among sensors in a WRSN. While the power diagram is built, charging strategies with dual-side charging capability are determined accordingly. In addition, a clustering-based approach is proposed to improve minimizing MR moving total distance, saving charging energy and total completion time in a round. Moreover, integrated strategies that apply a clustering-based approach on the dual-side charging strategies are presented in WRSNs. The simulation results show that, no matter with or without clustering, the performances of proposed strategies outperform the baseline strategies in three respects, energy saving, total distance reduced, and completion time reduced for MR in WSRNs.
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Samara, Ghassan, Mohammad Hassan, and Yahya Zayed. "An Intelligent Vice Cluster Head Election Protocol in WSN." International Journal of Advances in Soft Computing and its Applications 13, no. 3 (November 28, 2021): 202–22. http://dx.doi.org/10.15849/ijasca.211128.14.

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Wireless sensor networks (WSNs) has a practical ability to link a set of sensors to build a wireless network that can be accessed remotely; this technology has become increasingly popular in recent years. Wi-Fi-enabled sensor networks (WSNs) are used to gather information from the environment in which the network operates. Many obstacles prevent wireless sensor networks from being used in a wide range of fields. This includes maintaining network stability and extending network life. In a wireless network, sensors are the most essential component. Sensors are powered by a battery that has a finite amount of power. The battery is prone to power loss, and the sensor is therefore rendered inoperative as a result. In addition, the growing number of sensor nodes off-site affects the network's stability. The transmission and reception of information between the sensors and the base consumes the most energy in the sensor. An Intelligent Vice Cluster Head Selection Protocol is proposed in this study (IVC LEACH). In order to achieve the best performance with the least amount of energy consumption, the proposed hierarchical protocol relies on a fuzzy logic algorithm using four parameters to calculate the value of each node in the network and divides them into three hierarchical levels based on their value. This improves network efficiency and reliability while extending network life by 50 percent more than the original Low Energy Adaptive Clustering Hierarchy protocol. Keywords: Wireless Sensor Networks, Sensors, Communication Protocol, Fuzzy logic, Leach protocol.
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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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Mishra, Saurabh, Prof Rakesh Ranjan, Dr Sonika Singh, and Dr Gagan Singh. "Performance Analysis of MIMO Heterogeneous Wireless Sensor Networks." International Journal of Innovative Technology and Exploring Engineering 12, no. 12 (November 30, 2023): 25–31. http://dx.doi.org/10.35940/ijitee.l9742.11121223.

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Wireless Sensor Networks (WSN) are widely used in remote applications related to defence and healthcare. A network with nodes having different capabilities like sensing, various computational capabilities, power-efficient communication, and a varied sensing range is called a heterogeneous wireless sensor network. Heterogeneous wireless sensor networks using MIMO wireless channels are more useful for energy-efficient multi-channel communication. MIMO applications in wireless sensor networks have the potential to enhance throughput, reduce End-to-End Delay, improve packet delivery ratios, and conserve energy in wireless sensor networks. Its implementation needs to be carefully considered in light of the specific deployment conditions and resource constraints of the network, considering proper antenna design, synchronisation mechanisms, and energy-efficient algorithms. This paper presents a comparative performance analysis of MIMO wireless sensor networks and traditional wireless sensor networks without MIMO for various Quality of Service parameters like Packet Delivery Ratio, End to End Delay, Throughput and Residual energy. The research work shows that the application of MIMO in Wireless Sensor Networks enables sensor nodes to collaborate effectively, leading to improved reliability and coverage, and also increases the network's lifetime by conserving energy in resource-constrained sensor nodes through the preservation of Residual Energy.
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Swapna, Bamuli. "Scalable Network Architectures for Distributed Wireless Sensor Networks." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 06 (June 25, 2024): 1–5. http://dx.doi.org/10.55041/ijsrem36083.

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Advances in sensor era and laptop networks have enabled allotted sensor networks (DSNs) to evolve from small clusters of large sensors to big swarms of micro sensors, from constant sensor nodes to mobile nodes, from stressed out communications to wireless communications, from static community topology to dynamically converting topology. To layout those networks, the factors needed to be considered are the coverage place, mobility, power intake, communication Skills and so on. In this study a survey is given regarding the analysis of AC structure and DHC shape, flat tree and DG community, sensor structure layout, ad-hoc sensor networks, sensor packages and also an outline on the patron/server version and cell-Agent primarily based community
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Dissertations / Theses on the topic "Wireless sensor networks"

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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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Tan, Hailun Computer Science &amp Engineering Faculty of Engineering UNSW. "Secure network programming in wireless sensor networks." Awarded By:University of New South Wales. Computer Science & Engineering, 2010. http://handle.unsw.edu.au/1959.4/44835.

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Network programming is one of the most important applications in Wireless Sensor Networks as It provides an efficient way to update program Images running on sensor nodes without physical access to them. Securing these updates, however, remains a challenging and important issue, given the open deployment environment of sensor nodes. Though several security schemes have been proposed to impose the authenticity and Integrity protection on network programming applications, they are either energy Inefficient as they tend to use digital signature or lacks the data confidentiality. In addition, due to the absence of secure memory management in the current sensor hardware, the attacker could inject malicious code into the program flash by exploiting buffer overflow In the memory despite the secure code dissemination. The contribution of this thesis Is to provide two software-based security protocols and one hardware-based remote attestation protocol for network programming application. Our first protocol deploys multiple one-way key chains for a multi-hop sensor network. The scheme Is shown to be lower In computational, power consumption and communication costs yet still able to secure multi??hop propagation of program images. Our second protocol utilizes an Iterative hash structure to the data packets in network programming application, ensuring the data confidentiality and authenticity. In addition, we Integrated confidentiality and DoS-attack-resistance in a multi??hop code dissemination protocol. Our final solution is a hardware-based remote attestation protocol for verification of running codes on sensor nodes. An additional piece of tamper-proof hardware, Trusted Platform Module (TPM), is imposed into the sensor nodes. It secures the sensitive information (e.g., the session key) from attackers and monitors any platform environment changes with the Internal registers. With these features of TPM, the code Injection attack could be detected and removed when the contaminated nodes are challenged in our remote attestation protocol. We implement the first two software-based protocols with Deluge as the reference network programming protocol in TinyOS, evaluate them with the extensive simulation using TOSSIM and validate the simulation results with experiments using Tmote. We implement the remote attestation protocol on Fleck, a sensor platform developed by CSIRO that Integrates an Atmel TPM chip.
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Lim, Tiong Hoo. "Dependable network protocols in wireless sensor networks." Thesis, University of York, 2013. http://etheses.whiterose.ac.uk/4903/.

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This thesis is concerned with the dependability of Wireless Sensor Networks (WSNs). We propose an approach, inspired by the immune system, that allows individual nodes to detect, diagnose and recover from different failures by switching between different protocols using a multi-modal switching mechanism. A causal link between different failures in WSN is identified. Existing fault tolerance in WSNs approaches are examined. From the survey, it is identified that various attempts have been made to improve the fault tolerance of the communication protocol especially in the routing protocols. Although tests have been performed to evaluate the communication protocols prior to deployment, failures in WSNs are still being reported when deployed in real environments. A Systematic Protocol Evaluation Technique (SPET) is proposed and applied to evaluate the dependability of the proposed multi-modal protocol and reduce the uncertainties in the experiment and to demonstrate the confidence in the measurements taken from experiments.
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Chaves, Andrea, Bruno Mayoral, Hyun-Jin Park, Mark Tsang, and Sean Tunell. "Wireless Sensor Networks: A Grocery Store Application." International Foundation for Telemetering, 2008. http://hdl.handle.net/10150/606223.

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ITC/USA 2008 Conference Proceedings / The Forty-Fourth Annual International Telemetering Conference and Technical Exhibition / October 27-30, 2008 / Town and Country Resort & Convention Center, San Diego, California
This paper explains the development of a wireless network system implemented to streamline grocery store checkout procedures. The design employs a wireless telemetry network consisting of a base station and wireless motes (Micaz MPR2400) that will be located on certain aisles, and attached to shopping carts. This system allows customers to scan items while they shop and uses cashiers for payment purposes only. The objective is to minimize the amount of processing performed by cashiers in order to reduce waiting times in line. The system was tested in a simulation environment and waiting times were reduced by 65%.
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Dogru, Sedat. "Sycophant Wireless Sensor Networks Tracked By Sparsemobile Wireless Sensor Networks While Cooperativelymapping An Area." Phd thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12615139/index.pdf.

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In this thesis the novel concept of Sycophant Wireless Sensors (SWS) is introduced. A SWS network is a static ectoparasitic clandestine sensor network mounted incognito on a mobile agent using only the agent&rsquo
s mobility without intervention. SWS networks not only communicate with each other through mobileWireless Sensor Networks (WSN) but also cooperate with them to form a global hybrid Wireless Sensor Network. Such a hybrid network has its own problems and opportunities, some of which have been studied in this thesis work. Assuming that direct position measurements are not always feasible tracking performance of the sycophant using range only measurements for various communication intervals is studied. Then this framework was used to create a hybrid 2D map of the environment utilizing the capabilities of the mobile network the sycophant. In order to show possible applications of a sycophant deployment, the sycophant sensor node was equipped with a laser ranger as its sensor, and it was let to create a 2D map of its environment. This 2D map, which corresponds to a height dierent than the follower network, was merged with the 2D map of the mobile network forming a novel rough 3D map. Then by giving up from the need to properly localize the sycophant even when it is disconnected to the rest of the network, a full 3D map of the environment is obtained by fusing 2D map and tracking capabilities of the mobile network with the 2D vertical scans of the environment by the sycophant. And finally connectivity problems that arise from the hybrid sensor/actuator network were solved. For this 2 new connectivity maintenance algorithms, one based on the helix structures of the proteins, and the other based on the acute triangulation of the space forming a Gabriel Graph, were introduced. In this new algorithms emphasis has been given to sparseness in order to increase fault tolerance to regional problems. To better asses sparseness a new measure, called Resistance was introduced, as well as another called updistance.
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Sevgi, Cuneyt. "Network Dimensioning In Randomly Deployed Wireless Sensor Networks." Phd thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/2/12611213/index.pdf.

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In this study, we considered a heterogeneous, clustered WSN, which consists of two types of nodes (clusterheads and sensor nodes) deployed randomly over a sensing field. We investigated two cases based on how clusterheads can reach the sink: direct and multi-hop communication cases. Network dimensioning problems in randomly deployed WSNs are among the most challenging ones as the attributes of these networks are mostly non-deterministic. We focused on a number of network dimensioning problems based on the connected coverage concept, which is the degree of coverage achieved by only the connected devices. To evaluate connected coverage, we introduced the term cluster size, which is the expected value of the area covered by a clusterhead together with sensor nodes connected to it. We derived formulas for the cluster size and validated them by computer simulations. By using the cluster size formulas, we proposed a method to dimension a WSN for given targeted connected coverage. Furthermore, we formulated cost optimization problems for direct and multi-hop communication cases. These formulations utilize not only cluster size formulas but also the well-connectivity concept. We suggested some search heuristics to solve these optimization problems. Additionally, we justified that, in practical cases, node heterogeneity can provide lower cost solutions. We also investigated the lifetime of WSNs and for mulated a cost optimization problem with connected coverage and lifetime constraints. By solving this optimization problem, one can determine the number of nodes of each type and the initial energies of each type of node that leads to lowest cost solution while satisfying the minimum connected coverage and minimum lifetime requirements.
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Yuan, Fenghua. "Lightweight network management design for wireless sensor networks." Online access for everyone, 2007. http://www.dissertations.wsu.edu/Thesis/Fall2007/F_Yuan_081307.pdf.

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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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Chraibi, Youssef. "Localization in Wireless Sensor Networks." Thesis, KTH, Reglerteknik, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-107528.

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Similar to many technological developments, wireless sensor networks have emerged from military needs and found its way into civil applications. Today, wireless sensor networks has become a key technology for different types of ”smart environments”, and an intense research effort is currently underway to enable the application of wireless sensor networks for a wide rangeof industrial problems. Wireless networks are of particular importance whena large number of sensor nodes have to be deployed, and/or in hazardous situations. Localization is important when there is an uncertainty of the exact location of some fixed or mobile devices. One example has been in the supervision of humidity and temperature in forests and/or fields, where thousands of sensors are deployed by a plane, giving the operator little or no possibility to influence the precise location of each node. An effective localization algorithm can then use all the available information from the wireless sensor nodes to infer the position of the individual devices. Another application is the positioning of a mobile robot based on received signal strength from a set of radio beacons placed at known locations on the factory floor. This thesis work is carried out on the wireless automation testbed at the S3. Focusing on localization processes, we will first give an overview of the state of the art in this area. From the various techniques, one idea was found to have significant bearing for the development of a new algorithm. We present analysis and simulations of the algorithms, demonstrating improved accuracy compared to other schemes although the accuracy is probably not good enough for some high-end applications. A third aspect of the work concerns the feasibility of approaches based on received signal strength indication (RSSI). Multiple measurement series have been collected in the lab with the MoteIV wireless sensor node platform. The measurement campaign indicates significant fluctuations in the RSSI values due to interference and limited repeatability of experiments, which may limit the reliability of many localization schemes, especially in an indoor environment.
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Cao, Hui. "Stabilization in wireless sensor networks." Columbus, Ohio : Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1211079872.

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Books on the topic "Wireless sensor networks"

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Cui, Li, and Xiaolan Xie, eds. Wireless Sensor Networks. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-8174-5.

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Selmic, Rastko R., Vir V. Phoha, and Abdul Serwadda. Wireless Sensor Networks. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46769-6.

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Silva, Jorge Sá, Bhaskar Krishnamachari, and Fernando Boavida, eds. Wireless Sensor Networks. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-11917-0.

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Shen, Shikai, Kaiguo Qian, Shaojun Yu, and Wu Wang, eds. Wireless Sensor Networks. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6834-9.

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Picco, Gian Pietro, and Wendi Heinzelman, eds. Wireless Sensor Networks. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28169-3.

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Akyildiz, Ian F., and Mehmet Can Vuran. Wireless Sensor Networks. Chichester, UK: John Wiley & Sons, Ltd, 2010. http://dx.doi.org/10.1002/9780470515181.

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Yang, Shuang-Hua. Wireless Sensor Networks. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-5505-8.

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Krishnamachari, Bhaskar, Amy L. Murphy, and Niki Trigoni, eds. Wireless Sensor Networks. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04651-8.

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Guo, Songtao, Kai Liu, Chao Chen, and Hongyu Huang, eds. Wireless Sensor Networks. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-1785-3.

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Fahmy, Hossam Mahmoud Ahmad. Wireless Sensor Networks. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0412-4.

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Book chapters on the topic "Wireless sensor networks"

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Higgins, Henry. "Wireless Communication." In Body Sensor Networks, 155–88. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-6374-9_4.

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Fong, David Y. "WIRELESS SENSOR NETWORKS." In Internet of Things and Data Analytics Handbook, 197–213. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2016. http://dx.doi.org/10.1002/9781119173601.ch12.

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Buratti, Chiara, Marco Martalò, Roberto Verdone, and Gianluigi Ferrari. "Wireless Sensor Networks." In Signals and Communication Technology, 3–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-17490-2_1.

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Lazarescu, Mihai Teodor, and Luciano Lavagno. "Wireless Sensor Networks." In Handbook of Hardware/Software Codesign, 1261–302. Dordrecht: Springer Netherlands, 2017. http://dx.doi.org/10.1007/978-94-017-7267-9_38.

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Lazarescu, Mihai Teodor, and Luciano Lavagno. "Wireless Sensor Networks." In Handbook of Hardware/Software Codesign, 1–42. Dordrecht: Springer Netherlands, 2016. http://dx.doi.org/10.1007/978-94-017-7358-4_38-1.

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Öztürk, Yusuf. "Wireless Sensor Networks." In Studies in Computational Intelligence, 47–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-44910-2_3.

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Kale, Vivek. "Wireless Sensor Networks." In Agile Network Businesses, 417–43. New York : CRC Press, 2017.: Auerbach Publications, 2017. http://dx.doi.org/10.4324/9781315368559-22.

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Jin, Miao, Xianfeng Gu, Ying He, and Yalin Wang. "Wireless Sensor Networks." In Conformal Geometry, 253–96. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75332-4_10.

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Lewis, Frank L. "Wireless Sensor Networks." In Smart Environments, 11–46. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/047168659x.ch2.

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Thirupathi Rao, N., Eali Stephen Neal Joshua, and Debnath Bhattacharyya. "Wireless Sensor Networks." In Advanced Wireless Communication and Sensor Networks, 97–117. New York: Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781003326205-10.

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Conference papers on the topic "Wireless sensor networks"

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Priya, Shashank, Dan Popa, and Frank Lewis. "Energy Efficient Mobile Wireless Sensor Networks." In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-14078.

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Wireless sensor networks (WSN) have tremendous potential in many environmental and structural health monitoring applications including, gas, temperature, pressure and humidity monitoring, motion detection, and hazardous materials detection. Recent advances in CMOS-technology, IC manufacturing, and networking utilizing Bluetooth communications have brought down the total power requirements of wireless sensor nodes to as low as a few hundred microwatts. Such nodes can be used in future dense ad-hoc networks by transmitting data 1 to 10 meters away. For communication outside 10 meter ranges, data must be transmitted in a multi-hop fashion. There are significant implications to replacing large transmission distance WSN with multiple low-power, low-cost WSN. In addition, some of the relay nodes could be mounted on mobile robotic vehicles instead of being stationary, thus increasing the fault tolerance, coverage and bandwidth capacity of the network. The foremost challenge in the implementation of a dense sensor network is managing power consumption for a large number of nodes. The traditional use of batteries to power sensor nodes is simply not scalable to dense networks, and is currently the most significant barrier for many applications. Self-powering of sensor nodes can be achieved by developing a smart architecture which utilizes all the environmental resources available for generating electrical power. These resources can be structural vibrations, wind, magnetic fields, light, sound, temperature gradients and water currents. The generated electric energy is stored in the matching media selected by the microprocessor depending upon the power magnitude and output impedance. The stored electrical energy is supplied on demand to the sensors and communications devices. This paper shows the progress in our laboratory on powering stationary and mobile untethered sensors using a fusion of energy harvesting approaches. It illustrates the prototype hardware and software required for their implementation including MEMS pressure and strain sensors mounted on mobile robots or stationary, power harvesting modules, interface circuits, algorithms for interrogating the sensor, wireless data transfer and recording.
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Kaur, Harminder, and Sharvan Kumar Pahuja. "MAC Protocols for Wireless Body Sensor Network." In International Conference on Women Researchers in Electronics and Computing. AIJR Publisher, 2021. http://dx.doi.org/10.21467/proceedings.114.33.

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Wireless Body Area Networks, also known as the Wireless Body Sensor Networks, provides the monitoring of the health parameters in remote areas and where the medical facility is not available. Wireless Body Sensor Networks contains the body or placement of the sensors on body for measuring the medical and non-medical parameters. These networks share the wireless medium for the transmission of the data from one place to another. So the design of Medium Access Control is a challenging task for the WBSNs due to wireless media for less energy consumption and mobility. Various MAC protocols are designed to provide less energy consumption and improve the network lifetime. This paper presents the study of these existing MAC layer protocols based on different QoS parameters that define the network quality.
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ŠILJAK, HARUN, and BISWAJIT BASU. "NATURAL SYNCHRONIZATION OF WIRELESS SENSOR NETWORKS FOR STRUCTURAL HEALTH MONITORING." In Structural Health Monitoring 2021. Destech Publications, Inc., 2022. http://dx.doi.org/10.12783/shm2021/36278.

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Time synchronization in communication networks is a common issue: in a sensor network it means that the order of data samples becomes uncertain, which can make it unusable. Dedicated signals and schemes for synchronization of sensor networks has hence been a well-researched topic for decades. Here we bring in an approach to synchronization which uses the sensory data. Drawing inspiration from sensor time synchronization using environmental noise, we consider synchronizing sensory nodes for structural health monitoring–if the physical quantity the sensors measure is correlated, propagating as a wave, or oscillating in regular fashion, it is intuitively clear how to put it to use. We discuss when structural health monitoring signals can aid synchronization; we also connect this synchronization scheme to the idea of using physical human-made structures as reservoirs for reservoir computing, formulating synchronization as a reservoir computing task.
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Xue, Xin, Luis Gonzalez-Argueta, and V. Sundararajan. "Energy Scavenging for Wireless Sensor Networks." In ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/detc2007-35829.

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Conventional condition monitoring of electrical machinery is conducted by measuring signals such as currents and vibrations outside the motor. Wireless sensors now provide a means of accessing and measuring useful signals inside the motor where the phenomena responsible for failure occur. These sensors are capable of not merely sensing, but also processing, storage and eventually communication. Since all these activities require power that is supplied conventionally by batteries, the useful life of the sensor node is limited by the life of the battery. This paper describes the design of an energy scavenger capable of collecting energy from the fringing field in a three-phase induction motor. The field in the magnetic filed is converted to electrical energy for use in intelligent wireless sensor nodes. The alternating magnetic field in a three phase induction motor is first measured by the hall-effect sensors. A coil wound on a ferrite core harvests the leaked energy. The experimental results are compared to the theoretical calculations of induced voltage. The paper describes results from tests conducted with a prototype coil that is used to power wireless sensor nodes in a motor running at full speed.
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Sundararajan, V., Andrew Redfern, Michael Schneider, Paul Wright, and James Evans. "Wireless Sensor Networks for Machinery Monitoring." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-82224.

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Wireless sensor networks (WSNs) are currently been actively investigated in the research community on account of their unprecedented spatial density of sensors, local computational plus storage capacity, and potential for distributed and fault-tolerant monitoring. Today, they are mainly deployed for environmental monitoring - e.g. for “smart building” control, water quality monitoring, and botanical studies. In the future, it is clear they have a huge potential for industrial applications such as machinery monitoring, shop instrumentation, and process control. Wireless sensor nodes can be mounted on various parts of machinery and plant to promote early fault detection and analysis. Their small size and autonomy enables their placement in locations that are usually difficult to access. In addition, it is also possible, with minimal changes to the machine configuration, to deploy sensors on the machinery after it has been installed. The sensor nodes cannot only monitor their own output but also collaborate with neighboring nodes to determine the health of the overall machines and provide early warnings of potential failure. We study, in this paper, the benefits of using wireless sensor networks in machine tools and plant equipment. We discuss the uses of these networks and the issues that must be addressed in order for these implementations to be successful. We also present two case studies for machinery and machine too monitoring.
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Wen, Yao-Jung, Alice M. Agogino, and Kai Goebel. "Fuzzy Validation and Fusion for Wireless Sensor Networks." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-60964.

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Miniaturized, distributed, networked sensors — called motes — promise to be smaller, less expensive and more versatile than other sensing alternatives. While these motes may have less individual reliability, high accuracy for the overall system is still desirable. Sensor validation and fusion algorithms provide a mechanism to extract pertinent information from massively sensed data and identify incipient sensor failures. Fuzzy approaches have proven to be effective and robust in challenging sensor validation and fusion applications. The algorithm developed in this paper — called mote-FVF (fuzzy validation and fusion) — uses a fuzzy approach to define the correlation among sensor readings, assign a confidence value to each of them, and perform a fused weighted average. A sensor network implementing mote-FVF for monitoring the illuminance in a dimmable fluorescent lighting environment empirically demonstrates the timely response of the algorithm to sudden changes in normal operating conditions while correctly isolating faulty sensor readings.
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BARKA, Kamel, Lyamine GUEZOULI, and Assem REZKI. "UAV’s enhanced data collection for heterogeneous wireless sensor networks." In International Conference on Mechanical, Automotive and Mechatronics Engineering. Aksaray: ECER, 2023. http://dx.doi.org/10.53375/icmame.2023.253.

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In this article, we propose a protocol called DataGA-DRF (a protocol for Data collection using a Genetic Algorithm through Dynamic Reference Points) that collects data from Heterogeneous wireless sensor networks. This protocol is based on DGA (Destination selection according to Genetic Algorithm) to control the movement of the UAV (Unmanned aerial vehicle) between dynamic reference points that virtually represent the sensor node deployment. The dynamics of these points ensure an even distribution of energy consumption among the sensors and also improve network performance. To determine the best points, DataGA-DRF uses a classification algorithm such as K-Means.
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Segura, Gustavo A. Nunez, Arsenia Chorti, and Cíntia Borges Margi. "IDIT-SDN: Intrusion Detection Framework for Software-defined Wireless Sensor Networks." In Anais Estendidos do Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos. Sociedade Brasileira de Computação - SBC, 2023. http://dx.doi.org/10.5753/sbrc_estendido.2023.817.

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Software-Defined Networking has been used to leverage security solutions for wireless sensor networks. However, this paradigm turns networks vulnerable to distributed denial of service attacks. IDIT-SDN is a tool for Software-defined Wireless Sensor Networks devised for DoS and DDoS attacks simulation and detection. This tool provides a framework for anomaly detection and a communication protocol to share security wise information from the sensor network to the controller. We demonstrate its use by showing a cooperative DDoS attack detection and attacker identification application based on distributed (every node) and centralized (controller) anomaly detection.
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Madhag, Aqeel, and Jongeun Choi. "Distributed Navigation Strategy of Mobile Sensor Networks With Probabilistic Wireless Communication Links." In ASME 2015 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/dscc2015-9964.

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Mobile sensor networks have been widely used to predict spatio-temporal physical phenomena for various scientific and engineering applications. To accommodate the realistic models of mobile sensor networks, we incorporated probabilistic wireless communication links based on packet reception ratio (PRR) with distributed navigation. We then derived models of mobile sensor networks that predict Gaussian random fields from noise-corrupted observations under probabilistic wireless communication links. For the given model with probabilistic wireless communication links, we derived the prediction error variances for further sampling locations. Moreover, we designed a distributed navigation that minimizes the network cost function formulated in terms of the derived prediction error variances. Further, we have shown that the solution of distributed navigation with the probabilistic wireless communication links for mobile sensor networks are uniformly ultimately bounded with respect to that of the distributed one with the R-disk communication model. According to Monte Carlo simulation results, agent trajectories under distributed navigation with the probabilistic wireless communication links are similar to those with the R-disk communication model, which confirming the theoretical analysis.
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Kim, Hyung-Sin, Jin-Seok Han, and Yong-Hwan Lee. "Scalable network joining mechanism in wireless sensor networks." In 2012 IEEE Topical Conference on Wireless Sensors and Sensor Networks (WiSNet). IEEE, 2012. http://dx.doi.org/10.1109/wisnet.2012.6172139.

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Reports on the topic "Wireless sensor networks"

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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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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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Berry, Nina M., and Teresa H. Ko. On computer vision in wireless sensor networks. Office of Scientific and Technical Information (OSTI), September 2004. http://dx.doi.org/10.2172/919195.

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Davis, William B. Graphical Model Theory for Wireless Sensor Networks. Office of Scientific and Technical Information (OSTI), December 2002. http://dx.doi.org/10.2172/833692.

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Stephenson, Andrew J. Sinkhole Avoidance Routing in Wireless Sensor Networks. Fort Belvoir, VA: Defense Technical Information Center, May 2011. http://dx.doi.org/10.21236/ada554671.

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Liu, Donggang. Secure and Robust Clustering in Wireless Sensor Networks. Fort Belvoir, VA: Defense Technical Information Center, July 2008. http://dx.doi.org/10.21236/ada500585.

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Cybenko, George, Dorothy Gramm, and Walter Gramm. Instrumentation for Wireless Agent Networks and Sensor Webs. Fort Belvoir, VA: Defense Technical Information Center, December 2001. http://dx.doi.org/10.21236/ada405520.

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Liang, Qilian. Energy Efficient Wireless Sensor Networks Using Fuzzy Logic. Fort Belvoir, VA: Defense Technical Information Center, June 2005. http://dx.doi.org/10.21236/ada434605.

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Liang, Qilian. Energy Efficient Wireless Sensor Networks Using Fuzzy Logic. Fort Belvoir, VA: Defense Technical Information Center, December 2003. http://dx.doi.org/10.21236/ada419061.

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Liang, Qilian. Energy Efficient Wireless Sensor Networks Using Fuzzy Logic. Fort Belvoir, VA: Defense Technical Information Center, June 2004. http://dx.doi.org/10.21236/ada423016.

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