Relevant bibliographies by topics / Distributed Monitoring Algorithms

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Distributed Monitoring Algorithms'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Distributed Monitoring Algorithms"

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Cormode, Graham, S. Muthukrishnan, and Ke Yi. "Algorithms for distributed functional monitoring." ACM Transactions on Algorithms 7, no. 2 (2011): 1–20. http://dx.doi.org/10.1145/1921659.1921667.

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Chen, Jiecao, and Qin Zhang. "Improved Algorithms for Distributed Entropy Monitoring." Algorithmica 78, no. 3 (2016): 1041–66. http://dx.doi.org/10.1007/s00453-016-0194-z.

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Griswold, Victor Jon. "Core algorithms for autonomous monitoring of distributed systems." ACM SIGPLAN Notices 26, no. 12 (1991): 36–45. http://dx.doi.org/10.1145/127695.122762.

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Zou, Quan, Guoqing Li, and Wenyang Yu. "Cloud Computing Based on Computational Characteristics for Disaster Monitoring." Applied Sciences 10, no. 19 (2020): 6676. http://dx.doi.org/10.3390/app10196676.

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Resources related to remote-sensing data, computing, and models are scattered globally. The use of remote-sensing images for disaster-monitoring applications is data-intensive and involves complex algorithms. These characteristics make the timely and rapid processing of disaster-monitoring applications challenging and inefficient. Cloud computing provides a dynamically scalable resource over the Internet. The rapid development of cloud computing has led to an increase in the computational performance of data-intensive computing, providing powerful throughput by distributing computation across
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Grilo, Ahda P., Pengfei Gao, Wilsun Xu, and Madson C. de Almeida. "Load Monitoring Using Distributed Voltage Sensors and Current Estimation Algorithms." IEEE Transactions on Smart Grid 5, no. 4 (2014): 1920–28. http://dx.doi.org/10.1109/tsg.2014.2304011.

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Wu, Xiaoxuan, De Tian, Huiwen Meng, and Yi Su. "Distributed Parameter Identification Framework Based on Intelligent Algorithms for Permanent Magnet Synchronous Wind Generator." Energies 18, no. 3 (2025): 683. https://doi.org/10.3390/en18030683.

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Parameter identification of a permanent magnet synchronous wind generator (PMSWG) is of great significance for condition monitoring, fault diagnosis, and robust control. However, the conventional multi-parameter identification approach for a PMSWG is plagued by deficiencies, including its sluggish identification speed, subpar accuracy, and susceptibility to local optimization. In light of these challenges, this paper proposes a distributed parameter identification framework based on intelligent algorithms. The proposed approach involves the deployment of SSA, DBO, and PSO algorithms, leveragin
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Ma, Zhen, Xiyuan Chen, Cundeng Wang, and Bingbo Cui. "Real-Time Wing Deformation Monitoring via Distributed Fiber Bragg Grating and Adaptive Federated Filtering." Sensors 25, no. 14 (2025): 4343. https://doi.org/10.3390/s25144343.

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To address the issues of decreased accuracy and poor stability in distributed transfer alignment caused by factors such as wing deflection and deformation in complex flight environments, this paper proposes a wing-distributed transfer alignment method based on Fiber Bragg Grating (FBG). This paper establishes a flexural deformation model based on FBGs, establishes a coupling angle model and a dynamic lever arm model, derives the motion parameter relationship model between the main and the sub-nodes, establishes the corresponding transfer alignment filter, and proposes a federated adaptive filt
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Preti, F. "Overland transport of nitrate: algorithms validation." Water Science and Technology 39, no. 3 (1999): 77–92. http://dx.doi.org/10.2166/wst.1999.0141.

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An efficient and integrated approach for the study of overland transport of nitrate during runoff can be achieved by coupling water quality automatic monitoring and distributed parameter modeling. A semi-distributed model, essentially based upon a spatial discretization of the territory into square cells and upon a schematization of the main hydrological processes of erosion, transformation and transport of the chemical substances, was set up. It performs the lumped analysis of overland transport of nitrate (for the elementary cell of spatial discretization or experimental plot scale) and the
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HEGEDŰS, ISTVÁN, RÓBERT ORMÁNDI, and MÁRK JELASITY. "MASSIVELY DISTRIBUTED CONCEPT DRIFT HANDLING IN LARGE NETWORKS." Advances in Complex Systems 16, no. 04n05 (2013): 1350021. http://dx.doi.org/10.1142/s0219525913500215.

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Massively distributed data mining in large networks such as smart device platforms and peer-to-peer systems is a rapidly developing research area. One important problem here is concept drift, where global data patterns (movement, preferences, activities, etc.) change according to the actual set of participating users, the weather, the time of day, or as a result of events such as accidents or even natural catastrophes. In an important case — when the network is very large but only a few training samples can be obtained at each node locally — no efficient distributed solution is known that coul
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Kim, Seokhyun, and Yongsu Park. "DDR-Coin: An Efficient Probabilistic Distributed Trigger Counting Algorithm." Sensors 20, no. 22 (2020): 6446. http://dx.doi.org/10.3390/s20226446.

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A distributed trigger counting (DTC) problem is to detect w triggers in the distributed system consisting of n nodes. DTC algorithms can be used for monitoring systems using sensors to detect a significant global change. When designing an efficient DTC algorithm, the following goals should be considered; minimizing the whole number of exchanged messages used for counting triggers and even distribution of communication loads among nodes. In this paper, we present an efficient DTC algorithm, DDR-coin (Deterministic Detection of Randomly generated coins). The message complexity—the total number o
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Dissertations / Theses on the topic "Distributed Monitoring Algorithms"

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Pilourdault, Julien. "Scalable algorithms for monitoring activity traces." Thesis, Université Grenoble Alpes (ComUE), 2017. http://www.theses.fr/2017GREAM040/document.

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Dans cette thèse, nous étudions des algorithmes pour le monitoring des traces d’activité à grande échelle. Le monitoring est une aptitude clé dans plusieurs domaines, permettant d’extraire de la valeur des données ou d’améliorer les performances d’un système. Nous explorons d’abord le monitoring de données temporelles. Nous présentons un nouveau type de jointure sur des intervalles, qui inclut des fonctions de score caractérisant le degré de satisfaction de prédicats temporels. Nous étudions ces jointures dans le contexte du batch processing (traitement par lots). Nous formalisons la Ranked Te
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Cianci, Christopher Michael. "Distributed intelligent algorithms for robotic sensor networks monitoring discontinuous anisotropic environmental fields /." Lausanne : EPFL, 2009. http://library.epfl.ch/theses/?nr=4247.

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Thèse Ecole polytechnique fédérale de Lausanne EPFL, no 4247 (2009), Faculté informatique et communications IC, Programme doctoral Informatique, Communications et Information, Institut des sciences et technologies de l'environnement ISTE (Laboratoire de systèmes et algorithmes intelligents distribués DISAL). Dir.: Alcherio Martinoli.
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Sung, Minho. "Scalable and efficient distributed algorithms for defending against malicious Internet activity." Diss., Available online, Georgia Institute of Technology, 2006, 2006. http://etd.gatech.edu/theses/available/etd-07172006-134741/.

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Thesis (Ph. D.)--Computing, Georgia Institute of Technology, 2007.<br>Xu, Jun, Committee Chair ; Ahamad, Mustaque, Committee Member ; Ammar, Mostafa, Committee Member ; Bing, Benny, Committee Member ; Zegura, Ellen, Committee Member.
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Collet, Julien. "Exploration of parallel graph-processing algorithms on distributed architectures." Thesis, Compiègne, 2017. http://www.theses.fr/2017COMP2391/document.

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Avec l'explosion du volume de données produites chaque année, les applications du domaine du traitement de graphes ont de plus en plus besoin d'être parallélisées et déployées sur des architectures distribuées afin d'adresser le besoin en mémoire et en ressource de calcul. Si de telles architectures larges échelles existent, issue notamment du domaine du calcul haute performance (HPC), la complexité de programmation et de déploiement d’algorithmes de traitement de graphes sur de telles cibles est souvent un frein à leur utilisation. De plus, la difficile compréhension, a priori, du comportemen
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Fachini, Elizeu Elieber. "Um sistema de monitoramento para caracterização de algoritmos distribuídos." Universidade Federal de São Carlos, 2016. https://repositorio.ufscar.br/handle/ufscar/8251.

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Submitted by Milena Rubi (milenarubi@ufscar.br) on 2016-10-25T21:55:38Z No. of bitstreams: 1 FACHINI_Elizeu_2016.pdf: 7355773 bytes, checksum: 57880fc3ade64c5d25c3ec2901d87e9b (MD5)<br>Approved for entry into archive by Milena Rubi (milenarubi@ufscar.br) on 2016-10-25T21:55:54Z (GMT) No. of bitstreams: 1 FACHINI_Elizeu_2016.pdf: 7355773 bytes, checksum: 57880fc3ade64c5d25c3ec2901d87e9b (MD5)<br>Approved for entry into archive by Milena Rubi (milenarubi@ufscar.br) on 2016-10-25T21:56:04Z (GMT) No. of bitstreams: 1 FACHINI_Elizeu_2016.pdf: 7355773 bytes, checksum: 57880fc3ade64c5d25c3ec2901d
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Neggazi, Brahim. "Self-stabilizing algorithms for graph parameters." Thesis, Lyon 1, 2015. http://www.theses.fr/2015LYO10041/document.

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Le concept d'auto-stabilisation a été introduit par Dijkstra en 1973. Un système distribué est auto-stabilisant s'il peut démarrer de n'importe quelle configuration initiale et retrouver une configuration légitime en un temps fini par lui-même et sans aucune intervention extérieure. La convergence est également garantie lorsque le système est affecté par des fautes transitoires, ce qui en fait une approche élégante, non masquante, pour la tolérance aux pannes. L'auto-stabilisation a été étudiée dans divers domaines des systèmes distribués tels que les problèmes de synchronisation de l'horloge,
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O'Dwyer, Martin Joseph. "Implementation and appraisal of an in-fibre Bragg grating quasi-distributed health and usage monitoring system with applications to advanced materials." Thesis, Cranfield University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.341033.

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Peri, Sathya. "Efficient algorithms for monitoring distributed systems /." 2007. http://proquest.umi.com/pqdweb?did=1417818561&sid=12&Fmt=2&clientId=10361&RQT=309&VName=PQD.

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Yan, Jiaxiang. "Modeling, monitoring and optimization of discrete event systems using Petri nets." 2014. http://hdl.handle.net/1805/3874.

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Indiana University-Purdue University Indianapolis (IUPUI)<br>Yan, Jiaxiang. M.S.E.C.E., Purdue University, May 2013. Modeling, Monitoring and Optimization of Discrete Event Systems Using Petri Nets. Major Professor: Lingxi Li. In last decades, the research of discrete event systems (DESs) has attracts more and more attention because of the fast development of intelligent control strategies. Such control measures combine the conventional control strategies with discrete decision-making processes which simulate human decision-making processes. Due to the scale and complexity of common DESs, the
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Book chapters on the topic "Distributed Monitoring Algorithms"

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Barouti, Maria, Daniel Keren, Jacob Kogan, and Yaakov Malinovsky. "Clustering for Monitoring Distributed Data Streams." In Partitional Clustering Algorithms. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09259-1_12.

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Keren, Daniel, Guy Sagy, Amir Abboud, et al. "Monitoring Distributed, Heterogeneous Data Streams: The Emergence of Safe Zones." In Applied Algorithms. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04126-1_2.

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Melnik, E. V., M. V. Orda-Zhigulina, and D. V. Orda-Zhigulina. "Distributed Library Model Based on Distributed Ledger Technology for Monitoring and Diagnostics System." In Software Engineering and Algorithms. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77442-4_43.

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Serrano, Maria A., Erez Hadad, Roberto Cavicchioli, et al. "Distributed Big Data Analytics in a Smart City." In Technologies and Applications for Big Data Value. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78307-5_21.

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AbstractThis chapter describes an actual smart city use-case application for advanced mobility and intelligent traffic management, implemented in the city of Modena, Italy. This use case is developed in the context of the European Union’s Horizon 2020 project CLASS [4]—Edge and Cloud Computation: A highly Distributed Software for Big Data Analytics. This use-case requires both real-time data processing (data in motion) for driving assistance and online city-wide monitoring, as well as large-scale offline processing of big data sets collected from sensors (data at rest). As such, it demonstrate
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Masoudi, Pedram, Yvon Desnoyers, and Mike Grey. "Spatio-Temporal Optimization of Groundwater Monitoring Network at Pickering Nuclear Generating Station." In Springer Proceedings in Earth and Environmental Sciences. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-19845-8_15.

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AbstractThrough more than 400 wells, tritium leakage of Pickering Nuclear Generating Station has been monitored seasonally since 1999. Sampling and maintenance of monitoring wells being costly, it is required limiting number of samples while ensuring monitoring objectives. This study aims at proposing a geostatistical approach for sample reduction while meeting the monitoring objectives. So, four objectives were defined: (i) Geographical coverage. (ii) Denser sampling where tritium variability is high. (iii) Delimiting the threshold of 300 kBq/L, also (iv) the cut-off of 3000 kBq/L. These obje
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Sniatala, Pawel, M. Hadi Amini, and Kianoosh G. Boroojeni. "Robust Fault Tolerant Rail Door State Monitoring Systems." In Fundamentals of Brooks–Iyengar Distributed Sensing Algorithm. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-33132-0_6.

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Centelles, Roger Pueyo, Mennan Selimi, Felix Freitag, and Leandro Navarro. "A Monitoring System for Distributed Edge Infrastructures with Decentralized Coordination." In Algorithmic Aspects of Cloud Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58628-7_4.

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Casado-Vara, Roberto. "Blockchain-Based Distributed Cooperative Control Algorithm for WSN Monitoring." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-99608-0_56.

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Bendimerad, Nawel, Amal Boumedjout, and Bena Bot. "Distributed Algorithm for Area Monitoring in Directional Sensor Networks." In 12th International Conference on Information Systems and Advanced Technologies “ICISAT 2022”. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-25344-7_29.

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Bonakdarpour, Borzoo, Anik Momtaz, Dejan Ničković, and N. Ege Saraç. "Approximate Distributed Monitoring Under Partial Synchrony: Balancing Speed & Accuracy." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-74234-7_18.

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AbstractIn distributed systems with processes that do not share a global clock, partial synchrony is achieved by clock synchronization that guarantees bounded clock skew among all applications. Existing solutions for distributed runtime verification under partial synchrony against temporal logic specifications are exact but suffer from significant computational overhead. In this paper, we propose an approximate distributed monitoring algorithm for Signal Temporal Logic (STL) that mitigates this issue by abstracting away potential interleaving behaviors. This conservative abstraction enables a
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Conference papers on the topic "Distributed Monitoring Algorithms"

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Chen, Yiyi. "Distributed Financial Data Real-Time Monitoring System Based on Neural Network Algorithms." In 2024 Second International Conference on Networks, Multimedia and Information Technology (NMITCON). IEEE, 2024. http://dx.doi.org/10.1109/nmitcon62075.2024.10699200.

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Venkateswararao, Kuna, Gali Pavan Ratnam Nayudu, Jonnalagadda Balaji, J. N. V. R. Swarup Kumar, Irugu John Peter Noble, and K. E. Naresh Kumar. "Enhanced Sensor Fault Detection in Aquatic Monitoring using Deep Learning and Machine Learning Algorithms." In 2024 Eighth International Conference on Parallel, Distributed and Grid Computing (PDGC). IEEE, 2024. https://doi.org/10.1109/pdgc64653.2024.10984264.

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Christodoulou, Lakis, Andreas Chari, and Michael Georgiades. "AI-enhanced Healthcare IoT System: Advanced ML Detection and Classification Algorithms for Real-Time Cardiovascular Monitoring." In 2024 20th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT). IEEE, 2024. http://dx.doi.org/10.1109/dcoss-iot61029.2024.00071.

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Huang, Axin, Mary Jane C. Samonte, Xingyu Huang, and Zhilin Zhang. "Application Research of Emotion Analysis, Eye Tracking, and Head Movement Monitoring Based on Facial Recognition Algorithms in ESL Student Engagement Assessment." In 2024 5th International Conference on Information Science, Parallel and Distributed Systems (ISPDS). IEEE, 2024. http://dx.doi.org/10.1109/ispds62779.2024.10667641.

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Dumitrascu, Alexandru. "CONTROL SYSTEM FOR GREENHOUSES USING INDUSTRIAL NETWORKED DEVICES." In 24th SGEM International Multidisciplinary Scientific GeoConference 2024. STEF92 Technology, 2024. https://doi.org/10.5593/sgem2024/2.1/s07.05.

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The modern monitoring and control systems that are currently used in most fields are based on intelligent algorithms, distributed management systems, and a new generation of communication buses. For the monitoring and control of the processes inside a greenhouse, the use of sophisticated algorithms or complex devices is not required. However, to make the activity more efficient and increase the production of a greenhouse, a proposed solution is to use data management and control system such as PLC and HMI devices, which are interconnected using industrial bus and communication protocol � Profi
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van Hoestenberghe, Thomas, Timothy Van Caelenberghe, Niels De Vleeschouwer, Arnout Roukaerts, Daan Renders, and Timothy Van Caelenberghe. "Detection of Corrosion under Insulation Risks with Fiber Optic Technology." In CONFERENCE 2025. AMPP, 2025. https://doi.org/10.5006/c2025-00265.

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Abstract This paper describes a disruptive continuous monitoring system to detect Corrosion Under Insulation (CUI) risks for every meter of pipeline over large distances. Distributed Fiber Optic Sensing (DFOS) has emerged as a viable non-destructive ATEX-proof solution to detect CUI. The system uses a fiber optic cable applied at the outside of the cladding. From fiber optic readings and dedicated algorithms, the location and amount of corrosion are detected and localized with a spatial precision of 0.5 m. To evaluate the system effectiveness, plant operators conducted blind tests. The system
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Zhang, Jingqi. "Application of LSTM Algorithm in Motion Trajectory Monitoring System." In 2024 International Conference on Distributed Systems, Computer Networks and Cybersecurity (ICDSCNC). IEEE, 2024. https://doi.org/10.1109/icdscnc62492.2024.10939428.

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Dinu, Cristian-Mircea, Florin Pop, and Valentin Cristea. "Pattern Detection Model for Monitoring Distributed Systems." In 2011 13th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC). IEEE, 2011. http://dx.doi.org/10.1109/synasc.2011.22.

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Satzger, Benjamin, and Theo Ungerer. "Grouping Algorithms for Scalable Self-Monitoring Distributed Systems." In 2nd International ICST Conference on Autonomic Computing and Communication Systems. ICST, 2008. http://dx.doi.org/10.4108/icst.autonomics2008.4476.

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Griswold, Victor Jon. "Core algorithms for autonomous monitoring of distributed systems." In the 1991 ACM/ONR workshop. ACM Press, 1991. http://dx.doi.org/10.1145/122759.122762.

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