Thematische Bibliographien / Stream Processing System

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Auswahl der wissenschaftlichen Literatur zum Thema „Stream Processing System“

Autor: Grafiati

Veröffentlicht am 25. Mai 2024

Zuletzt aktualisiert am 31. Juli 2025

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Zeitschriftenartikel zum Thema "Stream Processing System"

Shuiying Yu, Shuiying Yu, Yinting Zheng Shuiying Yu, Fan Zhang Yinting Zheng, Hanhua Chen Fan Zhang, and Hai Jin Hanhua Chen. "TriJoin: A Time-Efficient and Scalable Three-Way Distributed Stream Join System." 網際網路技術學刊 24, no. 2 (2023): 475–85. http://dx.doi.org/10.53106/160792642023032402024.

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Stream join is one of the most fundamental operations in data stream processing applications. Existing distributed stream join systems can support efficient two-way join, which is a join operation between two streams. Based the two-way join, implementing a three-way join require to be split into double two-way joins, where the second two-way join needs to wait for the join result transmitted from the first two-way join. We show through experiments that such a design raises prohibitively high processing latency. To solve this problem, we propose TriJoin, a time-efficient three-way dist

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Arjun, Reddy Lingala. "Stream Processing Internals and Usecases." International Journal of Leading Research Publication 5, no. 4 (2024): 1–7. https://doi.org/10.5281/zenodo.14945841.

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Batch processing is widely used concept in data warehousing where many companies build analytical solutions deriving insights into their systems and building new products based on the analysis based on various aspects of the systems. The exponential growth of real-time data sources like IoT sensors, social media has necessitated systems capable of processing unbounded data streams with low latency, high throughput, and guaranteed correctness. Unlike batch processing, stream process- ing engines must handle continuous data flows with dynamic arrival patterns, out-of-order events, and variable w

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Shi, Peng, and Li Li. "Design of Network Analysis System Based on Stream Computing." Journal of Computational and Theoretical Nanoscience 14, no. 1 (2017): 64–68. http://dx.doi.org/10.1166/jctn.2017.6125.

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The functions of the network analysis system include detection and analysis of network data stream. According to the results of the network analysis, we monitor the network accident and avoid the security risks. This can improve the network performance and increase the network availability. As the data flow in the network is constantly produced, the biggest characteristic of network analysis system is that it is a real-time system. Because of the high requirements of the network data analysis and network fault processing, the system requires very high processing efficiency of the real time dat

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Valeev, S. S., N. V. Kondratyeva, A. S. Kovtunenko, M. A. Timirov, and R. R. Karimov. "Distributed stream data processing system in multi-agent safety system of infrastructure objects." Information Technology and Nanotechnology, no. 2416 (2019): 324–31. http://dx.doi.org/10.18287/1613-0073-2019-2416-324-331.

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The solution of the problem of resource management in distributed computing systems of processing stream data in safety systems of distributed objects is considered. The tasks of streaming data processing in a multi-level multi-agent evacuation system in an infrastructure object are considered. The features of the mathematical model of a distributed stream data processing system are discussed.

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EITER, THOMAS, PAUL OGRIS, and KONSTANTIN SCHEKOTIHIN. "A Distributed Approach to LARS Stream Reasoning (System paper)." Theory and Practice of Logic Programming 19, no. 5-6 (2019): 974–89. http://dx.doi.org/10.1017/s1471068419000309.

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AbstractStream reasoning systems are designed for complex decision-making from possibly infinite, dynamic streams of data. Modern approaches to stream reasoning are usually performing their computations using stand-alone solvers, which incrementally update their internal state and return results as the new portions of data streams are pushed. However, the performance of such approaches degrades quickly as the rates of the input data and the complexity of decision problems are growing. This problem was already recognized in the area of stream processing, where systems became distributed in orde

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Ye, Qian, and Minyan Lu. "s2p: Provenance Research for Stream Processing System." Applied Sciences 11, no. 12 (2021): 5523. http://dx.doi.org/10.3390/app11125523.

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The main purpose of our provenance research for DSP (distributed stream processing) systems is to analyze abnormal results. Provenance for these systems is not nontrivial because of the ephemerality of stream data and instant data processing mode in modern DSP systems. Challenges include but are not limited to an optimization solution for avoiding excessive runtime overhead, reducing provenance-related data storage, and providing it in an easy-to-use fashion. Without any prior knowledge about which kinds of data may finally lead to the abnormal, we have to track all transformations in detail,

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Park, Alfred J., Cheng-Hong Li, Ravi Nair, et al. "Towards flexible exascale stream processing system simulation." SIMULATION 88, no. 7 (2011): 832–51. http://dx.doi.org/10.1177/0037549711412981.

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Cho, Wonhyeong, Myeong-Seon Gil, Mi-Jung Choi, and Yang-Sae Moon. "Storm-based distributed sampling system for multi-source stream environment." International Journal of Distributed Sensor Networks 14, no. 11 (2018): 155014771881269. http://dx.doi.org/10.1177/1550147718812698.

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As a large amount of data streams occur rapidly in many recent applications such as social network service, Internet of Things, and smart factory, sampling techniques have attracted many attentions to handle such data streams efficiently. In this article, we address the performance improvement of binary Bernoulli sampling in the multi-source stream environment. Binary Bernoulli sampling has the n:1 structure where n sites transmit data to 1 coordinator. However, as the number of sites increases or the input stream explosively increases, the binary Bernoulli sampling may cause a severe bottlene

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Lin, Edgar Chia Han. "Research on Sequence Query Processing Techniques over Data Streams." Applied Mechanics and Materials 284-287 (January 2013): 3507–11. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.3507.

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Due to the great progress of computer technology and mature development of network, more and more data are generated and distributed through the network, which is called data streams. During the last couple of years, a number of researchers have paid their attention to data stream management, which is different from the conventional database management. At present, the new type of data management system, called data stream management system (DSMS), has become one of the most popular research areas in data engineering field. Lots of research projects have made great progress in this area. Since

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Endler, Markus, Jean-Pierre Briot, Vitor P. de Almeida, Ruhan dos Reis, and Francisco Silva e Silva. "Stream-Based Reasoning for IoT Applications — Proposal of Architecture and Analysis of Challenges." International Journal of Semantic Computing 11, no. 03 (2017): 325–44. http://dx.doi.org/10.1142/s1793351x1740013x.

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As distributed IoT applications become larger and more complex, the pure processing of raw sensor and actuation data streams becomes impractical. Instead, data streams must be fused into tangible facts and these pieces of information must be combined with a background knowledge to infer new pieces of knowledge. And since many IoT applications require almost real-time reactivity to stimulus of the environment, such information inference process has to be performed in a continuous, on-line manner. This paper proposes a new semantic model for data stream processing and real-time reasoning based o

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Dissertationen zum Thema "Stream Processing System"

Wladdimiro, Cottet Daniel. "Dynamic adaptation in Stream Processing Systems." Electronic Thesis or Diss., Sorbonne université, 2024. http://www.theses.fr/2024SORUS028.

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Le nombre de données produites par les systèmes ou applications Web actuels augmente rapidement en raison des nombreuses interactions avec les utilisateurs (dans le cadre par exemple, transactions boursières en temps réel, des jeux multijoueurs, des données en continu produits par Twitter, etc.). Ainsi, il existe une demande croissante, notamment dans les domaines du commerce, de la sécurité et de la recherche, pour des systèmes capables de traiter ces données en temps réel et de fournir des informations utiles dans un court laps de temps. Les systèmes de traitement des flux (SPS) répondent à

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Hongslo, Anders. "Stream Processing in the Robot Operating System framework." Thesis, Linköpings universitet, Artificiell intelligens och integrerad datorsystem, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-79846.

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Streams of information rather than static databases are becoming increasingly important with the rapid changes involved in a number of fields such as finance, social media and robotics. DyKnow is a stream-based knowledge processing middleware which has been used in autonomous Unmanned Aerial Vehicle (UAV) research. ROS (Robot Operating System) is an open-source robotics framework providing hardware abstraction, device drivers, communication infrastructure, tools, libraries as well as other functionalities. This thesis describes a design and a realization of stream processing in ROS based on th

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Kakkad, Vasvi. "Curracurrong: a stream processing system for distributed environments." Thesis, The University of Sydney, 2014. http://hdl.handle.net/2123/12861.

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Advances in technology have given rise to applications that are deployed on wireless sensor networks (WSNs), the cloud, and the Internet of things. There are many emerging applications, some of which include sensor-based monitoring, web traffic processing, and network monitoring. These applications collect large amount of data as an unbounded sequence of events and process them to generate a new sequences of events. Such applications need an adequate programming model that can process large amount of data with minimal latency; for this purpose, stream programming, among other paradigms, is ide

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Tokmouline, Timur. "A signal oriented stream processing system for pipeline monitoring." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/37106.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006. Includes bibliographical references (p. 115-117). In this thesis, we develop SignalDB, a framework for composing signal processing applications from primitive stream and signal processing operators. SignalDB allows the user to focus on the signal processing task and avoid needlessly spending time on learning a particular application programming interface (API). We use SignalDB to express acoustic and pressure transient methods for water pipeline monitoring as query plans c

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Robakowski, Mikolaj. "Comparison of State Backends for Modern Stream Processing System." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-290597.

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Distributed Stream Processing is a very popular computing paradigm used invarious modern computer systems. An important aspect of distributed streamprocessing systems is how they deal with computation state bigger than thesystem memory. This is often solved by the usage of a state backend – adatabase, usually an embedded one, that manages the state on the persistentstorage. However, this makes the performance of the whole system dependanton the performance of the database under the given workload. Log-structuredmerge-tree-based solutions are commonly used in stream processing systemsas a one-s

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Mousavi, Bamdad. "Scalable Stream Processing and Management for Time Series Data." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42295.

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There has been an enormous growth in the generation of time series data in the past decade. This trend is caused by widespread adoption of IoT technologies, the data generated by monitoring of cloud computing resources, and cyber physical systems. Although time series data have been a topic of discussion in the domain of data management for several decades, this recent growth has brought the topic to the forefront. Many of the time series management systems available today lack the necessary features to successfully manage and process the sheer amount of time series being generated today. In t

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Balazinska, Magdalena. "Fault-tolerance and load management in a distributed stream processing system." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/35287.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2006. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Includes bibliographical references (p. 187-199). Advances in monitoring technology (e.g., sensors) and an increased demand for online information processing have given rise to a new class of applications that require continuous, low-latency processing of large-volume data streams. These "stream processing application

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Ahmed, Abdulbasit. "Online network intrusion detection system using temporal logic and stream data processing." Thesis, University of Liverpool, 2013. http://livrepository.liverpool.ac.uk/12153/.

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These days, the world is becoming more interconnected, and the Internet has dominated the ways to communicate or to do business. Network security measures must be taken to protect the organization environment. Among these security measures are the intrusion detection systems. These systems aim to detect the actions that attempt to compromise the confidentiality, availability, and integrity of a resource by monitoring the events occurring in computer systems and/or networks. The increasing amounts of data that are transmitted at higher and higher speed networks created a challenging problem for

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Al-Sinayyid, Ali. "JOB SCHEDULING FOR STREAMING APPLICATIONS IN HETEROGENEOUS DISTRIBUTED PROCESSING SYSTEMS." OpenSIUC, 2020. https://opensiuc.lib.siu.edu/dissertations/1868.

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The colossal amounts of data generated daily are increasing exponentially at a never-before-seen pace. A variety of applications—including stock trading, banking systems, health-care, Internet of Things (IoT), and social media networks, among others—have created an unprecedented volume of real-time stream data estimated to reach billions of terabytes in the near future. As a result, we are currently living in the so-called Big Data era and witnessing a transition to the so-called IoT era. Enterprises and organizations are tackling the challenge of interpreting the enormous amount of raw data

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Addimando, Alessio. "Progettazione di un intrusion detection system su piattaforma big data." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/16755/.

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Negli ultimi anni, nel panorama digitale, è stato rilevato un ingente aumento del numero di dispositivi e utenti con accesso ad Internet. Proporzionalmente a questi fattori ogni giorno vengono generati continuamente, e in qualsiasi contesto, grandi quantità di dati difficili da gestire. Questo ha fatto emergere la necessità di riorganizzare gli asset aziendali per far fronte ad un calibro di informazione maggiore e per far in modo che la gestione stessa ne estragga valore concreto per la realtà decisionale. L'insieme di queste motivazioni da vita al fenomeno dei Big Data. Affiancato a ques

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Bücher zum Thema "Stream Processing System"

Fredericks, Jeffrey W. Decision support system for conjunctive stream-aquifer management. Colorado Water Resources Research Institute, 1995.

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Babbitt, Ronald E. Improved streamflow and water quality monitoring using a microprocessor-based system. U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1987.

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Babbitt, Ronald E. Improved streamflow and water quality monitoring using a microprocessor-based system. U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1987.

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IFIP World Computer Congress (17th 2002 Montreál, Québec). Intelligent information processing: IFIP 17th World Computer Congress-TC12 stream on intelligent information processing, August 25-30, 2002, Montreál, Québec, Canada. Kluwer Academic, 2002.

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Corporation, International Business Machines, ed. IBM Infosphere Streams harnessing data in motion. Vervante, 2010.

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Lane, Norman E. Users manual for the Automated Performance Test System (APTS). Essex Corp., 1990.

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International Business Machines Corporation. International Technical Support Organization, ed. IBM InfoSphere Streams: Assembling continuous insight in the information revolution. IBM Corp., International Technical Support Organization, 2011.

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A, Hemstrom Miles, and Pacific Northwest Research Station (Portland, Or.), eds. Midscale analysis of streamside characteristics in the upper Grande Ronde subbasin, northeastern Oregon. U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station, 2002.

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Krivoyekov, Syergyey, and Roman Ayzman. Psychophysiology. INFRA-M Academic Publishing LLC., 2015. http://dx.doi.org/10.12737/10884.

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Psychophysiology — the science studying interrelation of mentality of the person and physiological processes. Fundamental knowledge of work of a brain, first of all, of nervous regulation of functions of an organism, the general and specific features of the highest falls within the scope of its interests nervous activity, the defining character and behavior of the person, psychophysiological mechanisms of regulation of functional states. In the book neurophysiological bases of coding and information processing in nervous system, neural mechanisms of feelings, perceptions, mem

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Conference, Ontario Educational Research Council. [Papers presented at the 31st Annual Conference of the Ontario Educational Research Council, Toronto, Ontario, December 8-9, 1989]. s.n.], 1989.

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Buchteile zum Thema "Stream Processing System"

Gorawski, Marcin, Pawel Marks, and Michal Gorawski. "Modeling Data Stream Intensity in Distributed Stream Processing System." In Computer Networks. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38865-1_38.

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Gilani, Altaf, Satyajeet Sonune, Balakumar Kendai, and Sharma Chakravarthy. "The Anatomy of a Stream Processing System." In Flexible and Efficient Information Handling. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11788911_20.

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Le, Jia-jin, and Jian-wei Liu. "DDSQP: A WSRF-Based Distributed Data Stream Query System." In Parallel and Distributed Processing and Applications. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11576235_83.

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Zrilic, Djuro G. "A Δ-Σ Digital Amplitude Modulation System." In Functional Processing of Delta-Sigma Bit-Stream. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-47648-9_8.

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Nishii, Shunsuke, and Toyotaro Suzumura. "Highly Scalable Speech Processing on Data Stream Management System." In Database Systems for Advanced Applications. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29035-0_14.

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Wang, Xiaotong, Junhua Fang, Yuming Li, Rong Zhang, and Aoying Zhou. "Cost-Effective Data Partition for Distributed Stream Processing System." In Database Systems for Advanced Applications. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-55699-4_39.

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Zrilic, Djuro G. "A Δ-Σ Digital Stereo Multiplexing–Demultiplexing System." In Functional Processing of Delta-Sigma Bit-Stream. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-47648-9_7.

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Zou, Beiji, Tao Zhang, Chengzhang Zhu, Ling Xiao, Meng Zeng, and Zhi Chen. "Alps: An Adaptive Load Partitioning Scaling Solution for Stream Processing System on Skewed Stream." In Lecture Notes in Computer Science. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-12426-6_2.

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Jiang, Jiawei, Zhipeng Zhang, Bin Cui, Yunhai Tong, and Ning Xu. "StroMAX: Partitioning-Based Scheduler for Real-Time Stream Processing System." In Database Systems for Advanced Applications. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-55699-4_17.

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Srinii, Vason P., John Thendean, and Jan M. Rabaey. "Reconfigurable Memory Module in the RAMP System for Stream Processing." In High Performance Memory Systems. Springer New York, 2004. http://dx.doi.org/10.1007/978-1-4419-8987-1_8.

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Konferenzberichte zum Thema "Stream Processing System"

Park, Alfred J., Cheng-Hong Li, Ravi Nair, et al. "Flow: A Stream Processing System Simulator." In 2010 IEEE 24th Workshop on Principles of Advanced and Distributed Simulation (PADS 2010). IEEE, 2010. http://dx.doi.org/10.1109/pads.2010.5471658.

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Lee, Myungcheol, Miyoung Lee, Sung Jin Hur, and Ikkyun Kim. "Load adaptive distributed stream processing system for explosive stream data." In 2015 17th International Conference on Advanced Communication Technology (ICACT). IEEE, 2015. http://dx.doi.org/10.1109/icact.2015.7224896.

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Kwon, Oje, Yong-Soo Song, Jae-Hun Kim, and Ki-Joune Li. "SCONSTREAM: A Spatial Context Stream Processing System." In 2010 International Conference on Computational Science and Its Applications. IEEE, 2010. http://dx.doi.org/10.1109/iccsa.2010.48.

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Körber, Michael, Jakob Eckstein, Nikolaus Glombiewski, and Bernhard Seeger. "Event Stream Processing on Heterogeneous System Architecture." In the 15th International Workshop. ACM Press, 2019. http://dx.doi.org/10.1145/3329785.3329933.

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Michalak, Peter, and Paul Watson. "PATH2iot: A Holistic, Distributed Stream Processing System." In 2017 IEEE International Conference on Cloud Computing Technology and Science (CloudCom). IEEE, 2017. http://dx.doi.org/10.1109/cloudcom.2017.35.

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Wladdimiro, Daniel, Luciana Arantes, Pierre Sens, and Nicolas Hidalgo. "A Multi-Metric Adaptive Stream Processing System." In 2021 IEEE 20th International Symposium on Network Computing and Applications (NCA). IEEE, 2021. http://dx.doi.org/10.1109/nca53618.2021.9685871.

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"ITAIPU DATA STREAM MANAGEMENT SYSTEM - A Stream Processing System with Business Users in Mind." In 3rd International Conference on Software and Data Technologies. SciTePress - Science and and Technology Publications, 2008. http://dx.doi.org/10.5220/0001882000540064.

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Wang, Shengxiang, Hansheng Lu, Zhiyun Gao, and Shanfeng Hou. "Multifunctional video stream processing system based on DSP." In Photonics Asia 2002, edited by LiWei Zhou, Chung-Sheng Li, and Yoshiji Suzuki. SPIE, 2002. http://dx.doi.org/10.1117/12.481567.

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Alves de Souza Ramos, Thatyene Louise, Rodrigo Silva Oliveira, Ana Paula de Carvalho, Renato Antonio Celso Ferreira, and Wagner Meira Jr. "Watershed: A High Performance Distributed Stream Processing System." In 2011 23rd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD). IEEE, 2011. http://dx.doi.org/10.1109/sbac-pad.2011.31.

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Vogler, Michael, Johannes M. Schleicher, Christian Inzinger, Bernhard Nickel, and Schahram Dustdar. "Non-intrusive Monitoring of Stream Processing Applications." In 2016 IEEE Symposium on Service-Oriented System Engineering (SOSE). IEEE, 2016. http://dx.doi.org/10.1109/sose.2016.11.

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Berichte der Organisationen zum Thema "Stream Processing System"

Alchanatis, Victor, Stephen W. Searcy, Moshe Meron, W. Lee, G. Y. Li, and A. Ben Porath. Prediction of Nitrogen Stress Using Reflectance Techniques. United States Department of Agriculture, 2001. http://dx.doi.org/10.32747/2001.7580664.bard.

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Commercial agriculture has come under increasing pressure to reduce nitrogen fertilizer inputs in order to minimize potential nonpoint source pollution of ground and surface waters. This has resulted in increased interest in site specific fertilizer management. One way to solve pollution problems would be to determine crop nutrient needs in real time, using remote detection, and regulating fertilizer dispensed by an applicator. By detecting actual plant needs, only the additional nitrogen necessary to optimize production would be supplied. This research aimed to develop techniques for real tim

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Christopher, David A., and Avihai Danon. Plant Adaptation to Light Stress: Genetic Regulatory Mechanisms. United States Department of Agriculture, 2004. http://dx.doi.org/10.32747/2004.7586534.bard.

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Original Objectives: 1. Purify and biochemically characterize RB60 orthologs in higher plant chloroplasts; 2. Clone the gene(s) encoding plant RB60 orthologs and determine their structure and expression; 3. Manipulate the expression of RB60; 4. Assay the effects of altered RB60 expression on thylakoid biogenesis and photosynthetic function in plants exposed to different light conditions. In addition, we also examined the gene structure and expression of RB60 orthologs in the non-vascular plant, Physcomitrella patens and cloned the poly(A)-binding protein orthologue (43 kDa RB47-like protein).

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Ron, Eliora, and Eugene Eugene Nester. Global functional genomics of plant cell transformation by agrobacterium. United States Department of Agriculture, 2009. http://dx.doi.org/10.32747/2009.7695860.bard.

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The aim of this study was to carry out a global functional genomics analysis of plant cell transformation by Agrobacterium in order to define and characterize the physiology of Agrobacterium in the acidic environment of a wounded plant. We planed to study the proteome and transcriptome of Agrobacterium in response to a change in pH, from 7.2 to 5.5 and identify genes and circuits directly involved in this change. Bacteria-plant interactions involve a large number of global regulatory systems, which are essential for protection against new stressful conditions. The interaction of bacteria with

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Steffens, John C., and Eithan Harel. Polyphenol Oxidases- Expression, Assembly and Function. United States Department of Agriculture, 1995. http://dx.doi.org/10.32747/1995.7571358.bard.

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Polyphenol oxidases (PPOs) participate in the preparation of many plant products on the one hand and cause considerable losses during processing of plant products on the other hand. However, the physiological functions of plant PPO were still a subject of controversy at the onset of the project. Preliminary observations that suggested involvement of PPOs in resistance to herbivores and pathogens held great promise for application in agriculture but required elucidation of PPO's function if modulation of PPO expression is to be considered for improving plant protection or storage and processing

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