Relevant bibliographies by topics / Distributed

Contents

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

Academic literature on the topic 'Distributed'

Author: Grafiati
Published: 4 June 2021
Last updated: 8 June 2024

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Journal articles on the topic "Distributed"

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Burton, A. Mike. "The many ways to distribute distributed representations." Behavioral and Brain Sciences 23, no. 4 (August 2000): 472–73. http://dx.doi.org/10.1017/s0140525x00273354.

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Distributed representations can be distributed in very many ways. The specific choice of representation for a specific model is based on considerations unique to the area of study. General statements about the effectiveness of distributed models are therefore of little value. The popularity of these models is discussed, particularly with respect to reporting conventions.
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Fox, Peter T., and Karl J. Friston. "Distributed processing; distributed functions?" NeuroImage 61, no. 2 (June 2012): 407–26. http://dx.doi.org/10.1016/j.neuroimage.2011.12.051.

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Takamura, Seishi. "Distributed Video Coding." Journal of the Institute of Image Information and Television Engineers 61, no. 4 (2007): 443–46. http://dx.doi.org/10.3169/itej.61.443.

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Pester, Andreas, and Thomas Klinger. "Distributed Experiments and Distributed Learning." International Journal of Online and Biomedical Engineering (iJOE) 16, no. 06 (May 28, 2020): 19. http://dx.doi.org/10.3991/ijoe.v16i06.13661.

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The paper, an enhanced version of conference key presentation, investigates, how the development of new needs in education and developments in IT triggered technology enhanced learning. Online labs play an important in that area. Federation of labs is the new direction to answer the challenges, which come from the intensive use of online labs in the modern learning environments. VISIR Federation is a concrete attempt to implement such a federation. Distributed labs in a federation need commitments from the participants in organization, sharing lab and learning resources.
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Giere, Ronald N. "Distributed Cognition without Distributed Knowing." Social Epistemology 21, no. 3 (July 2007): 313–20. http://dx.doi.org/10.1080/02691720701674197.

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Fiore, Stephen M., Haydee M. Cuevas, Eduardo Salas, and Jonathan W. Schooler. "Distributed Teams and Distributed Memory." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 46, no. 3 (September 2002): 398–402. http://dx.doi.org/10.1177/154193120204600339.

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The nature of teams is changing in that the implementation of distributed teams as a definable organizational unit has substantially increased. In this paper we discuss a portion of the cognitive processes potentially impacting distributed team performance. We elaborate on how team opacity arising from distributed interaction can impact team cognition, with an emphasis on the critical memory components that are foundational to the development and implementation of shared mental models.
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Mukhopadhyay, Snehasis. "Distributed control and distributed computing." ACM SIGAPP Applied Computing Review 7, no. 1 (April 1999): 23–24. http://dx.doi.org/10.1145/570150.570157.

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McLeod, Poppy Lauretta. "Distributed People and Distributed Information." Small Group Research 44, no. 6 (September 5, 2013): 627–57. http://dx.doi.org/10.1177/1046496413500696.

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Harnad, Stevan, and Itiel E. Dror. "Distributed cognition." Distributed Cognition 14, no. 2 (September 21, 2006): 209–13. http://dx.doi.org/10.1075/pc.14.2.03har.

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Some of the papers in this Special Issue distribute cognition between what is going on inside individual cognizers’ heads and their outside worlds; others distribute cognition among different individual cognizers. Turing’s criterion for cognition was for individual, autonomous input/output capacity. It is not clear that distributed cognition could pass the Turing Test.
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Kojima, Hiroshi, Tohru Katsuno, Yosuke Nakanishi, Yoshikazu Fukuyama, Hideki Matsuda, and Yasuhisa Kanazawa. "E202 AN INTRODUCTION EFFECT EVALUATION TOOL FOR DISTRIBUTED GENERATORS(Distributed Energy System-3)." Proceedings of the International Conference on Power Engineering (ICOPE) 2009.2 (2009): _2–371_—_2–376_. http://dx.doi.org/10.1299/jsmeicope.2009.2._2-371_.

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Dissertations / Theses on the topic "Distributed"

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Krysiak, Bruce R. (Bruce Robert). "Distributed tools for distributed thought : networked StarLogo." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/36586.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.
Includes bibliographical references (leaves 42-43).
by Bruce R. Krysiak.
M.Eng.
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Dixon, Eric Richard. "Developing distributed applications with distributed heterogenous databases." Thesis, Virginia Tech, 1993. http://hdl.handle.net/10919/42748.

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Hsu, Ing-Miin. "Distributed rule monitoring in distributed active databases /." The Ohio State University, 1993. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487841975356679.

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Christakos, Constantine Kleomenis 1974. "Distributed-in/ distributed-out sensor networks : a new framework to analyze distributed phenomena." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/34183.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2006.
Includes bibliographical references (p. 155-165).
With a new way of thinking about organizing sensor networks, we demonstrate that we can more easily deploy and program these networks to solve a variety of different problems. We describe sensor networks that can analyze and actuate distributed phenomena without a central coordinator. Previous implementations of sensor networks have approached the problem from the perspective of centralized reporting of distributed events. By contrast, we create a system that allows users to infer the global state from within the sensor network itself, rather than by accessing an outside, central middleware layer. This is accomplished via dynamic creation of clusters of nodes based on application or intent, rather than proximity. The data collected and returned by these clusters is returned directly to the inquirer at his current location. By creating this Distributed-in/Distributed-out (DiDo) system that bypasses a middleware layer, our networks have the principal advantage of being easily configurable and deployable. We show that a system with this structure can solve path problems in a random graph. These graph problems are directly applicable to real-life applications such as discovering escape routes for people in a building with changing pathways. We show that the system is scalable, as reconfiguration requires only local communication.
(cont.) To test our assumptions, we build a suite of applications to create different deployment scenarios that model the physical world and set up simulations that allow us to measure performance. Finally, we create a set of simple primitives that serve as a high-level organizing protocol. These primitives can be used to solve different problems with distributed sensors, regardless of the underlying network protocols. The instructions provided by the sensors result in tangible performance improvements when the sensors' instructions are directed to agents within a simulated physical world.
by Constantine Kleomenis Christakos.
Ph.D.
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Wasif, Malik. "A Distributed Namespace for a Distributed File System." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-101482.

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Due to the rapid growth of data in recent years, distributed file systems have gained widespread adoption. The new breed of distributed file systems reliably store petabytes of data on commodity hardware, and also provide rich abstractions for massively parallel data analytics. The Hadoop Distributed File System (HDFS) is one such system which provides the storage layer for MapReduce, Hive, HBase and Mahout. The metadata server in HDFS, called the NameNode, is a centralized server which stores information about the whole namespace. The centralized architecture not only makes the NameNode a bottleneck and a single-point-of-failure, but also restricts the overall capacity of the filesystem. To solve the availability and scalability issues of HDFS, a new architecture is required. In this report, we propose a distributed implementation of the HDFS NameNode, where the filesystem metadata is stored in a distributed, in-memory, replicated database called MySQL Cluster. The NameNodes are state-less, and the throughput of the system can be increased by either adding NameNodes, or by adding more data nodes in NDB. HDFS clients can access the metadata by connecting to any one of the NameNodes. The evaluation section shows that the new architecture, as compared to HDFS, can handle more requests per second, store ten times more files and recover from failures within a few seconds.
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Bennett, John K. "Distributed Smalltalk : inheritance and reactiveness in distributed systems /." Thesis, Connect to this title online; UW restricted, 1988. http://hdl.handle.net/1773/6923.

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Calabrese, Chris M. Eng Massachusetts Institute of Technology. "Distributed inference : combining variational inference with distributed computing." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/85407.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 95-97).
The study of inference techniques and their use for solving complicated models has taken off in recent years, but as the models we attempt to solve become more complex, there is a worry that our inference techniques will be unable to produce results. Many problems are difficult to solve using current approaches because it takes too long for our implementations to converge on useful values. While coming up with more efficient inference algorithms may be the answer, we believe that an alternative approach to solving this complicated problem involves leveraging the computation power of multiple processors or machines with existing inference algorithms. This thesis describes the design and implementation of such a system by combining a variational inference implementation (Variational Message Passing) with a high-level distributed framework (Graphlab) and demonstrates that inference is performed faster on a few large graphical models when using this system.
by Chris Calabrese.
M. Eng.
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Norcross, Stuart John. "Deriving distributed garbage collectors from distributed termination algorithms." Thesis, University of St Andrews, 2004. http://hdl.handle.net/10023/14986.

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This thesis concentrates on the derivation of a modularised version of the DMOS distributed garbage collection algorithm and the implementation of this algorithm in a distributed computational environment. DMOS appears to exhibit a unique combination of attractive characteristics for a distributed garbage collector but the original algorithm is known to contain a bug and, previous to this work, lacks a satisfactory, understandable implementation. The relationship between distributed termination detection algorithms and distributed garbage collectors is central to this thesis. A modularised DMOS algorithm is developed using a previously published distributed garbage collector derivation methodology that centres on mapping centralised collection schemes to distributed termination detection algorithms. In examining the utility and suitability of the derivation methodology, a family of six distributed collectors is developed and an extension to the methodology is presented. The research work described in this thesis incorporates the definition and implementation of a distributed computational environment based on the ProcessBase language and a generic definition of a previously unimplemented distributed termination detection algorithm called Task Balancing. The role of distributed termination detection in the DMOS collection mechanisms is defined through a process of step-wise refinement. The implementation of the collector is achieved in two stages; the first stage defines the implementation of two distributed termination mappings with the Task Balancing algorithm; the second stage defines the DMOS collection mechanisms.
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Yeager, Philip S. "A distributed file system for distributed conferencing system." [Gainesville, Fla.] : University of Florida, 2003. http://purl.fcla.edu/fcla/etd/UFE0001123.

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Rieutord, Thibault. "Combinatorial characterization of asynchronous distributed computability." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLT007.

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Les systèmes informatiques modernes sont des systèmes distribués, allant de multiples processeurs sur une même puce à des systèmes internet de large échelle. Dans cette thèse nous étudions les problèmes de calculabilité et de complexité dans les systèmes distribués asynchrones communiquant par mémoire partagée.Dans la première et majeure partie de cette thèse, nous étudions la capacité des modèles communiquant par mémoire partagée à résoudre des tâches distribuées. Notre première contribution est une technique de simulation distribuée utilisant la capacité d’accord du système afin de synchroniser les différents processus entre eux. Cette technique de simulation permet de comparer la capacité de différents modèles à résoudre des tâches distribuées. À l’aide de cet outil, nous montrons que pour les modèles d’adversaires en mémoire partagée, la capacité à résoudre un ensemble particulier de tâches d’accord permet de déterminer sa capacité à résoudre n’importe quelle tâche distribuée. Nous utilisons ensuite les outils issus de la topologie combinatoire afin de caractériser la calculabilité des modèles par le biais de tâches affines: des complexes simpliciaux extraits d’itérations finies de la sous-division colorée standard. Cette caractérisation s’applique aux modèles dits sans-attente avec accès à des objets de “k-test-and-set” ainsi qu’à un large ensemble de modèles d’adversaires en mémoire partagée dits équitables. Ces résultats généralisent et améliorent toutes les caractérisations topologiques connues de la capacité à résoudre des tâches pour les modèles communiquant par mémoire partagée.Dans la seconde partie de la thèse, nous étudions la complexité spatiale de l’implémentation d’un stockage fiable, c.à.d., assurant qu’une valeur écrite en mémoire est persistante, dans le modèle à base de comparaison où seuls les identifiants peuvent être comparés. Nos résultats montrent l’existence d’un compromis non-trivial entre la complexité spatiale d’une implémentation et les garanties de vivacité qu’elle apporte
Modern computing systems are distributed, ranging from single-chip multi-processors to large-scale internet systems. In this thesis, we study computability and complexity issues raising in asynchronous crash-prone shared memory systems.The major part of this thesis is devoted to characterizing the power of a shared memory model to solve distributed tasks. Our first contribution is a refined and extended agreement-based simulation technique that allows us to reason about the relative task computability of shared-memory models. Using this simulation technique, we show that the task computability of a shared-memory adversarial model is grasped by its ability to solve specific agreement tasks. We then use the language of combinatorial topology to characterize the task computability of shared-memory models via affine tasks: sub-complexes of a finite iteration of the standard chromatic subdivision. Our characterization applies to the wait-free model enhanced with k-test-and-set objects and a to large class of fair adversarial models. These results generalize and improve all previously derived topological characterizations of the task computability power of shared memory models.In the second part of the thesis, we focus on space complexity of implementing stable storage, i.e., ensuring that written values persists in memory, in the comparison-based model using multi-writer registers. Our results exhibit a non-trivial tradeoff between space complexity of stable-storage implementations and the progress guarantees they provide
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Books on the topic "Distributed"

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Rolia, Jerome, Jacob Slonim, and John Botsford, eds. Open Distributed Processing and Distributed Platforms. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-0-387-35188-9.

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Postavsky, Uri. Distributed compilation using distributed shared memory. Ottawa: National Library of Canada = Bibliothèque nationale du Canada, 1991.

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Postavsky, Uri. Distributed compilation using distributed shared memory. Toronto: University of Toronto, Dept. of Computer Science, 1990.

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Mullender, Sape, ed. Distributed systems. New York, NY, USA: ACM, 1990. http://dx.doi.org/10.1145/90417.

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Dror, Itiel E., and Stevan Harnad, eds. Cognition Distributed. Amsterdam: John Benjamins Publishing Company, 2008. http://dx.doi.org/10.1075/bct.16.

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Cowley, Stephen J., ed. Distributed Language. Amsterdam: John Benjamins Publishing Company, 2011. http://dx.doi.org/10.1075/bct.34.

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Alstein, Dick. Distributed algorithms. Eindhoven: University of Eindhoven, 1996.

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Oblinger, Diana G. Distributed learning. Boulder, Colo: CAUSE, 1996.

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Lushetich, Natasha, and Iain Campbell. Distributed Perception. London: Routledge, 2021. http://dx.doi.org/10.4324/9781003157021.

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Moses, Yoram, ed. Distributed Computing. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-48653-5.

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Book chapters on the topic "Distributed"

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Bless, Marc. "Distributed Meetings in Distributed Teams." In Lecture Notes in Business Information Processing, 251–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13054-0_27.

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Abadi, Martín, Mike Burrows, Himabindu Pucha, Adam Sadovsky, Asim Shankar, and Ankur Taly. "Distributed Authorization with Distributed Grammars." In Programming Languages with Applications to Biology and Security, 10–26. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25527-9_3.

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Prinz, Andreas. "Distributed Computing on Distributed Memory." In System Analysis and Modeling. Languages, Methods, and Tools for Systems Engineering, 67–84. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01042-3_5.

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Cowley, Stephen J. "Distributed language." In Distributed Language, 1–14. Amsterdam: John Benjamins Publishing Company, 2011. http://dx.doi.org/10.1075/bct.34.01cow.

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Dron, Jon. "Distributed Teaching." In Encyclopedia of Teacher Education, 1–6. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-1179-6_109-1.

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Yokoo, Makoto. "Distributed Breakout." In Distributed Constraint Satisfaction, 81–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-59546-2_5.

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Pickering, Robert, and Kit Eason. "Distributed Applications." In Beginning F# 4.0, 223–40. Berkeley, CA: Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-1374-2_10.

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Loper, Margaret L. "Distributed Simulation." In Modeling and Simulation in the Systems Engineering Life Cycle, 241–53. London: Springer London, 2015. http://dx.doi.org/10.1007/978-1-4471-5634-5_20.

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Aragues, Rosario, Carlos Sagues, and Youcef Mezouar. "Distributed Localization." In Parallel and Distributed Map Merging and Localization, 37–64. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25886-7_3.

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Raynal, Michel, Julien Stainer, and Gadi Taubenfeld. "Distributed Universality." In Lecture Notes in Computer Science, 469–84. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-14472-6_31.

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Conference papers on the topic "Distributed"

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Avijit, Kumar, Anupam Datta, and Robert Harper. "Distributed programming with distributed authorization." In the 5th ACM SIGPLAN workshop. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1708016.1708021.

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Eichhorn, Leo, Tanya Shreedhar, Aleksandr Zavodovski, and Nitinder Mohan. "Distributed Ledgers for Distributed Edge." In CoNEXT '21: The 17th International Conference on emerging Networking EXperiments and Technologies. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3488663.3493687.

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Redmond, John A., Isabel Czarnocki, Jonathan Luntz, Diann Brei, and Andrew Enke. "Active Distributed Attachment Surfaces: Distributed Latching Technique and Demonstration." In ASME 2012 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/smasis2012-8237.

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Latches are essential mechanical elements used to controllably connect multiple bodies throughout industry. Latches conventionally attach bodies at a single point or at a few discrete points, and are designed for multiple operation cycles. Actuator controlled latches, minimize the amount of complexity and costs involved with installation and removal by making the attachment between structures controllable, tool-free and fast. However, the use of multiple single point fasteners carries additional part count, material costs, and labor associated with installation and removal, and can creating load concentrations at attachment sites. Alternatively, surface attachments, such as traditional hook and loop mechanisms, distribute structural connection over an area or across many points reducing stress concentrations, allowing engagement of multiple bodies, maintaining structural connections in nonspecific locations and orientations and reducing labor costs to install and detach bodies. However, performance limitations of conventional surface attachments, such as low retention force, restrict potential applications. An active distributed attachment technique has the potential to increase the performance of conventional distributed attachments, as well as overcome the complexity and operation of conventional point attachments. This paper introduces three active distributed latch approaches (Pegboard, Interlocking Teeth, and Active Velcro) that utilize lightweight, compact SMA actuation. Proof-of-concept prototypes were built, and tested experimentally to investigate the engagement, retention, and release performance. The best performing of the three is demonstrated in a full application scale. The first generation prototypes improved upon the performance of conventional surface attachments and show promise in maintaining the necessary structural attachment for industrial applications.
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Fermann, Carla J. "Distributed consulting in a distributed environment." In the 18th annual ACM SIGUCCS conference. New York, New York, USA: ACM Press, 1990. http://dx.doi.org/10.1145/99186.99220.

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Ryu, Kunhee, and Juhoon Back. "Distributed Kalman-filtering: Distributed optimization viewpoint." In 2019 IEEE 58th Conference on Decision and Control (CDC). IEEE, 2019. http://dx.doi.org/10.1109/cdc40024.2019.9029645.

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Mao, Mengjie, Hong An, Bobin Deng, Tao Sun, Xuechao Wei, Wei Zhou, and Wenting Han. "Distributed replay protocol for distributed uniprocessors." In the 26th ACM international conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2304576.2304580.

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Zhu, Lijun, Yifan Zeng, and Mengmou Li. "Distributed Formation Control via Distributed Optimization." In 2022 IEEE 17th International Conference on Control & Automation (ICCA). IEEE, 2022. http://dx.doi.org/10.1109/icca54724.2022.9831891.

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Chong, Chee-Yee, Kuo-Chu Chang, and Shozo Mori. "Distributed Tracking in Distributed Sensor Networks." In 1986 American Control Conference. IEEE, 1986. http://dx.doi.org/10.23919/acc.1986.4789229.

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Chiu, Chuan-Feng, Steen J. Hsu, and Sen-Ren Jan. "Distributed MapReduce framework using distributed hash table." In 2013 International Joint Conference on Awareness Science and Technology & Ubi-Media Computing (iCAST-UMEDIA). IEEE, 2013. http://dx.doi.org/10.1109/icawst.2013.6765487.

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Fink, Bryan. "Distributed computation on dynamo-style distributed storage." In the eleventh ACM SIGPLAN workshop. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2364489.2364497.

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Reports on the topic "Distributed"

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Allwein, Gerard, and William L. Harrison. Distributed Logics. Fort Belvoir, VA: Defense Technical Information Center, October 2014. http://dx.doi.org/10.21236/ada610943.

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Hungate, Joseph, and Geraldina Fernandes. Distributed systems:. Gaithersburg, MD: National Institute of Standards and Technology, 1995. http://dx.doi.org/10.6028/nist.ir.5735.

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Cooper, L. N. Distributed Memory. Fort Belvoir, VA: Defense Technical Information Center, March 1985. http://dx.doi.org/10.21236/ada153364.

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Garrett, Charles Kristopher. Distributed Computing (MPI). Office of Scientific and Technical Information (OSTI), June 2016. http://dx.doi.org/10.2172/1258356.

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

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Buss, John, Rico Magbanua, Chrisman Thompson, John Goff, Andrew Moss, Damien Wall, Sean Jurgensen, Kyle Moyer, Ceying Foo, and Wei Q. Toh. Distributed Surface Force. Fort Belvoir, VA: Defense Technical Information Center, June 2014. http://dx.doi.org/10.21236/ada607535.

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Blake, Charles, Maureen Doyle, David A. Karr, and David Bakken. Distributed Shared Workspace. Fort Belvoir, VA: Defense Technical Information Center, July 1999. http://dx.doi.org/10.21236/ada367576.

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Greenberg, Ira B., and Peter K. Rathman. Distributed Database Integrity. Fort Belvoir, VA: Defense Technical Information Center, March 1992. http://dx.doi.org/10.21236/ada253272.

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Baron, Dror, Marco F. Duarte, Michael B. Wakin, Shriram Sarvotham, and Richard G. Baraniuk. Distributed Compressive Sensing. Fort Belvoir, VA: Defense Technical Information Center, January 2009. http://dx.doi.org/10.21236/ada521228.

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Morse, A. S. Intelligent Distributed Control. Fort Belvoir, VA: Defense Technical Information Center, August 2012. http://dx.doi.org/10.21236/ada567139.

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Journal articles Dissertations / Theses Books
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