Relevant bibliographies by topics / Distributed computing

Academic literature on the topic 'Distributed computing'

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Published: 4 June 2021
Last updated: 6 July 2024

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Journal articles on the topic "Distributed computing"

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Keidar, Idit. "Distributed computing column 36 distributed computing." ACM SIGACT News 40, no. 4 (January 25, 2010): 64–67. http://dx.doi.org/10.1145/1711475.1711489.

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Rajsbaum, Sergio. "Distributed Computing." ACM SIGACT News 32, no. 3 (September 2001): 53–62. http://dx.doi.org/10.1145/500559.500561.

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Dwork, Cynthia. "Distributed computing." ACM SIGACT News 26, no. 1 (March 1995): 17–19. http://dx.doi.org/10.1145/203610.203614.

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Ryland, Jane N. "Distributed computing." New Directions for Higher Education 1988, no. 62 (1988): 27–33. http://dx.doi.org/10.1002/he.36919886205.

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Sakariya, Harsh Bipinbhai, and Ganesh D. "Taxonomy of Load Balancing Strategies in Distributed Systems." International Journal of Innovative Research in Computer and Communication Engineering 12, no. 03 (March 25, 2024): 1796–802. http://dx.doi.org/10.15680/ijircce.2024.1203070.

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Large-scale parallel and distributed computing systems are becoming more popular as a result of falling hardware prices and improvements in computer networking technologies. Improved performance and resource sharing are potential benefits of distributed computing systems. We have provided a summary of distributed computing in this essay. The differences between parallel and distributed computing, terms related to distributed computing, task distribution in distributed computing, performance metrics in distributed computing systems, parallel distributed algorithm models, benefits of distributed computing, and distributed computing's application domain were all covered in this paper.
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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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Talekar, Mr Bhushan, Miss Sonali Chaudhari, Prof Vinayak Shinde, and Prof Gayatri Masiwal. "Distributed Computing Challenges." IOSR Journal of Computer Engineering 16, no. 2 (2014): 28–31. http://dx.doi.org/10.9790/0661-162102831.

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Farrens, Matt. "Distributed decentralized computing." ACM Computing Surveys 28, no. 4es (December 1996): 28. http://dx.doi.org/10.1145/242224.242259.

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Coady, Yvonne, Oliver Hohlfeld, James Kempf, Rick McGeer, and Stefan Schmid. "Distributed Cloud Computing." ACM SIGCOMM Computer Communication Review 45, no. 2 (April 22, 2015): 38–43. http://dx.doi.org/10.1145/2766330.2766337.

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Schmidt, D. C. "Distributed Object Computing." IEEE Communications Magazine 35, no. 2 (February 1997): 42–44. http://dx.doi.org/10.1109/mcom.1997.565654.

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Dissertations / Theses on the topic "Distributed computing"

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Datla, Dinesh. "Wireless Distributed Computing in Cloud Computing Networks." Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/51729.

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The explosion in growth of smart wireless devices has increased the ubiquitous presence of computational resources and location-based data. This new reality of numerous wireless devices capable of collecting, sharing, and processing information, makes possible an avenue for new enhanced applications. Multiple radio nodes with diverse functionalities can form a wireless cloud computing network (WCCN) and collaborate on executing complex applications using wireless distributed computing (WDC). Such a dynamically composed virtual cloud environment can offer services and resources hosted by individual nodes for consumption by user applications. This dissertation proposes an architectural framework for WCCNs and presents the different phases of its development, namely, development of a mathematical system model of WCCNs, simulation analysis of the performance benefits offered by WCCNs, design of decision-making mechanisms in the architecture, and development of a prototype to validate the proposed architecture. The dissertation presents a system model that captures power consumption, energy consumption, and latency experienced by computational and communication activities in a typical WCCN. In addition, it derives a stochastic model of the response time experienced by a user application when executed in a WCCN. Decision-making and resource allocation play a critical role in the proposed architecture. Two adaptive algorithms are presented, namely, a workload allocation algorithm and a task allocation - scheduling algorithm. The proposed algorithms are analyzed for power efficiency, energy efficiency, and improvement in the execution time of user applications that are achieved by workload distribution. Experimental results gathered from a software-defined radio network prototype of the proposed architecture validate the theoretical analysis and show that it is possible to achieve 80 % improvement in execution time with the help of just three nodes in the network.
Ph. D.
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Li, Guangxing. "Supporting distributed realtime computing." Thesis, University of Cambridge, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.309077.

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Evers, David Martin. "Distributed computing with objects." Thesis, University of Cambridge, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.318049.

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Riddoch, David James. "Low latency distributed computing." Thesis, University of Cambridge, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.619850.

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BOLDRIN, FABIO. "Web Distributed Computing Systems." Doctoral thesis, Università degli studi di Ferrara, 2011. http://hdl.handle.net/11392/2388764.

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The thesis presents the PhD study about a new approach in distributed computing based on the exploitation of web browsers as clents, using technologies and best practices of Javascript, AJAX and Flex. The described solution has two main advantages: it is client free, so no additional programs have to be installed to perform the computation, and it requires low CPU usage, so clientside computation is no invasive for users. The solution is developed with both AJAX and Adobe® Flex® technologies embedding a pseudoclient into a web page that hosts the computation in the form of a banner. While users browse the hosting web page, client side of the system query the server side part for a subproblem, called crunch, computes the solution(s) and sends back it to the server. All the process is always transparent for the users navigation experience and computer use in general. The thesis shows the feasibility of the system and the good performances that can be achieved, with details over tests and metrics that have been defined to measure the performance indexes. The new architecture has been tested through this performance metrics by implementing two examples of distributed computing, the cracking of the RSA cryptosystem through the factorization of the public key and the Pearson's correlation index between smples in genetic data sets. Results have shown good feasibility of this approach both in a closed environment and also in an Internet environment, in a typical real situation. A mathematical model has been developed over this solution. The main goals of the model are to describe and classify different categories of problems on the basis of the feasibility and o find the limits in the dimensioning of the scheduling systems to have convenience in the use of this approach.
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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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Higham, Lisa. "Randomized distributed computing on rings." Thesis, University of British Columbia, 1988. http://hdl.handle.net/2429/28839.

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The communication complexity of fundamental problems in distributed computing on an asynchronous ring are examined from both the algorithmic and lower bound perspective. A detailed study is made of the effect on complexity of a number of assumptions about the algorithms. Randomization is shown to influence both the computability and complexity of several problems. Communication complexity is also shown to exhibit varying degrees of sensitivity to additional parameters including admissibility of error, kind of error, knowledge of ring size, termination requirements, and the existence of identifiers. A unified collection of formal models of distributed computation on asynchronous rings is developed which captures the essential characteristics of a spectrum of distributed algorithms those that are error free (deterministic, Las Vegas, and nondeterministic), and those that err with small probability (Monte Carlo and nondeterministic/probabilistic). The nondeterministic and nondeterministic/probabilistic models are introduced as natural generalizations of the Las Vegas and Monte Carlo models respectively, and prove useful in deriving lower bounds. The unification helps to clarify the essential differences between the progressively more general notions of a distributed algorithm. In addition, the models reveal the sensitivity of various problems to the parameters listed above. Complexity bounds derived using these models typically vary depending on the type of algorithm being investigated. The lower bounds are complemented by algorithms with matching complexity while frequently the lower bounds hold on even more powerful models than those required by the algorithms. Among the algorithms and lower bounds presented are two specific results which stand out because of their relative significance. 1. If g is any nonconstant cyclic function of n variables, then any nondeterministic algorithm for computing g on an anonymous ring of size n has complexity [Formula Omitted] bits of communication; and, there is a is nonconstant cyclic boolean function [Formula Omitted], such that [Formula Omitted] can be computed by a Las Vegas algorithm in [Formula Omitted] expected bits of communication on a ring of size n. 2. The expected complexity of computing AND (and a number of other natural functions) on a ring of fixed size n in the Monte Carlo model is [Formula Omitted] messages and bits where [Formula Omitted] is the allowable probability of error.
Science, Faculty of
Computer Science, Department of
Graduate
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Gao, Yiran. "Dynamic inter-domain distributed computing." Thesis, Queen Mary, University of London, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.510898.

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Bouchard, David S. M. Massachusetts Institute of Technology. "Embodied emergence : distributed computing manipulatives." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/41743.

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Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2007.
Includes bibliographical references (p. 65-67).
Distributed systems and the emergent properties that can arise out of simple localized interactions have fascinated scientists and artists alike for the last century. They challenge the notions of control and creativity, producing outcomes that can be beautiful, engaging and surprising at the same time. While extensive work has been done using computer simulations of such systems in fields like artificial life and generative art, their physically embodied counterparts are still in their infancy, in part due to the complexity of building and deploying such systems. In this thesis, I will discuss how simple tangible nodes can enable playful and creative experimentation with the concept of emergent behavior. Specifically, I will address how embodied interaction scenarios involving parallel systems can be implemented and how a range of sensing and actuating possibilities can be leveraged to generate novel and engaging experiences for the end users. In particular, the use of sound will be explored as a medium for representation. Finally, I will argue that there is value in making the transition from software simulations to a situated and manipulable instantiation of these concepts, both for the designer of a system and its users.
by David Bouchard.
S.M.
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Vaikuntanathan, Vinod. "Distributed computing with imperfect randomness." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/34354.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.
Includes bibliographical references (p. 41-43).
Randomness is a critical resource in many computational scenarios, enabling solutions where deterministic ones are elusive or even provably impossible. However, the randomized solutions to these tasks assume access to a pure source of unbiased, independent coins. Physical sources of randomness, on the other hand, are rarely unbiased and independent although they do seem to exhibit somewhat imperfect randomness. This gap in modeling questions the relevance of current randomized solutions to computational tasks. Indeed, there has been substantial investigation of this issue in complexity theory in the context of the applications to efficient algorithms and cryptography. This work seeks to determine whether imperfect randomness, modeled appropriately, is "good enough" for distributed algorithms. Namely, can we do with imperfect randomness all that we can do with perfect randomness, and with comparable efficiency ? We answer this question in the affirmative, for the problem of Byzantine agreement. We construct protocols for Byzantine agreement in a variety of scenarios (synchronous or asynchronous networks, with or without private channels), in which the players have imperfect randomness. Our solutions are essentially as efficient as the best known randomized Byzantine agreement protocols, which traditionally assume that all the players have access to perfect randomness.
by Vinod Vaikuntanathan.
S.M.
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Books on the topic "Distributed computing"

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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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Jayanti, Prasad, ed. Distributed Computing. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48169-9.

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Malkhi, Dahlia, ed. Distributed Computing. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-36108-1.

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Herlihy, Maurice, ed. Distributed Computing. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-40026-5.

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Fraigniaud, Pierre, ed. Distributed Computing. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11561927.

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Kutten, Shay, ed. Distributed Computing. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0056467.

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Afek, Yehuda, ed. Distributed Computing. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41527-2.

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Das, Sajal K., and Swapan Bhattacharya, eds. Distributed Computing. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-36385-8.

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Kuhn, Fabian, ed. Distributed Computing. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-45174-8.

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Welch, Jennifer, ed. Distributed Computing. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45414-4.

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Book chapters on the topic "Distributed computing"

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Delfino, Manuel. "Distributed Computing." In Particle Physics Reference Library, 613–44. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-35318-6_14.

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Kao, Ming-Yang. "Distributed Computing." In Encyclopedia of Algorithms, 258. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-30162-4_117.

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Walmsley, Mark. "Distributed Computing." In Multi-Threaded Programming in C++, 185–213. London: Springer London, 2000. http://dx.doi.org/10.1007/978-1-4471-0725-5_10.

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Delfino, M. "Distributed Computing." In Detectors for Particles and Radiation. Part 1: Principles and Methods, 388–403. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-03606-4_14.

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Shekhar, Shashi, and Hui Xiong. "Distributed Computing." In Encyclopedia of GIS, 246. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_311.

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Wang, Liang, and Jianxin Zhao. "Distributed Computing." In Architecture of Advanced Numerical Analysis Systems, 243–79. Berkeley, CA: Apress, 2022. http://dx.doi.org/10.1007/978-1-4842-8853-5_10.

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AbstractDistributed computing has been playing a significant role in current smart applications in various fields. In this chapter, we first briefly give a bird’s-eye view of this topic, introducing various programming paradigms. Next, we introduce Actor, an OCaml-based distributed computing engine, and how it works together with Owl. We then focus on one key element in distributed computing: the synchronization. We introduce four different types of synchronization methods or “barriers” that are commonly used in current systems. Next, we elaborate how these barriers are designed and provide illustrations from the theoretical perspective. Finally, we use evaluations to show the performance trade-offs in using different barriers.
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Gu, Zhaoquan, Yuexuan Wang, Qiang-Sheng Hua, and Francis C. M. Lau. "Distributed Computing." In Rendezvous in Distributed Systems, 15–22. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-3680-4_2.

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Taubenfeld, Gadi. "Distributed Computing." In Distributed Computing Pearls, 1–7. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-031-02012-4_1.

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Karim, Ramin, Diego Galar, and Uday Kumar. "Distributed Computing." In AI Factory, 291–329. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003208686-9.

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Jayanti, Prasad. "Wait-free computing." In Distributed Algorithms, 19–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/bfb0022136.

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Conference papers on the topic "Distributed computing"

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Liu, Ming T. (Mike). "Distributed computing." In the 1992 ACM annual conference. New York, New York, USA: ACM Press, 1992. http://dx.doi.org/10.1145/131214.131287.

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"Distributed computing." In 2010 IEEE International Conference on Intelligent Computer Communication and Processing (ICCP). IEEE, 2010. http://dx.doi.org/10.1109/iccp.2010.5606426.

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Cruz, Rui S., and Miguel Casquilho. "Distributed Computing." In 2019 14th Iberian Conference on Information Systems and Technologies (CISTI). IEEE, 2019. http://dx.doi.org/10.23919/cisti.2019.8760827.

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Rashid, Zryan Najat, Subhi R. M. Zebari, Karzan Hussein Sharif, and Karwan Jacksi. "Distributed Cloud Computing and Distributed Parallel Computing: A Review." In 2018 International Conference on Advanced Science and Engineering (ICOASE). IEEE, 2018. http://dx.doi.org/10.1109/icoase.2018.8548937.

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Krishnaswamy, Dilip. "Wireless distributed computing." In the 1st International Conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2185216.2185228.

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Fu, Zhongyi, and Young Choon Lee. "Collaborative Distributed Computing." In UbiComp '18: The 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3267305.3267608.

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Lynch, Nancy A. "Distributed computing theory." In the thirty-ninth annual ACM symposium. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1250790.1250826.

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Babaoglu, Ozalp, and Alina Sirbu. "Cognified Distributed Computing." In 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS). IEEE, 2018. http://dx.doi.org/10.1109/icdcs.2018.00118.

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Kearns, Lorna Richey. "Distributed computing support." In the 19th annual ACM SIGUCCS conference. New York, New York, USA: ACM Press, 1991. http://dx.doi.org/10.1145/122898.122927.

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Schmutz, H., H. Eberle, U. Hollberg, and M. Seifert. "Distributed academic computing." In the 2nd workshop. New York, New York, USA: ACM Press, 1986. http://dx.doi.org/10.1145/503956.503976.

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Reports on the topic "Distributed computing"

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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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Lamport, Leslie, and Nancy Lynch. Chapter on Distributed Computing. Fort Belvoir, VA: Defense Technical Information Center, February 1989. http://dx.doi.org/10.21236/ada208996.

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Kaplansky, I., and Richard M. Karp. Parallel and Distributed Computing. Fort Belvoir, VA: Defense Technical Information Center, December 1986. http://dx.doi.org/10.21236/ada182935.

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Hariri, Salim, Dongmin Kim, Yoonhee Kim, and Ilkyeun Ra. Virtual Distributed Computing Environment. Fort Belvoir, VA: Defense Technical Information Center, March 2000. http://dx.doi.org/10.21236/ada376238.

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Kaplansky, Irving, and Richard Karp. Parallel and Distributed Computing. Fort Belvoir, VA: Defense Technical Information Center, December 1986. http://dx.doi.org/10.21236/ada176477.

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Fagg, Graham E. Cooperative Fault Tolerant Distributed Computing. Office of Scientific and Technical Information (OSTI), March 2006. http://dx.doi.org/10.2172/877391.

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Hurley, Patrick M., and Scott M. Huse. The Survivable Distributed Computing Environment. Fort Belvoir, VA: Defense Technical Information Center, June 1994. http://dx.doi.org/10.21236/ada281637.

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Childers, L., L. Liming, and I. Foster. Perspectives on distributed computing : thirty people, four user types, and the distributed computing user experience. Office of Scientific and Technical Information (OSTI), October 2008. http://dx.doi.org/10.2172/946032.

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Qiu, Qinru. Low Power Computing in Distributed Systems. Fort Belvoir, VA: Defense Technical Information Center, April 2006. http://dx.doi.org/10.21236/ada450272.

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Gowdy, Stephen J. The BaBar Experiment's Distributed Computing Model. Office of Scientific and Technical Information (OSTI), May 2002. http://dx.doi.org/10.2172/799061.

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