Academic literature on the topic 'Distributed systems and algorithms'
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Journal articles on the topic "Distributed systems and algorithms"
Kindler, Ekkart, and Sibylle Peuker. "Integrating Distributed Algorithms into Distributed Systems." Fundamenta Informaticae 37, no. 3 (1999): 291–309. http://dx.doi.org/10.3233/fi-1999-37306.
Full textLee, Hyeon-Seok, and Jae-Jung Yun. "Advanced MPPT Algorithm for Distributed Photovoltaic Systems." Energies 12, no. 18 (September 19, 2019): 3576. http://dx.doi.org/10.3390/en12183576.
Full textDao-Tran, Minh, Thomas Eiter, Michael Fink, and Thomas Krennwallner. "Distributed Evaluation of Nonmonotonic Multi-context Systems." Journal of Artificial Intelligence Research 52 (April 29, 2015): 543–600. http://dx.doi.org/10.1613/jair.4574.
Full textChallenger, Moharram, Elif Haytaoglu, Gorkem Tokatli, Orhan Dagdeviren, and Kayhan Erciyes. "A Hybrid Distributed Mutual Exclusion Algorithm for Cluster-Based Systems." Mathematical Problems in Engineering 2013 (2013): 1–15. http://dx.doi.org/10.1155/2013/703414.
Full textCastanon, D., and D. Teneketzis. "Distributed estimation algorithms for nonlinear systems." IEEE Transactions on Automatic Control 30, no. 5 (May 1985): 418–25. http://dx.doi.org/10.1109/tac.1985.1103972.
Full textCiobanu, Gabriel. "Distributed algorithms over communicating membrane systems." Biosystems 70, no. 2 (July 2003): 123–33. http://dx.doi.org/10.1016/s0303-2647(03)00035-2.
Full textZhuravel, S., O. Shpur, and Yu Pyrih. "METHOD OF ACHIEVING CONSENSUS IN DISTRIBUTED SERVICE." Information and communication technologies, electronic engineering 2, no. 2 (December 2022): 58–66. http://dx.doi.org/10.23939/ictee2022.02.058.
Full textMishra, Swati, and Sanjaya Kumar Panda. "Efficient Fault Tolerant Algorithms for Internet Distributed Systems." International Journal of Knowledge Discovery in Bioinformatics 7, no. 1 (January 2017): 71–90. http://dx.doi.org/10.4018/ijkdb.2017010106.
Full textLogeswaran, Rajasvaran, and Li-Choo Chen. "Load Balancing Algorithms in Distributed Service Architectures for Medical Applications." International Journal of Healthcare Information Systems and Informatics 5, no. 1 (January 2010): 76–90. http://dx.doi.org/10.4018/jhisi.2010110305.
Full textBalanescu, Tudor, Radu Nicolescu, and Huiling Wu. "Asynchronous P Systems." International Journal of Natural Computing Research 2, no. 2 (April 2011): 1–18. http://dx.doi.org/10.4018/jncr.2011040101.
Full textDissertations / Theses on the topic "Distributed systems and algorithms"
Pandit, Saurav. "Approximation algorithms for distributed systems." Diss., University of Iowa, 2010. https://ir.uiowa.edu/etd/870.
Full textBernabéu-Aubán, José Manuel. "Location finding algorithms for distributed systems." Diss., Georgia Institute of Technology, 1988. http://hdl.handle.net/1853/32951.
Full textCornejo, Collado Alejandro. "Local distributed algorithms for multi-robot systems." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/79220.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (p. 165-173) and index.
The field of swarm robotics focuses on controlling large populations of simple robots to accomplish tasks more effectively than what is possible using a single robot. This thesis develops distributed algorithms tailored for multi-robot systems with large populations. Specifically we focus on local distributed algorithms since their performance depends primarily on local parameters on the system and are guaranteed to scale with the number of robots in the system. The first part of this thesis considers and solves the problem of finding a trajectory for each robot which is guaranteed to preserve the connectivity of the communication graph, and when feasible it also guarantees the robots advanced towards a goal defined by an arbitrary motion planner. We also describe how to extend our proposed approach to preserve the k-connectivity of a communication graph. Finally, we show how our connectivity-preserving algorithm can be combined with standard averaging procedures to yield a provably correct flocking algorithm. The second part of this thesis considers and solves the problem of having each robot localize an arbitrary subset of robots in a multi-robot system relying only on sensors at each robot that measure the angle, relative to the orientation of each robot, towards neighboring robots in the communication graph. We propose a distributed localization algorithm that computes the relative orientations and relative positions, up to scale, of an arbitrary subset of robots. For the case when the robots move in between rounds we show how to use odometry information to allow each robot to compute the relative positions complete with scale, of an arbitrary subset of robots. Finally we describe how to use the our localization algorithm to design a variety of multi-robot tasks.
by Alejandro Cornejo.
Ph.D.
Saia, Jared. "Algorithms for managing data in distributed systems /." Thesis, Connect to this title online; UW restricted, 2002. http://hdl.handle.net/1773/6941.
Full textWilhelm, Daniel. "Ordered broadcast algorithms in dynamic distributed systems." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS135.
Full textCausal broadcast is a fundamental building block of many distributed and parallel applications, where processes collaborate to perform common tasks, such as high performance computing, distributed databases, conferencing, social networks or other services providing a service to many users. In such systems, processes often require a broadcast primitive to share information that must be ordered to be meaningful, and causal order has been proven to be the strongest order that can be implemented in systems where partitioning can occur. Existing causal broadcast algorithms are either not scalable or they do not tolerate all the dynamics introduced by processes that join and leave the system or fail during execution. Some works append on messages all the information required to causally order them at destination. However, it has been proved that a structure with one entry per process in the system is the minimal structure required to ensure the causal delivery of broadcast messages. Hence, algorithms that append all the causal information on messages do not scale. Some other works make assumptions on the system, such as the network topology or the FIFO property of the communication channels. Such works do not handle well the dynamics caused by processes that join and leave the system or fail. Hence, these works do not handle all the possible dynamics of distributed systems. In this thesis, we provide causal broadcast algorithms that do scale and tolerate the dynamics of distributed systems. We first provide causal broadcast algorithms for Mobile Networks. Such networks have specific features: limited capacities of nodes (computation, storage, energy), unreliable communication channels, and the dynamics of connections due to node mobility, node failure, and join/leave operations of nodes. In the second part, we address causal broadcast provided with constant size clocks. Constant size clocks tolerate process churn and have a size that does not depend on the number of processes. However, they do not characterize causality and algorithms using them only ensure causal order probabilistically. We first propose an error detector, based on hashes, which analyzes the constant size clocks of messages before delivering them in order to detect messages which have causal dependencies that the process did not deliver yet. Second, we propose an algorithm to retrieve the causal dependencies of messages, which we use to ensure the causal delivery of messages tagged by the error detector. Third, we propose a new clock build with constant size clocks and which adapts its size to the number of concurrent messages inside the system. We implemented the contributions on the OMNeT++ simulator. Both causal broadcast algorithms were implemented on the framework INET, which is a realistic network simulator implementing interferences on the wireless network, network layers and node mobility among others. Results confirm that the presented causal broadcast algorithms outperform existing algorithms done for Mobile Networks while making realistic network assumptions. The contributions to constant size clocks were implemented on the OMNeT++ simulator. Results show that the hash-based error detector detected all messages whose causal dependencies have not been delivered yet. Combining the hash-based error detector with the algorithm to retrieve the causal dependencies of messages allowed to deliver all messages in causal order. We analyzed the limits of the hash-based error detector and the retrieval of causal dependencies. Finally, results show that the proposed clock adapts itself well to the number of concurrent messages inside the system
Huq, Sikder Rezwanul. "Locally self-adjusting distributed algorithms." Diss., University of Iowa, 2018. https://ir.uiowa.edu/etd/6594.
Full textGhodsi, Ali. "Distributed k-ary System: Algorithms for Distributed Hash Tables." Doctoral thesis, KTH, Mikroelektronik och Informationsteknik, IMIT, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4186.
Full textQC 20100824
AGATE, Vincenzo. "REPUTATION MANAGEMENT ALGORITHMS IN DISTRIBUTED APPLICATIONS." Doctoral thesis, Università degli Studi di Palermo, 2020. http://hdl.handle.net/10447/395198.
Full textObrovac, Marko. "Chemical Computing for Distributed Systems: Algorithms and Implementation." Phd thesis, Université Rennes 1, 2013. http://tel.archives-ouvertes.fr/tel-00925257.
Full textDivi, Vijay 1980. "Estimation and calibration algorithms for distributed sampling systems." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/45874.
Full textIncludes bibliographical references (p. 153-157).
Traditionally, the sampling of a signal is performed using a single component such as an analog-to-digital converter. However, many new technologies are motivating the use of multiple sampling components to capture a signal. In some cases such as sensor networks, multiple components are naturally found in the physical layout; while in other cases like time-interleaved analog-to-digital converters, additional components are added to increase the sampling rate. Although distributing the sampling load across multiple channels can provide large benefits in terms of speed, power, and resolution, a variety mismatch errors arise that require calibration in order to prevent a. degradation in system performance.In this thesis, we develop low-complexity, blind algorithms for the calibration of distributed sampling systems. In particular, we focus on recovery from timing skews that cause deviations from uniform timing. Methods for bandlimited input reconstruction from nonuniform recurrent samples are presented for both the small-mismatch and the low-SNR domains. Alternate iterative reconstruction methods are developed to give insight into the geometry of the problem.From these reconstruction methods, we develop time-skew estimation algorithms that have high performance and low complexity even for large numbers of components. We also extend these algorithms to compensate for gain mismatch between sampling components. To understand the feasibility of implementation, analysis is also presented for a sequential implementation of the estimation algorithm.In distributed sampling systems, the minimum input reconstruction error is dependent upon the number of sampling components as well as the sample times of the components. We develop bounds on the expected reconstruction error when the time-skews are distributed uniformly.
(cont) Performance is compared to systems where input measurements are made via projections onto random bases, an alternative to the sinc basis of time-domain sampling. From these results, we provide a framework on which to compare the effectiveness of any calibration algorithm.Finally, we address the topic of extreme oversampling, which pertains to systems with large amounts of oversampling due to redundant sampling components. Calibration algorithms are developed for ordering the components and for estimating the input from ordered components. The algorithms exploit the extra samples in the system to increase estimation performance and decrease computational complexity.
by Vijay Divi.
Ph.D.
Books on the topic "Distributed systems and algorithms"
Chow, Randy. Distributed operating systems & algorithms. Reading, Mass: Addison Wesley, 1996.
Find full textChow, Randy. Distributed operating systems & algorithms. Reading, Mass: Addison-Wesley, 1997.
Find full textHaddad, Serge. Distributed systems: Design and algorithms. Hoboken, NJ: John Wiley & Sons, 2011.
Find full textRaynal, Michel. Distributed Algorithms for Message-Passing Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38123-2.
Full textKshemkalyani, Ajay D. Distributed computing: Principles, algorithms, and systems. Cambridge: Cambridge University Press, 2008.
Find full textKshemkalyani, Ajay. Distributed Computing: Principles, Algorithms, and Systems. Leiden: Cambridge University Press, 2008.
Find full textNeumann, Dirk, Mark Baker, Jörn Altmann, and Omer Rana, eds. Economic Models and Algorithms for Distributed Systems. Basel: Birkhäuser Basel, 2010. http://dx.doi.org/10.1007/978-3-7643-8899-7.
Full textNeumann, Dirk. Economic models and algorithms for distributed systems. Basel: Birkhäuser, 2010.
Find full textGhosh, Sukumar. Distributed systems: An algorithmic approach. Boca Raton: CRC Press, Taylor & Franciss Group, 2015.
Find full textDistributed systems: An algorithmic approach. Boca Raton: Chapman & Hall/CRC, 2007.
Find full textBook chapters on the topic "Distributed systems and algorithms"
Ölveczky, Peter Csaba. "Distributed Algorithms." In Designing Reliable Distributed Systems, 211–32. London: Springer London, 2017. http://dx.doi.org/10.1007/978-1-4471-6687-0_13.
Full textDolev, Danny. "Theory and practice in distributed systems." In Distributed Algorithms, 71. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/bfb0022138.
Full textRicciardi, Aleta, Kenneth Birman, and Patrick Stephenson. "The cost of order in asynchronous systems." In Distributed Algorithms, 329–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/3-540-56188-9_22.
Full textIsraeli, Amos, Amnon Shaham, and Asaf Shirazi. "Linear-time snapshot protocols for unbalanced systems." In Distributed Algorithms, 26–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/3-540-57271-6_25.
Full textDolev, Shlomi. "Optimal time self stabilization in dynamic systems." In Distributed Algorithms, 160–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/3-540-57271-6_34.
Full textMoser, Louise E., and P. M. Melliar-Smith. "Total ordering algorithms for asynchronous Byzantine systems." In Distributed Algorithms, 242–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/bfb0022151.
Full textHélary, Jean-Michel, Achour Mostéfaoui, and Michel Raynal. "Virtual precedence in asynchronous systems: Concept and applications." In Distributed Algorithms, 170–84. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0030683.
Full textStoller, Scott D. "Detecting global predicates in distributed systems with clocks." In Distributed Algorithms, 185–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0030684.
Full textBabaoğlu, Özalp, Alberto Bartoli, and Gianluca Dini. "Replicated file management in large-scale distributed systems." In Distributed Algorithms, 1–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/bfb0020420.
Full textVidyasankar, K., and Toshimi Minoura. "An optimistic resiliency control scheme for distributed database systems." In Distributed Algorithms, 297–309. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/bfb0019810.
Full textConference papers on the topic "Distributed systems and algorithms"
Zambonelli, F. "Distributed algorithms and systems." In Proceedings Eleventh Euromicro Conference on Parallel, Distributed and Network-Based Processing. IEEE, 2003. http://dx.doi.org/10.1109/empdp.2003.1183591.
Full textJiannong Cao, Yifeng Chen, Kang Zhang, and Yanxiang He. "Checkpointing in hybrid distributed systems." In 7th International Symposium on Parallel Architectures, Algorithms and Networks, 2004. Proceedings. IEEE, 2004. http://dx.doi.org/10.1109/ispan.2004.1300471.
Full textOsmera, P. "Multilevel distributed genetic algorithms." In 1st International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications (GALESIA). IEE, 1995. http://dx.doi.org/10.1049/cp:19951099.
Full textMcLurkin, James. "Distributed algorithms for multi-robot systems." In the 6th international conference. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1236360.1236432.
Full textMcLurkin, James. "Distributed Algorithms for Multi-Robot Systems." In 2007 6th International Symposium on Information Processing in Sensor Networks. IEEE, 2007. http://dx.doi.org/10.1109/ipsn.2007.4379717.
Full textRichard, Alexander, Jesse Francis, and Jalal Kawash. "Basic Distributed Algorithms Visual Simulations for Distributed Systems Students." In 2021 IEEE Global Engineering Education Conference (EDUCON). IEEE, 2021. http://dx.doi.org/10.1109/educon46332.2021.9453906.
Full textDidona, Diego, Panagiota Fatourou, Rachid Guerraoui, Jingjing Wang, and Willy Zwaenepoel. "Distributed Transactional Systems Cannot Be Fast." In SPAA '19: 31st ACM Symposium on Parallelism in Algorithms and Architectures. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3323165.3323189.
Full textCechin, Sérgio Luis, and Ingrid Jansch-Pôrto. "Performance Evaluation of Checkpoint and Rollback-Recovery Algorithms for Distributed Systems." In Simpósio Brasileiro de Arquitetura de Computadores e Processamento de Alto Desempenho. Sociedade Brasileira de Computação, 1998. http://dx.doi.org/10.5753/sbac-pad.1998.22668.
Full textLuo, Yang, King Tin Lam, and Cho-Li Wang. "Path-Analytic Distributed Object Prefetching." In 2009 10th International Symposium on Pervasive Systems, Algorithms, and Networks. IEEE, 2009. http://dx.doi.org/10.1109/i-span.2009.131.
Full textCiobanu, Gabriel. "TiMo: Timed Mobility in Distributed Systems." In 2013 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC). IEEE, 2013. http://dx.doi.org/10.1109/synasc.2013.8.
Full textReports on the topic "Distributed systems and algorithms"
Prasadan, Arvind. Sketching Algorithms in Distributed Systems. Office of Scientific and Technical Information (OSTI), October 2021. http://dx.doi.org/10.2172/1826094.
Full textCho, Kilseok, Alan D. George, Raj Subramaniyan, and Keonwook Kim. Parallel Algorithms for Adaptive Matched-Field Processing in Distributed Array Systems. Fort Belvoir, VA: Defense Technical Information Center, January 2003. http://dx.doi.org/10.21236/ada465545.
Full textCho, Kilseok, Alan D. George, and Raj Subramaniyan. Fault-Tolerant Parallel Algorithms for Adaptive Matched-Field Processing on Distributed Array Systems. Fort Belvoir, VA: Defense Technical Information Center, September 2004. http://dx.doi.org/10.21236/ada466282.
Full textCristian, Flaviu. AASERT Grant - Distributed Systems and Flow Analysis Algorithm. Fort Belvoir, VA: Defense Technical Information Center, November 1997. http://dx.doi.org/10.21236/ada334840.
Full textVarshney, Pramod K., and Wael Hashlamoun. ALGORITHMS FOR SENSOR FUSION: Applications of Distance Measures and Probability of Error Bounds to Distributed. Detection Systems. Volume 2. Fort Belvoir, VA: Defense Technical Information Center, December 1991. http://dx.doi.org/10.21236/ada254634.
Full textDavis, M., D. Costyk, and A. Narang. Distributed and Electric Power System Aggregation Model and Field Configuration Equivalency Validation Testing: Supplemental Report on Penetration Software Algorithms. Office of Scientific and Technical Information (OSTI), March 2005. http://dx.doi.org/10.2172/15011464.
Full textMeyer, David, and Jeffrey Remmel. Distributed Algorithms for Sensor Fusion. Fort Belvoir, VA: Defense Technical Information Center, October 2002. http://dx.doi.org/10.21236/ada415039.
Full textLeighton, Tom. Parallel and Distributed Computing Combinatorial Algorithms. Fort Belvoir, VA: Defense Technical Information Center, October 1993. http://dx.doi.org/10.21236/ada277333.
Full textJajodia, Sushil. Replica Control Algorithms in Distributed Databases. Fort Belvoir, VA: Defense Technical Information Center, July 1993. http://dx.doi.org/10.21236/ada271571.
Full textHungate, 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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