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Relevant bibliographies by topics / Distributed databases

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Academic literature on the topic 'Distributed databases'

Author: Grafiati

Published: 4 June 2021

Last updated: 30 July 2024

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Journal articles on the topic "Distributed databases"

1

Shuhadah, W. N., M. Mat Deris, A. Noraziah, M. Y. Saman, and M. Rabiei. "Database Consistency Using Update-Ordering in Distributed Databases." Journal of Algorithms & Computational Technology 1, no. 1 (January 2007): 17–44. http://dx.doi.org/10.1260/174830107780122676.

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Bonifati, Angela, Panos K. Chrysanthis, Aris M. Ouksel, and Kai-Uwe Sattler. "Distributed databases and peer-to-peer databases." ACM SIGMOD Record 37, no. 1 (March 2008): 5–11. http://dx.doi.org/10.1145/1374780.1374781.

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Frank, Andrew U. "Distributed Databases for Surveying." Journal of Surveying Engineering 111, no. 1 (March 1985): 79–88. http://dx.doi.org/10.1061/(asce)0733-9453(1985)111:1(79).

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Ammann, P., and S. Jajodia. "Rethinking integrity [distributed databases]." IEEE Concurrency 5, no. 4 (October 1997): 5–6. http://dx.doi.org/10.1109/4434.641618.

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Thuraisingham, Bhavani. "Security for Distributed Databases." Information Security Technical Report 6, no. 2 (June 2001): 95–102. http://dx.doi.org/10.1016/s1363-4127(01)00210-2.

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Ibrahim, Rafea Mohammed. "Data Synchronization for Distributed Heterogeneous Database." Journal of Electrical Systems 20, no. 4s (April 8, 2024): 2573–78. http://dx.doi.org/10.52783/jes.3165.

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Heterogeneous distributed database concurrent data is one of the important topics of heterogeneous databases that have important meaning. This paper discusses the mechanism of optimizing data synchronization for distributed heterogeneous database and trying to propose real solutions. Database synchronization is the exchange of records in databases on the condition that they are different. When modifications are made to a specific database, they will be applied to the database that has been synchronized in different environments and servers horizontally. The synchronization is either a one-way or two-way application and can be incidental, i.e. it is synchronous to the local network and asynchronous to the Internet due to its lagging technology. Heterogeneous distributed database systems consisting of a row storage database and a column storage database will face many difficulties, due to the inconsistent storage type such as: synchronization speed mismatch in data synchronization compared to a homogeneously distributed database system. Heterogeneous database management systems work on exchanging information for a package of various formats, accessing modification information in a heterogeneous database, maintaining the independence of the proposed system, and ensuring a good application of the proposed system in order to reach data synchronization between several packages of databases.

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Sheth, Amit P., and James A. Larson. "Federated database systems for managing distributed, heterogeneous, and autonomous databases." ACM Computing Surveys 22, no. 3 (September 1990): 183–236. http://dx.doi.org/10.1145/96602.96604.

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ABORISADE, D. O., A. S. SODIYA, A. A. ODUMOSU, O. Y. ALOWOSILE, and A. A. ADEDEJI. "A SURVIVABLE DISTRIBUTED DATABASE AGAINST BYZANTINE FAILURE." Journal of Natural Sciences Engineering and Technology 15, no. 2 (November 22, 2017): 61–72. http://dx.doi.org/10.51406/jnset.v15i2.1684.

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Distributed Database Systems have been very useful technologies in making a wide range of information available to users across the World. However, there are now growing security concerns, arising from the use of distributed systems, particularly the ones attached to critical systems. More than ever before, data in distributed databases are more susceptible to attacks, failures or accidents owing to advanced knowledge explosions in network and database technologies. The imperfection of the existing security mechanisms coupled with the heightened and growing concerns for intrusion, attack, compromise or even failure owing to Byzantine failure are also contributing factors. The importance of survivable distributed databases in the face of byzantine failure, to other emerging technologies is the motivation for this research. Furthermore, It has been observed that most of the existing works on distributed database only dwelled on maintaining data integrity and availability in the face of attack. There exist few on availability or survibability of distributed databases owing to internal factors such as internal sabotage or storage defects. In this paper, an architecture for entrenching survivability of Distributed Databases occasioned by Byzantine failures is proposed. The proposed architecture concept is based on re-creating data on failing database server based on a set threshold value.The proposed architecture is tested and found to be capable of improving probability of survivability in distributed database where it is implemented to 99.6% from 99.2%.

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Ghosh, Deb, and Mysore Ramaswamy. "Configuring Geographically Distributed Videotex Databases." Journal of Database Management 2, no. 4 (October 1991): 27–37. http://dx.doi.org/10.4018/jdm.1991100103.

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Deen, S. M., R. R. Amin, and M. C. Taylor. "Data Integration in Distributed Databases." IEEE Transactions on Software Engineering SE-13, no. 7 (July 1987): 860–64. http://dx.doi.org/10.1109/tse.1987.233497.

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Dissertations / Theses on the topic "Distributed databases"

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Unnava, Vasundhara. "Query processing in distributed database systems." Connect to resource, 1992. http://rave.ohiolink.edu/etdc/view.cgi?acc%5Fnum=osu1261314105.

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Bielecki, Pavel. "Distributed relational database system of occasionally connected databases." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2000. http://handle.dtic.mil/100.2/ADA378092.

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Karlapalem, Kamalakar. "Redesign of distributed relational databases." Diss., Georgia Institute of Technology, 1992. http://hdl.handle.net/1853/9173.

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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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Juntunen, R. (Risto). "Tradeoffs in distributed databases." Bachelor's thesis, University of Oulu, 2016. http://urn.fi/URN:NBN:fi:oulu-201602231230.

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In a distributed database data is spread throughout the network into separated nodes with different DBMS systems (Date, 2000). According to CAP-theorem three database properties — consistency, availability and partition tolerance cannot be achieved simultaneously in distributed database systems. Two of these properties can be achieved but not all three at the same time (Brewer, 2000). Since this theorem there has been some development in network infrastructure. Also new methods to achieve consistency in distributed databases has emerged. This paper discusses trade-offs in distributed databases.

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Andriopoulos, X. "Databases for distributed realtime systems." Thesis, Imperial College London, 1986. http://hdl.handle.net/10044/1/37926.

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Xu, Lianghong. "Online Deduplication for Distributed Databases." Research Showcase @ CMU, 2016. http://repository.cmu.edu/dissertations/719.

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The rate of data growth outpaces the decline of hardware costs, and there has been an ever-increasing demand in reducing the storage and network overhead for online database management systems (DBMSs). The most widely used approach for data reduction in DBMSs is blocklevel compression. Although this method is simple and effective, it fails to address redundancy across blocks and therefore leaves significant room for improvement for many applications. This dissertation proposes a systematic approach, termed similaritybased deduplication, which reduces the amount of data stored on disk and transmitted over the network beyond the benefits provided by traditional compression schemes. To demonstrate the approach, we designed and implemented dbDedup, a lightweight record-level similaritybased deduplication engine for online DBMSs. The design of dbDedup exploits key observations we find in database workloads, including small item sizes, temporal locality, and the incremental nature of record updates. The proposed approach differs from traditional chunk-based deduplication approaches in that, instead of finding identical chunks anywhere else in the data corpus, similarity-based deduplication identifies a single similar data-item and performs differential compression to remove the redundant parts for greater savings. To achieve high efficiency, dbDedup introduces novel encoding, caching and similarity selection techniques that significantly mitigate the deduplication overhead with minimal loss of compression ratio. For evaluation, we integrated dbDedup into the storage and replication components of a distributed NoSQL DBMS and analyzed its properties using four real datasets. Our results show that dbDedup achieves up to 37⇥ reduction in the storage size and replication traffic of the database on its own and up to 61⇥ reduction when paired with the DBMS’s block-level compression. dbDedup provides both benefits with negligible effect on DBMS throughput or client latency (average and tail).

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Garcia, Hong-Mei Chen. "A semantics-based methodology for integrated distributed database design: Toward combined logical and fragmentation design and design automation." Diss., The University of Arizona, 1992. http://hdl.handle.net/10150/185936.

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The many advantages of Distributed Database (DDB) systems can only be achieved through proper DDB designs. Since designing a DDB is very difficult and expert designers are relatively few in number, "good" DDB design methodologies and associated computer-aided design tools are needed to help designers cope with design complexity and improve their productivity. Unfortunately, previous DDB design research focused on solving subproblems of data distribution design in isolation. As a result, past research on a general DDB design methodology offered only methodological frameworks that, at best, aggregate a set of non-integrated design techniques. The conventional separation of logical design from fragmentation design is problematic, but has not been fully analyzed. This dissertation presents the SEER-DTS methodology developed for the purposes of overcoming the methodological inadequacies of conventional design methodologies, resolving the DDB design problem in an integrated manner and facilitating design automation. It is based on a static semantic data model, SEER (Synthesized Extended Entity-Relationship Model) and a dynamic data model, DTS (Distributed Transaction Scheme), which together provide complete and consistent modeling mechanisms for acquiring/representing DDB design inputs and facilitating DDB schema design. In this methodology, requirement/distribution analysis and conceptual design are integrated and logical and fragmentation designs are combined. "Semantics-based" design techniques have been developed to allow for end-user design specifications and seamless design schema transformations, thereby simplifying design tasks. Towards our ultimate goal of design automation, an architectural framework for a computer-aided DDB design system, Auto-DDB, was formulated and the system was prototyped. As part of the developmental effort, a real-world DDB design case study was conducted to verify the applicability of the SEER-DTS methodology in a manual design mode. The results of a laboratory experiment showed that the SEER-DTS methodology produced better design outcomes (in terms of design effectiveness and efficiency) than a Conventional Best methodology performed by non-expert designers in an automated design mode. However, no statistically significant difference was found in user-perceived ease of use.

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Potter, Anthony. "Query answering in distributed RDF databases." Thesis, University of Oxford, 2017. http://ora.ox.ac.uk/objects/uuid:2ed8a003-7850-4699-bdbf-38be68673813.

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To simplify data integration and exchange, modern applications often represent their data using the Resource Description Framework (RDF). As the amount of the available data keeps increasing, many RDF datasets cannot be processed using centralised RDF stores. A common solution is to distribute RDF data in a cluster of shared-nothing servers, and to query the data using a distributed query algorithm. Existing approaches typically use a variant of the data exchange operator to shuffle partial query answers between servers and thus ensure that every query answer is produced. Decisions as to when and where to shuffle the data are usually made statically - that is, at query compile time. In this thesis, we argue that such approaches can miss opportunities for local computation and thus incur considerable overheads. Moreover, we present a novel distributed query evaluation algorithm for RDF based on dynamic data exchange, where all computation that can be done locally is guaranteed to be performed on a single server. Our approach can successfully process any query even if the memory available at each server is bounded, and we argue that this is critical in distributed systems where intermediate results can easily exceed the capacity of each server. We also present a new query planning approach that balances the cost of communication against the cost of local processing at each server, as well as a new approach to partitioning RDF data that aims to increase locality in each server. We have implemented our approach in the well-known RDFox data store, and our empirical evaluation suggests that our techniques can outperform the state of the art by orders of magnitude in terms of query evaluation times, network communication, and memory use.

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Books on the topic "Distributed databases"

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Burleson, Donald K. Managing distributed databases: Building bridges between database islands. New York: Wiley, 1994.

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Fong, Elizabeth. Guide to distributed database management. Gaitherburg, MD: U.S. Dept. of Commerce, National Bureau of Standards, 1988.

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N, Chorafas Dimitris. Handbook of database management and distributed relational databases. Princeton, N.J: Petrocelli Books, 1989.

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Teresa, Hopper, and International Business Machines Corporation, eds. Distributed relational database architecture: Connectivity guide. 4th ed. Upper Saddle River, NJ: Prentice Hall PTR, 1995.

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5

Ceri, Stefano. Distributed databases: Principles and systems. New York: McGraw-Hill, 1985.

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Killen, Michael. SAA: Managing distributed data. New York: McGraw-Hill, 1991.

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Cardiff, J. Unified access to distributed heterogenous databases. Dublin: Trinity College, Department of Computer Science, 1991.

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Jablonski, Stefan. Datenverwaltung in verteilten Systemen: Grundlagen und Lösungskonzepte. Berlin: Springer-Verlag, 1990.

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Hunstock, Jens. Integration konzeptioneller Datenbankschemata. Lohmar: J. Eul, 2001.

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Radeke, Elke. Federation and migration among database systems. Aachen: Shaker, 1996.

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Book chapters on the topic "Distributed databases"

1

Thomasian, Alexander. "Distributed Databases." In Database Concurrency Control, 111–17. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4757-2473-8_6.

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Deen, S. M. "Distributed Databases." In Principles and Practice of Database Systems, 357–74. London: Macmillan Education UK, 1985. http://dx.doi.org/10.1007/978-1-349-17958-9_15.

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Smith, William. "Distributed Databases." In Systems Building with Oracle, 491–522. London: Macmillan Education UK, 2004. http://dx.doi.org/10.1007/978-0-230-00094-0_20.

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Shekhar, Shashi, and Hui Xiong. "Distributed Databases." In Encyclopedia of GIS, 246. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_312.

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Coquil, David, and Harald Kosch. "Distributed Databases." In Handbook of Computer Networks, 298–311. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118256107.ch19.

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Sikora, Z. M. "Distributed Databases." In Oracle Database Principles, 192–99. London: Macmillan Education UK, 1997. http://dx.doi.org/10.1007/978-1-349-14693-2_12.

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Domdouzis, Konstantinos, Peter Lake, and Paul Crowther. "Distributed Databases." In Undergraduate Topics in Computer Science, 213–22. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-42224-0_10.

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Kalnis, Panos. "Distributed Spatial Databases." In Encyclopedia of Database Systems, 1–7. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4899-7993-3_136-2.

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Kalnis, Panos. "Distributed Spatial Databases." In Encyclopedia of Database Systems, 920–25. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_136.

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Kalnis, Panos. "Distributed Spatial Databases." In Encyclopedia of Database Systems, 1215–22. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_136.

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Conference papers on the topic "Distributed databases"

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Klieb, Leslie. "Distributed disconnected databases." In the 1996 ACM symposium. New York, New York, USA: ACM Press, 1996. http://dx.doi.org/10.1145/331119.331200.

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Pupezescu, Valentin. "ADVANCES IN KNOWLEDGE DISCOVERY IN DISTRIBUTED DATABASES." In eLSE 2015. Carol I National Defence University Publishing House, 2015. http://dx.doi.org/10.12753/2066-026x-15-046.

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The Knowledge Discovery in Distributed Databases is the process of extracting useful information from a collection of data stored in distributed databases. A distributed database is a collection of data replicated over a number of different computers. The best suited structures for working with distributed databases are the Distributed Committee-Machines. Distributed Committee-Machines are a combination of neural networks that work in a distributed manner as a group in order to obtain better performance than individual neural networks in solving data mining tasks inside the KDD process. In this paper I aim to study the interaction between Distributed Committee-Machines and distributed databases. The process of replication on multiple machines can become very slow once the number of the machines from the replication topology grows. Such behaviour is explicable because of the complex software that is used in real implementations of the replication process in order to make available the same data on multiple machines. Because of this situation, working with Distributed Committee-Machines in a distributed environment can be very problematic. In this paper I propose a design that overcomes those disadvantages and a new type of approach in storing the neural networks. The developed system stores the entire neural network in a real relational databases. All the neural structures that were used were multilayer perceptrons trained with the backpropagation algorithm. The non-optimized architecture has the disadvantage of writing all the results on the master system. All the data (TR - training set, TS - testing set, results) are duplicated on each slave machine. This working methods it's time consuming because of the internal functioning of the replication process. With this system, the distributed speedup is below one. The optimized DCM structure eliminates the problems inherited from replication by writing all the result locally in special tables that won't be replicated on all the distributed machines. Whenever the neural networks finds an optimal result, the neural network will write in the database all the important parameters. Here I used also a new approach which consists of storing the entire neural network in the table as BLOB (Binary Large Object) object. The method can be beneficial also in new types of eLearning technics such as the adaptive eLearning method that uses neural networks. With the optimized design of DCM structures the speedup in all the experiments is almost equal with the number of distributed machines that were used.

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Ruan, Pingcheng, Tien Tuan Anh Dinh, Dumitrel Loghin, Meihui Zhang, Gang Chen, Qian Lin, and Beng Chin Ooi. "Blockchains vs. Distributed Databases." In SIGMOD/PODS '21: International Conference on Management of Data. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3448016.3452789.

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Simmons, Robert J., Bernardo Toninho, and Frank Pfenning. "Distributed deductive databases, declaratively." In the 2011 ACM SIGPLAN X10 Workshop. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2212736.2212742.

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Artail, Hassan, Haidar Safa, Rana ELZinnar, and Hicham Hamze. "A Distributed Database Framework from Mobile Databases in MANETs." In Third IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob 2007). IEEE, 2007. http://dx.doi.org/10.1109/wimob.2007.4390848.

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Xu, Wenhao, Jing Li, Yongwei Wu, Xiaomeng Huang, and Guangwen Yang. "VDM: Virtual Database Management for Distributed Databases and File Systems." In 2008 Seventh International Conference on Grid and Cooperative Computing (GCC). IEEE, 2008. http://dx.doi.org/10.1109/gcc.2008.42.

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Sun, Dalie, Sai Wu, Jianzhong Li, and Anthony K. H. Tung. "Skyline-join in distributed databases." In 2008 IEEE 24th International Conference on Data Engineeing workshop (ICDE Workshop 2008). IEEE, 2008. http://dx.doi.org/10.1109/icdew.2008.4498313.

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Xu, Bo, Ouri Wolfson, and Sam Chamberlain. "Spatially distributed databases on sensors." In the eighth ACM international symposium. New York, New York, USA: ACM Press, 2000. http://dx.doi.org/10.1145/355274.355297.

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Wiederhold, Gio, and XiaoLei Qian. "Modeling asynchrony in distributed databases." In 1984 IEEE First International Conference on Data Engineering. IEEE, 1987. http://dx.doi.org/10.1109/icde.1987.7272379.

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De Silva, L. P. Daswin Pasantha, and Manjula Dissanayake. "Optimal Design of Distributed Databases." In 2006 International Conference on Information and Automation. IEEE, 2006. http://dx.doi.org/10.1109/icinfa.2006.374142.

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Reports on the topic "Distributed databases"

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Jajodia, Sushil. Replica Control Algorithms in Distributed Databases. Fort Belvoir, VA: Defense Technical Information Center, July 1993. http://dx.doi.org/10.21236/ada271571.

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Parsons, Amy. Distributed computing support program`s databases. Office of Scientific and Technical Information (OSTI), May 1996. http://dx.doi.org/10.2172/576757.

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Chang, LiWu, and Ira S. Moskowitz. A Study of Inference Problems in Distributed Databases. Fort Belvoir, VA: Defense Technical Information Center, January 2002. http://dx.doi.org/10.21236/ada464386.

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Fong, Elizabeth N., Charles L. Sheppard, and Kathryn A. Harvill. Guide to design, implementation and management of distributed databases. Gaithersburg, MD: National Institute of Standards and Technology, 1991. http://dx.doi.org/10.6028/nist.sp.500-185.

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Peddi, Praveen, and Lisa C. DiPippo. A Replication Strategy for Distributed Real-Time Object-Oriented Databases. Fort Belvoir, VA: Defense Technical Information Center, April 2002. http://dx.doi.org/10.21236/ada477629.

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Croft, W. Bruce. Browsing, Discovery, and Search in Large Distributed Databases of Complex and Scanned Documents. Fort Belvoir, VA: Defense Technical Information Center, January 2000. http://dx.doi.org/10.21236/ada372353.

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Lauret, Jerome, and Michael Furey. CWS4DB: A Customizable Web Service for Efficient Access to Distributed Nuclear Physics Relational Databases. Office of Scientific and Technical Information (OSTI), June 2013. http://dx.doi.org/10.2172/1083469.

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Son, Sang H., and Craig Chaney. Supporting the Requirements for Multi-Level Secure and Real-Time Databases in Distributed Environments. Fort Belvoir, VA: Defense Technical Information Center, January 1997. http://dx.doi.org/10.21236/ada478995.

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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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Maryanski, Fred. Dynamically Reconfigurable Distributed Database Systems. Fort Belvoir, VA: Defense Technical Information Center, March 1988. http://dx.doi.org/10.21236/ada194716.

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