Dissertations / Theses on the topic 'Distributed processing'
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Lee, Li 1975. "Distributed signal processing." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/86436.
Full textLu, Yu-En. "Distributed proximity query processing." Thesis, University of Cambridge, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.612165.
Full textWu, Tsung-li. "Distributed processing on link enhancement." Thesis, Monterey, California. Naval Postgraduate School, 1992. http://hdl.handle.net/10945/23869.
Full textde, Errico Luciano. "Agent-based distributed parallel processing." Thesis, University of Surrey, 1996. http://epubs.surrey.ac.uk/843822/.
Full textNorcross, Stuart John. "Deriving distributed garbage collectors from distributed termination algorithms." Thesis, University of St Andrews, 2004. http://hdl.handle.net/10023/14986.
Full textBenelallam, Amine. "Model transformation on distributed platforms : decentralized persistence and distributed processing." Thesis, Nantes, Ecole des Mines, 2016. http://www.theses.fr/2016EMNA0288/document.
Full textModel-Driven Engineering (MDE) is gaining ground in industrial environments, thanks to its promise of lowering software development and maintenance effort. It has been adopted with success in producing software for several domains like civil engineering, car manufacturing and modernization of legacy software systems. As the models that need to be handled in model-driven engineering grow in scale, it became necessary to design scalable algorithms for model transformation (MT) as well as well-suitable persistence frameworks. One way to cope with these issues is to exploit the wide availability of distributed clusters in the Cloud for the distributed execution of model transformations and their persistence. On one hand, programming models such as MapReduce and Pregel may simplify the development of distributed model transformations. On the other hand, the availability of different categories of NoSQL databases may help to store efficiently the models. However, because of the dense interconnectivity of models and the complexity of transformation logics, scalability in distributed model processing is challenging. In this thesis, we propose our approach for scalable model transformation and persistence. We exploit the high-level of abstraction of relational MT languages and the well-defined semantics of existing distributed programming models to provide a relational model transformation engine with implicit distributed execution. The syntax of the MT language is not modified and no primitive for distribution is added. Hence developers are not required to have any acquaintance with distributed programming.We extend this approach with an efficient model distribution algorithm, based on the analysis of relational model transformation and recent results on balanced partitioning of streaming graphs. We applied our approach to a popular MT language, ATL, on top of a well-known distributed programming model, MapReduce. Finally, we propose a multi-persistence backend for manipulating and storing models in NoSQL databases according to the modeling scenario. Especially, we focus on decentralized model persistence for distributed model transformations
孫昱東 and Yudong Sun. "A distributed object model for solving irregularly structured problemson distributed systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B31243630.
Full textKumar, Rohit 1986. "Temporal graph mining and distributed processing." Doctoral thesis, Universitat Politècnica de Catalunya, 2018. http://hdl.handle.net/10803/620623.
Full textCon el reciente crecimiento de las redes sociales y el deseo humano de interactuar con el mundo digital, una gran cantidad de datos de interacción humano-a-humano o humano-a-dispositivo se generan cada segundo. Con el auge de los dispositivos IoT, las interacciones dispositivo-a-dispositivo también están en alza. Todas estas interacciones no son más que una representación de como la red subyacente conecta distintas entidades en el tiempo. Modelar estas interacciones en forma de red de interacciones presenta una gran cantidad de oportunidades únicas para descubrir patrones interesantes y entender la dinamicidad de la red. Entender la dinamicidad de la red es clave ya que encapsula la forma en la que nos comunicamos, socializamos, consumimos información y somos influenciados. Para ello, en esta tesis doctoral, nos centramos en analizar una red de interacciones para entender como la red subyacente es usada. Definimos una red de interacciones como una sequencia de interacciones grabadas en el tiempo E sobre aristas de un grafo estático G=(V, E). Las redes de interacción se pueden usar para modelar gran cantidad de aplicaciones reales, por ejemplo en una red social o de comunicaciones cada interacción sobre una arista representa una interacción entre dos usuarios (correo electrónico, llamada, retweet), o en el caso de una red financiera una interacción entre dos cuentas para representar una transacción. Analizamos las redes de interacción bajo múltiples escenarios. En el primero, estudiamos las redes de interacción bajo un modelo de ventana deslizante. Asumimos que un nodo puede mandar información a otros nodos si estan conectados utilizando aristas presentes en una ventana temporal. En este modelo, estudiamos como la importancia o centralidad de un nodo evoluciona en el tiempo. En el segundo escenario añadimos restricciones adicionales respecto como la información fluye entre nodos. Asumimos que un nodo puede mandar información a otros nodos solo si existe un camino temporal entre ellos. Para restringir la longitud de los caminos temporales también asumimos una ventana temporal. Aplicamos este modelo para resolver este problema de maximización de influencia restringido temporalmente. Analizando los datos de la red de interacción bajo nuestro modelo intentamos descubrir los k nodos más influyentes. Examinamos nuestro modelo en interacciones humano-a-humano, usando datos de redes sociales, como en ubicación-a-ubicación usando datos de redes sociales basades en localización (LBSNs). En el mismo escenario también minamos camínos cíclicos temporales para entender los patrones de comunicación en una red. Existen múltiples aplicaciones para cíclos temporales y aparecen naturalmente en redes de comunicación donde una persona envía un mensaje y después de un tiempo reacciona a una cadena de reacciones de compañeros en el mensaje. En redes financieras, por otro lado, la presencia de un ciclo temporal puede indicar ciertos tipos de fraude. Proponemos algoritmos eficientes para todos nuestros análisis y evaluamos su eficiencia y efectividad en datos reales. Finalmente, dado que muchos de los algoritmos estudiados tienen una gran demanda computacional, también estudiamos los algoritmos de procesado distribuido de grafos. Un aspecto importante de procesado distribuido de grafos es el de correctamente particionar los datos del grafo entre distintas máquinas. Gran cantidad de investigación se ha realizado en estrategias para particionar eficientemente un grafo, pero no existe un particionamento bueno para todos los tipos de grafos y algoritmos. Escoger la mejor estrategia de partición no es trivial y es mayoritariamente un ejercicio de prueba y error. Con tal de abordar este problema, proporcionamos un modelo de costes para dar un mejor entendimiento en como una estrategia de particionamiento actúa dado un grafo y un algoritmo.
Lei, Ma. "Distributed query processing using composite semijoins." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ62238.pdf.
Full textLiu, Ying. "Query optimization for distributed stream processing." [Bloomington, Ind.] : Indiana University, 2007. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3274258.
Full textSource: Dissertation Abstracts International, Volume: 68-07, Section: B, page: 4597. Adviser: Beth Plale. Title from dissertation home page (viewed Apr. 21, 2008).
McCue, Daniel Lawrence. "Selective transparency in distributed transaction processing." Thesis, University of Newcastle Upon Tyne, 1992. http://hdl.handle.net/10443/2020.
Full textJoyce, Elizabeth Mary. "Security in a distributed processing environment." Thesis, University of Plymouth, 2001. http://hdl.handle.net/10026.1/1638.
Full textArgile, Andrew Duncan Stuart. "Distributed processing in decision support systems." Thesis, Nottingham Trent University, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.259647.
Full textNewton, Ryan Rhodes 1980. "Language design for distributed stream processing." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/46795.
Full textThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (p. 149-152).
Applications that combine live data streams with embedded, parallel, and distributed processing are becoming more commonplace. WaveScript is a domain-specific language that brings high-level, type-safe, garbage-collected programming to these domains. This is made possible by three primary implementation techniques, each of which leverages characteristics of the streaming domain. First, WaveScript employs an evaluation strategy that uses a combination of interpretation and reification to partially evaluate programs into stream dataflow graphs. Second, we use profile-driven compilation to enable many optimizations that are normally only available in the synchronous (rather than asynchronous) dataflow domain. Finally, an empirical, profile-driven approach also allows us to compute practical partitions of dataflow graphs, spreading them across embedded nodes and more powerful servers. We have used our language to build and deploy applications, including a sensor-network for the acoustic localization of wild animals such as the Yellow-Bellied marmot. We evaluate WaveScript's performance on this application, showing that it yields good performance on both embedded and desktop-class machines. Our language allowed us to implement the application rapidly, while outperforming a previous C implementation by over 35%, using fewer than half the lines of code. We evaluate the contribution of our optimizations to this success. We also evaluate WaveScript's ability to extract parallelism from this and other applications.
by Ryan Rhodes Newton.
Ph.D.
Unnava, Vasundhara. "Query processing in distributed database systems." Connect to resource, 1992. http://rave.ohiolink.edu/etdc/view.cgi?acc%5Fnum=osu1261314105.
Full textLopes, Cassio Guimaraes. "Distributed cooperative strategies for adaptive processing." Diss., Restricted to subscribing institutions, 2008. http://proquest.umi.com/pqdweb?did=1581123071&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.
Full textKumar, Rohit. "Temporal Graph Mining and Distributed Processing." Doctoral thesis, Universite Libre de Bruxelles, 2018. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/271527.
Full textDoctorat en Sciences de l'ingénieur et technologie
info:eu-repo/semantics/nonPublished
Kotto, Kombi Roland. "Distributed query processing over fluctuating streams." Thesis, Lyon, 2018. http://www.theses.fr/2018LYSEI050/document.
Full textIn a Big Data context, stream processing has become a very active research domain. In order to manage ephemeral data (Velocity) arriving at important rates (Volume), some specific solutions, denoted data stream management systems (DSMSs),have been developed. DSMSs take as inputs some queries, called continuous queries,defined on a set of data streams. Acontinuous query generates new results as long as new data arrive in input. In many application domains, data streams haveinput rates and distribution of values which change over time. These variations may impact significantly processingrequirements for each continuous query.This thesis takes place in the ANR project Socioplug (ANR-13-INFR-0003). In this context, we consider a collaborative platformfor stream processing. Each user can submit multiple continuous queries and contributes to the execution support of theplatform. However, as each processing unit supporting treatments has limited resources in terms of CPU and memory, asignificant increase in input rate may cause the congestion of the system. The problem is then how to adjust dynamicallyresource usage to processing requirements for each continuous query ? It raises several challenges : i) how to detect a need ofreconfiguration ? ii) when reconfiguring the system to avoid its congestion at runtime ?In this work, we are interested by the different processing steps involved in the treatment of a continuous query over adistributed infrastructure. From this global analysis, we extract mechanisms enabling dynamic adaptation of resource usage foreach continuous query. We focus on automatic parallelization, or auto-parallelization, of operators composing the executionplan of a continuous query. We suggest an original approach based on the monitoring of operators and an estimation ofprocessing requirements in near future. Thus, we can increase (scale-out), or decrease (scale-in) the parallelism degree ofoperators in a proactive many such as resource usage fits to processing requirements dynamically. Compared to a staticconfiguration defined by an expert, we show that it is possible to avoid the congestion of the system in many cases or to delay itin most critical cases. Moreover, we show that resource usage can be reduced significantly while delivering equivalentthroughput and result quality. We suggest also to combine this approach with complementary mechanisms for dynamic adaptation of continuous queries at runtime. These differents approaches have been implemented within a widely used DSMS and have been tested over multiple and reproductible micro-benchmarks
CABIDDU, DANIELA. "Distributed processing of large triangle meshes." Doctoral thesis, Università degli Studi di Cagliari, 2016. http://hdl.handle.net/11584/266876.
Full textAl-Shakarchi, Ahmad. "Scalable audio processing across heterogeneous distributed resources : an investigation into distributed audio processing for Music Information Retrieval." Thesis, Cardiff University, 2013. http://orca.cf.ac.uk/47855/.
Full textDahlberg, Tobias. "Distributed Storage and Processing of Image Data." Thesis, Linköpings universitet, Databas och informationsteknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-85109.
Full textGottemukkala, Vibby. "Scalability issues in distributed and parallel databases." Diss., Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/8176.
Full textBennett, 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.
Full textJuntunen, R. (Risto). "Tradeoffs in distributed databases." Bachelor's thesis, University of Oulu, 2016. http://urn.fi/URN:NBN:fi:oulu-201602231230.
Full textGunaseelan, L. "Debugging of Distributed object systems." Diss., Georgia Institute of Technology, 1994. http://hdl.handle.net/1853/9219.
Full textNavaratnam, Srivallipuranandan. "Reliable group communication in distributed systems." Thesis, University of British Columbia, 1987. http://hdl.handle.net/2429/26505.
Full textScience, Faculty of
Computer Science, Department of
Graduate
Fukuzono, Hayato. "Spatial Signal Processing on Distributed MIMO Systems." 京都大学 (Kyoto University), 2016. http://hdl.handle.net/2433/217206.
Full textBelghoul, Abdeslem. "Optimizing Communication Cost in Distributed Query Processing." Thesis, Université Clermont Auvergne (2017-2020), 2017. http://www.theses.fr/2017CLFAC025/document.
Full textIn this thesis, we take a complementary look to the problem of optimizing the time for communicating query results in distributed query processing, by investigating the relationship between the communication time and the middleware configuration. Indeed, the middleware determines, among others, how data is divided into batches and messages before being communicated over the network. Concretely, we focus on the research question: given a query Q and a network environment, what is the best middleware configuration that minimizes the time for transferring the query result over the network? To the best of our knowledge, the database research community does not have well-established strategies for middleware tuning. We present first an intensive experimental study that emphasizes the crucial impact of middleware configuration on the time for communicating query results. We focus on two middleware parameters that we empirically identified as having an important influence on the communication time: (i) the fetch size F (i.e., the number of tuples in a batch that is communicated at once to an application consuming the data) and (ii) the message size M (i.e., the size in bytes of the middleware buffer, which corresponds to the amount of data that can be communicated at once from the middleware to the network layer; a batch of F tuples can be communicated via one or several messages of M bytes). Then, we describe a cost model for estimating the communication time, which is based on how data is communicated between computation nodes. Precisely, our cost model is based on two crucial observations: (i) batches and messages are communicated differently over the network: batches are communicated synchronously, whereas messages in a batch are communicated in pipeline (asynchronously), and (ii) due to network latency, it is more expensive to communicate the first message in a batch compared to any other message that is not the first in its batch. We propose an effective strategy for calibrating the network-dependent parameters of the communication time estimation function i.e, the costs of first message and non first message in their batch. Finally, we develop an optimization algorithm to effectively compute the values of the middleware parameters F and M that minimize the communication time. The proposed algorithm allows to quickly find (in small fraction of a second) the values of the middleware parameters F and M that translate a good trade-off between low resource consumption and low communication time. The proposed approach has been evaluated using a dataset issued from application in Astronomy
Wang, Yang. "Distributed parallel processing in networks of workstations." Ohio : Ohio University, 1994. http://www.ohiolink.edu/etd/view.cgi?ohiou1174328416.
Full textVijayakumar, Nithya Nirmal. "Data management in distributed stream processing systems." [Bloomington, Ind.] : Indiana University, 2007. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3278228.
Full textSource: Dissertation Abstracts International, Volume: 68-09, Section: B, page: 6093. Adviser: Beth Plale. Title from dissertation home page (viewed May 9, 2008).
Jonassen, Simon. "Efficient Query Processing in Distributed Search Engines." Doctoral thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-20206.
Full textMühleisen, Hannes [Verfasser]. "Architecture-independent distributed query processing / Hannes Mühleisen." Berlin : Freie Universität Berlin, 2013. http://d-nb.info/1031100261/34.
Full textAlgire, Martin. "Distributed multi-processing for high performance computing." Thesis, McGill University, 2000. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=31180.
Full textAl-Bassiouni, Abdel-Aziz Mahmoud. "Optimum signal processing in distributed sensor systems." Thesis, Monterey, California: U.S. Naval Postgraduate School, 1987. http://hdl.handle.net/10945/22401.
Full textWe consider the problem of detection of known signals in noise using quantized, discrete sensor observations. Optimal design of the quantizers at the sensor sites as well as the global fusion of the quantized observations is presented. Also the equivalence between a team of two sensors and their fusion centre and another team of a primary decision maker and a second opinion is shown. Since the fusion of information is a main pillar of the thesis, an early chapter is devoted to the optimum fusion policy. Extension of the results to the case of vector sensor observations is also considered
Wong, Kar Leong. "A message controller for distributed processing systems." Thesis, Nottingham Trent University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.312309.
Full textWang, Wei. "Distributed real-time processing for automotive applications." Thesis, Cranfield University, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.427159.
Full textMurphy, Donald P. "Parallel Distributed Processing of Realtime Telemetry Data." International Foundation for Telemetering, 1987. http://hdl.handle.net/10150/615233.
Full textAn architecture is described for Processing Multiple digital PCM telemetry streams. This architecture is implemented using a collection of Motorola mono-board microprocessor units (MPUs) in a single chassis called an Intermediate Processing Unit (IPU). Multiple IPUs can be integrated using a common input data bus. Each IPU is capable of processing a single PCM digital telemetry stream. Processing, in this context, includes conversion of raw sample count data to engineering units; computation of derived quantities from measurement sample data; calculation of minimum, maximum, average and cyclic [(maximum - minimum)/2] values for both measurement and derived data over a preselected time interval; out-of-limit, dropout and wildpoint detection; strip chart recording of selected data; transmission of both measurement and derived data to a high-speed, large-capacity disk storage subsystem; and transmission of compressed data to the host computer for realtime processing and display. All processing is done in realtime with at most two PCM major frames time latency.
Millar, Dean Lee. "Parallel distributed processing in rock engineering systems." Thesis, Imperial College London, 2008. http://hdl.handle.net/10044/1/37116.
Full textKanagasabapathy, Shri. "Distributed adaptive signal processing for frequency estimation." Thesis, Imperial College London, 2016. http://hdl.handle.net/10044/1/49783.
Full textMühleisen, Hannes Fabian [Verfasser]. "Architecture-independent distributed query processing / Hannes Mühleisen." Berlin : Freie Universität Berlin, 2013. http://nbn-resolving.de/urn:nbn:de:kobv:188-fudissthesis000000042056-2.
Full textCHEN, HONG. "A WEB-BASED DISTRIBUTED IMAGE PROCESSING SYSTEM." University of Cincinnati / OhioLINK, 2000. http://rave.ohiolink.edu/etdc/view?acc_num=ucin975338078.
Full textAndersson, Sara. "Data Processing and Collection in Distributed Systems." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-85313.
Full textDistribuerade system kan ses i en mängd olika applikationer som används idag. Tritech jobbar med flera produkter som till viss del består av distribuerade system av noder. Det dessa system har gemensamt är att noderna samlar in data och denna data kommer på ett eller ett annat sätt behöva bearbetas. En fråga som ofta behövs besvaras vid uppsättning av arkitekturen för sådana projekt är huruvida datan ska bearbetas, d.v.s. vilken arkitektkonfiguration som är mest lämplig för systemet. Att ta dessa beslut har visat sig inte alltid vara helt simpelt, och det ändrar sig relativt snabbt med den utvecklingen som sker på dessa områden. Denna uppsats syftar till att utföra en studie om vilka faktorer som påverkar valet av arkitektur för ett distribuerat system samt hur dessa faktorer förhåller sig mot varandra. För att kunna analysera vilka faktorer som påverkar valet av arkitektur och i vilken utsträckning, implementerades en simulator. Simulatorn tog faktorerna som input och returnerade en eller flera arkitekturkonfigurationer som output. Genom att utföra kvalitativa intervjuer valdes faktorerna till simulatorn. Faktorerna som analyserades i denna uppsats var: säkerhet, lagring, arbetsminne, storlek på data, antal noder, databearbetning per datamängd, robust kommunikation, batteriförbrukning och kostnad. Från de kvalitativa intervjuerna och från förstudien valdes även fem stycken arkitekturkonfigurationer. De valda arkitekturerna var: thin-client server, thick-client server, three-tier client-server, peer-to-peer, och cloud computing. Simulatorn validerades inom de tre givna användarfallen: lantbruk, tågindustri och industriell IoT. Valideringen bestod av fem befintliga projekt från Tritech. Från resultatet av valideringen producerade simulatorn korrekta resultat för tre av de fem projekten. Utifrån simulatorns resultat, kunde det ses vilka faktorer som påverkade mer vid valet av arkitektur och är svåra att kombinera i en och samma arkitekturkonfiguration. Dessa faktorer var säkerhet tillsammans med arbetsminne och robust kommunikation. Samt arbetsminne tillsammans med batteriförbrukning visade sig också vara faktorer som var svåra att kombinera i samma arkitektkonfiguration. Därför, enligt simulatorn, kan det ses att de faktorer som påverkar valet av arkitektur var arbetsminne, batteriförbrukning, säkerhet och robust kommunikation. Genom att använda simulatorns resultat utformades en beslutsmatris vars syfte var att underlätta valet av arkitektur. Utvärderingen av beslutsmatrisen bestod av fyra projekt från Tritech som inkluderade de tre givna användarfallen: lantbruk, tågindustrin och industriell IoT. Resultatet från utvärderingen av beslutsmatrisen visade att de två arkitekturerna som fick flest poäng, var en av arkitekturerna den som användes i det validerade projektet
Peng, Yanfeng. "Distributed processing, reconfigurable processes and active network." Thesis, Aston University, 2003. http://publications.aston.ac.uk/8005/.
Full textPeterson, Krystal, Samuel Richter, Adam Schafer, Steve Grant, and Kurt Kosbar. "DISTRIBUTED COMPUTING PROCESSOR FOR SIGNAL PROCESSING APPLICATIONS." International Foundation for Telemetering, 2016. http://hdl.handle.net/10150/624191.
Full textGao, Su. "Distributed signal processing using nested lattice codes." Thesis, Imperial College London, 2012. http://hdl.handle.net/10044/1/9238.
Full textEbrahimian, Mohammad Reza. "Power system operations : state estimation distributed processing /." Digital version accessible at:, 1999. http://wwwlib.umi.com/cr/utexas/main.
Full textDrougas, Ioannis. "Rate allocation in distributed stream processing systems." Diss., [Riverside, Calif.] : University of California, Riverside, 2008. http://proquest.umi.com/pqdweb?index=0&did=1663077971&SrchMode=2&sid=1&Fmt=2&VInst=PROD&VType=PQD&RQT=309&VName=PQD&TS=1268240766&clientId=48051.
Full textIncludes abstract. Title from first page of PDF file (viewed March 10, 2010). Available via ProQuest Digital Dissertations. Includes bibliographical references (p. 93-98). Also issued in print.
Xu, Songcen. "Distributed signal processing algorithms for wireless networks." Thesis, University of York, 2015. http://etheses.whiterose.ac.uk/9516/.
Full textXia, Yu S. M. Massachusetts Institute of Technology. "Logical timestamps in distributed transaction processing systems." Thesis, Massachusetts Institute of Technology, 2018. https://hdl.handle.net/1721.1/122877.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (pages 73-79).
Distributed transactions are such transactions with remote data access. They usually suffer from high network latency (compared to the internal overhead) during data operations on remote data servers, and therefore lengthen the entire transaction executiont time. This increases the probability of conflicting with other transactions, causing high abort rates. This, in turn, causes poor performance. In this work, we constructed Sundial, a distributed concurrency control algorithm that applies logical timestamps seaminglessly with a cache protocol, and works in a hybrid fashion where an optimistic approach is combined with lock-based schemes. Sundial tackles the inefficiency problem in two ways. Firstly, Sundial decides the order of transactions on the fly. Transactions get their commit timestamp according to their data access traces. Each data item in the database has logical leases maintained by the system. A lease corresponds to a version of the item. At any logical time point, only a single transaction holds the 'lease' for any particular data item. Therefore, lease holders do not have to worry about someone else writing to the item because in the logical timeline, the data writer needs to acquire a new lease which is disjoint from the holder's. This lease information is used to calculate the logical commit time for transactions. Secondly, Sundial has a novel caching scheme that works together with logical leases. The scheme allows the local data server to automatically cache data from the remote server while preserving data coherence. We benchmarked Sundial along with state-of-the-art distributed transactional concurrency control protocols. On YCSB, Sundial outperforms the second best protocol by 57% under high data access contention. On TPC-C, Sundial has a 34% improvement over the state-of-the-art candidate. Our caching scheme has performance gain comparable with hand-optimized data replication. With high access skew, it speeds the workload by up to 4.6 x.
"This work was supported (in part) by the U.S. National Science Foundation (CCF-1438955)"
by Yu Xia.
S.M.
S.M. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
Sun, Yudong. "A distributed object model for solving irregularly structured problems on distributed systems /." Hong Kong : University of Hong Kong, 2001. http://sunzi.lib.hku.hk/hkuto/record.jsp?B23501662.
Full text