Literatura académica sobre el tema "Data storage reduction"
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Artículos de revistas sobre el tema "Data storage reduction"
Bostoen, Tom, Sape Mullender y Yolande Berbers. "Power-reduction techniques for data-center storage systems". ACM Computing Surveys 45, n.º 3 (junio de 2013): 1–38. http://dx.doi.org/10.1145/2480741.2480750.
Texto completoSinghal, Shubhanshi, Pooja Sharma, Rajesh Kumar Aggarwal y Vishal Passricha. "A Global Survey on Data Deduplication". International Journal of Grid and High Performance Computing 10, n.º 4 (octubre de 2018): 43–66. http://dx.doi.org/10.4018/ijghpc.2018100103.
Texto completoTong, Yulai, Jiazhen Liu, Hua Wang, Ke Zhou, Rongfeng He, Qin Zhang y Cheng Wang. "Sieve: A Learned Data-Skipping Index for Data Analytics". Proceedings of the VLDB Endowment 16, n.º 11 (julio de 2023): 3214–26. http://dx.doi.org/10.14778/3611479.3611520.
Texto completoSheetal, Annabathula Phani, Giddaluru Lalitha, Arepalli Peda Gopi y Vejendla Lakshman Narayana. "Secured Data Transmission with Integrated Fault Reduction Scheduling in Cloud Computing". Ingénierie des systèmes d information 26, n.º 2 (30 de abril de 2021): 225–30. http://dx.doi.org/10.18280/isi.260209.
Texto completoMing-Huang Chiang, David, Chia-Ping Lin y Mu-Chen Chen. "Data mining based storage assignment heuristics for travel distance reduction". Expert Systems 31, n.º 1 (26 de diciembre de 2012): 81–90. http://dx.doi.org/10.1111/exsy.12006.
Texto completoSzekely, Geza, Th Lindblad, L. Hildingsson y W. Klamra. "On the reduction of data storage from high-dispersion experiments". Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 292, n.º 2 (julio de 1990): 431–34. http://dx.doi.org/10.1016/0168-9002(90)90398-p.
Texto completoYasuda, Shin, Jiro Minabe y Katsunori Kawano. "Optical noise reduction for dc-removed coaxial holographic data storage". Optics Letters 32, n.º 2 (23 de diciembre de 2006): 160. http://dx.doi.org/10.1364/ol.32.000160.
Texto completoFirtha, Ferenc. "Development of data reduction function for hyperspectral imaging". Progress in Agricultural Engineering Sciences 3, n.º 1 (1 de diciembre de 2007): 67–88. http://dx.doi.org/10.1556/progress.3.2007.4.
Texto completoAbd Manan, Wan Nurazieelin Wan y Mohamad Aizi Salamat. "Concept of minimizing the response time for reducing dynamic data redundancy in cloud computing". Indonesian Journal of Electrical Engineering and Computer Science 15, n.º 3 (1 de septiembre de 2019): 1597. http://dx.doi.org/10.11591/ijeecs.v15.i3.pp1597-1602.
Texto completoKim, Jang Hyun y Hyunseok Yang. "TuC-1-4 NOISE REDUCTION METHOD USING EXTENDED KALMAN FILTER FOR TILT SERVO CONTROL IN HOLOGRAPHIC DATA STORAGE SYSTEM". Proceedings of JSME-IIP/ASME-ISPS Joint Conference on Micromechatronics for Information and Precision Equipment : IIP/ISPS joint MIPE 2015 (2015): _TuC—1–4–1—_TuC—1–4–3. http://dx.doi.org/10.1299/jsmemipe.2015._tuc-1-4-1.
Texto completoTesis sobre el tema "Data storage reduction"
Huffman, Michael John. "JDiet: Footprint Reduction for Memory-constrained Systems". DigitalCommons@CalPoly, 2009. https://digitalcommons.calpoly.edu/theses/108.
Texto completoDini, Cosmin. "Mécanismes de traitement des données dans les réseaux de capteurs sans fils dans les cas d'accès intermittent à la station de base". Phd thesis, Université de Haute Alsace - Mulhouse, 2010. http://tel.archives-ouvertes.fr/tel-00576919.
Texto completoMajed, Aliah. "Sensing-based self-reconfigurable strategies for autonomous modular robotic systems". Electronic Thesis or Diss., Brest, École nationale supérieure de techniques avancées Bretagne, 2022. http://www.theses.fr/2022ENTA0013.
Texto completoModular robotic systems (MRSs) have become a highly active research today. It has the ability to change the perspective of robotic systems from machines designed to do certain tasks to multipurpose tools capable of accomplishing almost any task. They are used in a wide range of applications, including reconnaissance, rescue missions, space exploration, military task, etc. Constantly, MRS is built of “modules” from a few to several hundreds or even thousands. Each module involves actuators, sensors, computational, and communicational capabilities. Usually, these systems are homogeneous where all the modules are identical; however, there could be heterogeneous systems that contain different modules to maximize versatility. One of the advantages of these systems is their ability to operate in harsh environments in which contemporary human-in-the-loop working schemes are risky, inefficient and sometimes infeasible. In this thesis, we are interested in self-reconfigurable modular robotics. In such systems, it uses a set of detectors in order to continuously sense its surroundings, locate its own position, and then transform to a specific shape to perform the required tasks. Consequently, MRS faces three major challenges. First, it offers a great amount of collected data that overloads the memory storage of the robot. Second it generates redundant data which complicates the decision making about the next morphology in the controller. Third, the self reconfiguration process necessitates massive communication between the modules to reach the target morphology and takes a significant processing time to self-reconfigure the robotic. Therefore, researchers’ strategies are often targeted to minimize the amount of data collected by the modules without considerable loss in fidelity. The goal of this reduction is first to save the storage space in the MRS, and then to facilitate analyzing data and making decision about what morphology to use next in order to adapt to new circumstances and perform new tasks. In this thesis, we propose an efficient mechanism for data processing and self-reconfigurable decision-making dedicated to modular robotic systems. More specifically, we focus on data storage reduction, self-reconfiguration decision-making, and efficient communication management between modules in MRSs with the main goal of ensuring fast self-reconfiguration process
"Kernel-space inline deduplication file systems for virtual machine image storage". 2013. http://library.cuhk.edu.hk/record=b5549294.
Texto completoWe explore the use of deduplication for eliminating the storage of redundant data in RAID from a file-system design perspective. We propose ScaleDFS, a deduplication file system that seeks to achieve scalable read/write throughput in RAID. ScaleDFS is built on three novel design features. First, we improve the write throughput by exploiting multiple CPU cores to parallelize the processing of the cryptographic fingerprints that are used to identify redundant data. Second, we improve the read throughput by specifically caching in memory the recently read blocks that have been deduplicated. Third, we reduce the memory usage by enhancing the data structures that are used for fingerprint lookups. ScaleDFS is implemented as a POSIX-compliant, kernel-space driver module that can be deployed in commodity hardware configurations. We conduct microbenchmark experiments using synthetic workloads, and macrobenchmark experiments using a dataset of 42 VM images of different Linux distributions. We show that ScaleDFS achieves higher read/write throughput than existing open-source deduplication file systems in RAID.
Detailed summary in vernacular field only.
Ma, Mingcao.
"October 2012."
Thesis (M.Phil.)--Chinese University of Hong Kong, 2013.
Includes bibliographical references (leaves 39-42).
Abstracts also in Chinese.
Chapter 1 --- Introduction --- p.2
Chapter 2 --- Literature Review --- p.5
Chapter 2.1 --- Backup systems --- p.5
Chapter 2.2 --- Use of special hardware --- p.6
Chapter 2.3 --- Scalable storage --- p.6
Chapter 2.4 --- Inline DFSs --- p.6
Chapter 2.5 --- VM image storage with deduplication --- p.7
Chapter 3 --- ScaleDFS Background --- p.8
Chapter 3.1 --- Spatial Locality of Fingerprint Placement --- p.9
Chapter 3.2 --- Prefetching of Fingerprint Stores --- p.12
Chapter 3.3 --- Journaling --- p.13
Chapter 4 --- ScaleDFS Design --- p.15
Chapter 4.1 --- Parallelizing Deduplication --- p.15
Chapter 4.2 --- Caching Read Blocks --- p.17
Chapter 4.3 --- Reducing Memory Usage --- p.17
Chapter 5 --- Implementation --- p.20
Chapter 5.1 --- Choice of Hash Function --- p.20
Chapter 5.2 --- OpenStack Deployment --- p.21
Chapter 6 --- Experiments --- p.23
Chapter 6.1 --- Microbenchmarks --- p.23
Chapter 6.2 --- OpenStack Deployment --- p.28
Chapter 6.3 --- VM Image Operations in a RAID Setup --- p.33
Chapter 7 --- Conclusions and FutureWork --- p.38
Bibliography --- p.39
"Live deduplication storage of virtual machine images in an open-source cloud". 2012. http://library.cuhk.edu.hk/record=b5549139.
Texto completoDeduplication is a technique that eliminates the storage of redundant data blocks. In particular, it has been shown to effectively reduce the disk space for storing multi-gigabyte virtual machine (VM) images. However, there remain challenging deployment issues of enabling deduplication in a cloud platform, where VM images are regularly inserted and retrieved. We propose a kernel-space deduplication file systems called LiveDFS, which can serve as a VM image storage backend in an open-source cloud platform that is built on low-cost commodity hardware configurations. LiveDFS is built on several novel design features. Specifically, the main feature of LiveDFS is to exploit spatial locality of placing deduplication metadata on disk with respect to the underlying file system layout. LiveDFS is POSIX-compliant and is implemented as Linux kernel-space file systems. We conduct testbed experiments of the read/write performance of LiveDFS using a dataset of 42 VM images of different Linux distributions. Our work justifies the feasibility of deploying LiveDFS in a cloud platform under commodity settings.
Detailed summary in vernacular field only.
Ng, Chun Ho.
Thesis (M.Phil.)--Chinese University of Hong Kong, 2012.
Includes bibliographical references (leaves 39-42).
Abstracts also in Chinese.
Chapter 1 --- Introduction --- p.1
Chapter 2 --- LiveDFS Design --- p.5
Chapter 2.1 --- File System Layout --- p.5
Chapter 2.2 --- Deduplication Primitives --- p.6
Chapter 2.3 --- Deduplication Process --- p.8
Chapter 2.3.1 --- Fingerprint Store --- p.9
Chapter 2.3.2 --- Fingerprint Filter --- p.11
Chapter 2.4 --- Prefetching of Fingerprint Stores --- p.14
Chapter 2.5 --- Journaling --- p.15
Chapter 2.6 --- Ext4 File System --- p.17
Chapter 3 --- Implementation Details --- p.18
Chapter 3.1 --- Choice of Hash Function --- p.18
Chapter 3.2 --- OpenStack Deployment --- p.19
Chapter 4 --- Experiments --- p.21
Chapter 4.1 --- I/O Throughput --- p.21
Chapter 4.2 --- OpenStack Deployment --- p.26
Chapter 5 --- Related Work --- p.34
Chapter 6 --- Conclusions and Future Work --- p.37
Bibliography --- p.39
Libros sobre el tema "Data storage reduction"
SINGH, Dr ANIMESH, Dr BHAWNA CHOUDHARY y Dr MANISHA GUPTA. TRANSFORMING BUSINESS THROUGH DIGITALIZATION. KAAV PUBLICATIONS, DELHI, INDIA, 2021. http://dx.doi.org/10.52458/9789391842390.2021.eb.
Texto completoMaugeri, Leonardo. Beyond the Age of Oil. ABC-CLIO, LLC, 2010. http://dx.doi.org/10.5040/9798400618161.
Texto completoCapítulos de libros sobre el tema "Data storage reduction"
Čtvrtník, Mikuláš. "Data Minimisation—Storage Limitation—Archiving". En Archives and Records, 197–240. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-18667-7_8.
Texto completoLofstead, Jay, Gregory Jean-Baptiste y Ron Oldfield. "Delta: Data Reduction for Integrated Application Workflows and Data Storage". En Lecture Notes in Computer Science, 142–52. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46079-6_11.
Texto completoMa, Jeonghyeon y Chanik Park. "Parallelizing Inline Data Reduction Operations for Primary Storage Systems". En Lecture Notes in Computer Science, 301–7. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62932-2_29.
Texto completoZou, Ruobing, Oscar C. Au, Lin Sun, Sijin Li y Wei Dai. "An Adaptive Motion Data Storage Reduction Method for Temporal Predictor". En Advances in Image and Video Technology, 48–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25346-1_5.
Texto completoYu, Wangyang, Guanjun Liu y Leifeng He. "A Reduction Method of Analyzing Data-Liveness and Data-Boundedness for a Class of E-commerce Business Process Nets". En Security, Privacy, and Anonymity in Computation, Communication, and Storage, 70–83. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49148-6_7.
Texto completoChakravarthy, S. Kalyan, N. Sudhakar, E. Srinivasa Reddy, D. Venkata Subramanian y P. Shankar. "Dimension Reduction and Storage Optimization Techniques for Distributed and Big Data Cluster Environment". En Soft Computing and Medical Bioinformatics, 47–54. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0059-2_6.
Texto completoChandrasekhar, A. Poorna y T. Sobha Rani. "Storage and Retrieval of Large Data Sets: Dimensionality Reduction and Nearest Neighbour Search". En Communications in Computer and Information Science, 262–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32129-0_29.
Texto completoZhang, Guanglin, Kaijiang Yi, Wenqian Zhang y Demin Li. "Cost Reduction for Micro-Grid Powered Data Center Networks with Energy Storage Devices". En Wireless Algorithms, Systems, and Applications, 647–59. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94268-1_53.
Texto completoSethuramalingam, R., Abhishek Asthana, S. Xygkaki, K. Liu, J. Eduardo, S. Wilson y C. Bater. "Energy Demand Reduction in Data Centres Using Computational Fluid Dynamics". En Springer Proceedings in Energy, 275–84. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-30960-1_26.
Texto completoTamura, Takao. "Improvement of the Flood-Reduction Function of Forests Based on Their Interception Evaporation and Surface Storage Capacities". En Ecological Research Monographs, 93–104. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-6791-6_7.
Texto completoActas de conferencias sobre el tema "Data storage reduction"
Nakajima, M., M. Hamada, M. Moribe, H. Hirano, K. Itoh y S. Ogawa. "Reduction of Media Noise in Optical Disks". En Optical Data Storage. Washington, D.C.: Optica Publishing Group, 1985. http://dx.doi.org/10.1364/ods.1985.thcc5.
Texto completoOkubo, Shuichi, Masayuki Kubogata y Mitsuya Okada. "Reduction of cross erase in phase change media". En Optical Data Storage. Washington, D.C.: Optica Publishing Group, 1998. http://dx.doi.org/10.1364/ods.1998.wb.3.
Texto completoUshiyama, Junko, Yasushi Miyauchi, Toshinori Sugiyama, Toshimichi Shintani, Takahiro Kurokawa y Harukazu Miyamoto. "Interlayer Cross-talk Reduction by Controlling Backward Reflectivity for Multilayer Disks". En Optical Data Storage. Washington, D.C.: OSA, 2007. http://dx.doi.org/10.1364/ods.2007.wdpdp3.
Texto completoOkubo, Shuichi, Masayuki Kubogata y Mitsuya Okada. "Reduction of cross-erase in phase-change media". En Optical Data Storage '98, editado por Shigeo R. Kubota, Tomas D. Milster y Paul J. Wehrenberg. SPIE, 1998. http://dx.doi.org/10.1117/12.327934.
Texto completoEto, Soichiro, Hiroyuki Minemura, Yumiko Anzai y Toshimichi Shintani. "Disc Design for Reduction of Random Data Bit Error Rate in Super-Resolution". En Optical Data Storage. Washington, D.C.: OSA, 2007. http://dx.doi.org/10.1364/ods.2007.wdpdp5.
Texto completoKim, Hye-Rim, Ki-Mun Pak, Ji-Song Lim y Yong-Hyub Won. "Error reduction in reconstruction of kinoform CGH patterns for a hologram ID tag system". En Optical Data Storage 2010, editado por Susanna Orlic y Ryuichi Katayama. SPIE, 2010. http://dx.doi.org/10.1117/12.858951.
Texto completoMilster, Tom D., Robert M. Trusty, Mark S. Wang, Fred F. Froehlich y J. Kevin Erwin. "Micro-optic lens for data storage". En Optical Data Storage. Washington, D.C.: Optica Publishing Group, 1991. http://dx.doi.org/10.1364/ods.1991.tud3.
Texto completovan Rosmalen, G. E., J. A. H. Kahlman y C. M. J. van Uijen. "A Compact, One-Laser, Optical Tape Recording System for High-Definition Digital Video". En Optical Data Storage. Washington, D.C.: Optica Publishing Group, 1994. http://dx.doi.org/10.1364/ods.1994.mb3.
Texto completoLu, Maohua, David Chambliss, Joseph Glider y Cornel Constantinescu. "Insights for data reduction in primary storage". En the 5th Annual International Systems and Storage Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2367589.2367606.
Texto completoGardner, K., PR Helfet, RJ Longman y RM Pettigrew. "Plasmon Media Technology". En Optical Data Storage. Washington, D.C.: Optica Publishing Group, 1985. http://dx.doi.org/10.1364/ods.1985.wdd4.
Texto completoInformes sobre el tema "Data storage reduction"
LaBonte, Don, Etan Pressman, Nurit Firon y Arthur Villordon. Molecular and Anatomical Characterization of Sweetpotato Storage Root Formation. United States Department of Agriculture, diciembre de 2011. http://dx.doi.org/10.32747/2011.7592648.bard.
Texto completoBadia, R., J. Ejarque, S. Böhm, C. Soriano y R. Rossi. D4.4 API and runtime (complete with documentation and basic unit testing) for IO employing fast local storage. Scipedia, 2021. http://dx.doi.org/10.23967/exaqute.2021.9.001.
Texto completoBerkowitz, Jacob, Nathan Beane, Kevin Philley, Nia Hurst y Jacob Jung. An assessment of long-term, multipurpose ecosystem functions and engineering benefits derived from historical dredged sediment beneficial use projects. Engineer Research and Development Center (U.S.), agosto de 2021. http://dx.doi.org/10.21079/11681/41382.
Texto completoCoulson, Wendy, Tom McGrath y James McCarthy. PR-312-16202-R03 Methane Emissions from Transmission and Storage Subpart W Sources. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), septiembre de 2019. http://dx.doi.org/10.55274/r0011619.
Texto completoLichter, Amnon, Joseph L. Smilanick, Dennis A. Margosan y Susan Lurie. Ethanol for postharvest decay control of table grapes: application and mode of action. United States Department of Agriculture, julio de 2005. http://dx.doi.org/10.32747/2005.7587217.bard.
Texto completoBotulinum Neurotoxin-Producing Clostridia, Working Group on. Report on Botulinum Neurotoxin-Producing Clostridia. Food Standards Agency, agosto de 2023. http://dx.doi.org/10.46756/sci.fsa.ozk974.
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