Relevant bibliographies by topics / Computer Storage Optimization

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Computer Storage Optimization'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 September 2023

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Journal articles on the topic "Computer Storage Optimization"

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Allen, Frances E., and Janet Fabri. "Automatic storage optimization." ACM SIGPLAN Notices 39, no. 4 (2004): 28–37. http://dx.doi.org/10.1145/989393.989398.

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Yolchuyev, Agil, and Janos Levendovszky. "Data Chunks Placement Optimization for Hybrid Storage Systems." Future Internet 13, no. 7 (2021): 181. http://dx.doi.org/10.3390/fi13070181.

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“Hybrid Cloud Storage” (HCS) is a widely adopted framework that combines the functionality of public and private cloud storage models to provide storage services. This kind of storage is especially ideal for organizations that seek to reduce the cost of their storage infrastructure with the use of “Public Cloud Storage” as a backend to on-premises primary storage. Despite the higher performance, the hybrid cloud has latency issues, related to the distance and bandwidth of the public storage, which may cause a significant drop in the performance of the storage systems during data transfer. This issue can become a major problem when one or more private storage nodes fail. In this paper, we propose a new framework for optimizing the data uploading process that is currently used with hybrid cloud storage systems. The optimization is concerned with spreading the data over the multiple storages in the HCS system according to some predefined objective functions. Furthermore, we also used Network Coding technics for minimizing data transfer latency between the receiver (private storages) and transmitter nodes.
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Hofmann, René, Sabrina Dusek, Stephan Gruber, and Gerwin Drexler-Schmid. "Design Optimization of a Hybrid Steam-PCM Thermal Energy Storage for Industrial Applications." Energies 12, no. 5 (2019): 898. http://dx.doi.org/10.3390/en12050898.

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The efficiency of industrial processes can be increased by balancing steam production and consumption with a Ruths steam storage system. The capacity of this storage type depends strongly on the volume; therefore, a hybrid storage concept was developed, which combines a Ruths steam storage with phase change material. The high storage capacity of phase change material can be very advantageous, but the low thermal conductivity of this material is a limiting factor. On the contrary, Ruths steam storages have fast reaction times, meaning that the hybrid storage concept should make use of the advantages and compensate for the disadvantages of both storage types. To answer the question on whether this hybrid storage concept is economically feasible, a non-linear design optimization tool for a hybrid storage system is presented. From a preliminary approximation, the results show that the costs of hybrid storage can be reduced, in comparison to a Ruths steam storage with the same storage capacity. Furthermore, a possible hybrid storage design for a real industrial implementation is discussed. Based on further analyses, it was shown that under certain conditions, the retrofitting of a conventional Ruths steam storage to a hybrid storage can be advantageous and cost-effective, compared to an additional Ruths steam storage.
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Gagliardi, Marco, and Cosimo Spera. "Optimization models for computer data storage design: An application." Computers & Industrial Engineering 26, no. 4 (1994): 743–56. http://dx.doi.org/10.1016/0360-8352(94)90009-4.

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Joisha, Pramod G., and Prithviraj Banerjee. "Static array storage optimization in MATLAB." ACM SIGPLAN Notices 38, no. 5 (2003): 258–68. http://dx.doi.org/10.1145/780822.781160.

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Melikov, A. Z., and A. A. Molchanov. "Stock optimization in transportation/storage systems." Cybernetics and Systems Analysis 28, no. 3 (1992): 484–87. http://dx.doi.org/10.1007/bf01125431.

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Kim, Younghyun. "Computer-Aided Design and Optimization of Hybrid Energy Storage Systems." Foundations and Trends® in Electronic Design Automation 7, no. 4 (2013): 247–338. http://dx.doi.org/10.1561/1000000035.

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Engelfriet, Joost, and Willem de Jong. "Attribute storage optimization by stacks." Acta Informatica 27, no. 6 (1990): 567–81. http://dx.doi.org/10.1007/bf00277390.

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Jiang, L., and C. W. Wu. "Topology optimization of energy storage flywheel." Structural and Multidisciplinary Optimization 55, no. 5 (2016): 1917–25. http://dx.doi.org/10.1007/s00158-016-1576-1.

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Wang, Xun, and Jie Rong. "The Computer Network Optimization Model Based on Neural Network Algorithm Research." Advanced Materials Research 798-799 (September 2013): 545–48. http://dx.doi.org/10.4028/www.scientific.net/amr.798-799.545.

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The speed of development of the computer network is an urgent need to comprehensively improve and optimize the overall performance of the network. Neural network algorithm has a massively parallel processing and distributed information storage, Hopfield neural network showed a unique advantage in the associative memory and optimization based on the neural network algorithm for computer network optimization model of Hopfield neural network theory and reality computer network, modern optimization methods, it is combined.
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Dissertations / Theses on the topic "Computer Storage Optimization"

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Thies, William Frederick 1978. "A unified framework for scheduling and storage optimization." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/87842.

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Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.<br>Includes bibliographical references (p. 65-67).<br>by William Frederick Thies.<br>M.Eng.
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Edwards, Laura E. (Laura Elaine). "Optimization of data storage for the adaptive transformer monitoring system." Thesis, Massachusetts Institute of Technology, 1992. http://hdl.handle.net/1721.1/12770.

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Thesis (B.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1992.<br>Includes bibliographical references (leaves 150-151).<br>by Laura E. Edwards.<br>B.S.
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Tandon, Ashish. "Analysis and optimization of data storage using enhanced object models in the .NET framework." Thesis, Edinburgh Napier University, 2007. http://researchrepository.napier.ac.uk/Output/4047.

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The purpose of thesis is to benchmark the database to examine and analyze the performance using the Microsoft COM+ the most commonly used component framework heavily used for developing component based applications. The prototype application based on Microsoft Visual C#.NET language used to benchmark the database performance on Microsoft .NET Framework environment 2.0 and 3.0 using the different sizes of data range from low (100 Rows) to high volume (10000 Rows) of data with five or ten number of users connections. There are different type of application used like COM+, Non-COM+ and .NET based application to show their performance on the different volume of data with specified numbers of user on the .NET Framework 2.0 and 3.0. The result has been analyzed and collected using the performance counter variables of an operating system and used Microsoft .NET class libraries which help in collecting system's level performance information as well. This can be beneficial to developers, stakeholders and management to decide the right technology to be used in conjunction with a database. The results and experiments conducted in this project results in the substantial gain in the performance, scalability and availability of component based application using the Microsoft COM+ features like object pooling, application pooling, role- based, transactions isolation and constructor enabled. The outcome of this project is that Microsoft COM+ component based application provides optimized database performance results using the SQL Server. There is a performance gain of at least 10% in the COM+ based application as compared to the Non COM+ based application. COM+ services features come at the performance penalty. It has been noticed that there is a performance difference between the COM+ based application and the application based on role based security, constructor enable and transaction isolation of around 15%, 20% and 35% respectively. The COM+ based application provides performance gain of around 15% and 45% on the low and medium volume of data on a .NET Framework 2.0 in comparison to 3.0. There is a significant gain in the COM+ Server based application on .NET Framework 3.0 of around 10% using high volume of data. This depicts that high volume of data application works better with Framework 3.0 as compared to 2.0 on SQL Server. The application performance type results represents that COM+ component based application provides better performance results over Non-COM+ and .NET based application. The difference between the performance of COM+ application based on low and medium volume of data was around 20% and 30%. .NET based application performs better on the high volume of data results in performance gain of around 10%. Similarly more over the same results provided on the test conducted on the MS Access. Where COM+ based application running under .NET Framework 2.0 performs better result other than the Non-COM+ and .NET based application on a low and medium volume of data and .NET Framework 3.0 based COM+ application performs better results on high volume of data.
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Bonadies, Monica. "Analysis and optimization of a solar thermal collector with integrated storage." Master's thesis, University of Central Florida, 2010. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4531.

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Solar energy, a topic popular in the United States during the oil embargo of the 1970?'s, has become a relevant topic once more with the current focus on reducing greenhouse emissions. Solar thermal energy in particular has become popular as it uses existing steam turbine technology to produce electricity, with the benefit of using solar energy to produce steam rather than coal or nuclear heat sources. Solar thermal can also be used at lower temperatures to heat water for pools or for residential use. While this energy source has its benefits, it has the problem of being opportunistic ?? the energy must be used as it is captured. With the integration of storage, a solar thermal system becomes more viable for use. In this work, a low temperature (50-70o C) thermal storage unit with a solar thermal collector is experimentally run then studied using both analytical and numerical methods. With these methods, suggestions for future developments of the storage unit are made. The prototype collector and storage combination tested worked best during the winter months, when there was low humidity. Furthermore, the heat exchanger design within the storage unit was found to work well for charging (heating) the unit, but not for discharging the storage to heat water. The best modeling method for the storage unit was the use of FLUENT, which would allow for the suggested changes to the prototype to be simulated before the next prototype was constructed.<br>ID: 028731128; System requirements: World Wide Web browser and PDF reader.; Mode of access: World Wide Web.; Thesis (M.S.M.E.)--University of Central Florida, 2010.; Includes bibliographical references.<br>M.S.M.E.<br>Masters<br>Department of Mechanical, Materials and Aerospace Engineering<br>Engineering and Computer Science<br>Thermofluids
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Helkin, Steven Alexander. "Design and optimization of a wave energy harvester utilizing a flywheel energy storage system." Master's thesis, University of Central Florida, 2011. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4774.

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This thesis details the design and optimization of a buoy used to collect renewable energy from ocean waves. The proposed buoy is a point absorber--a device that transforms the kinetic energy of the vertical motion of surface waves into electrical energy. The focus of the research is on the mechanical system used to collect the energy, and methods to improve it for eventual use in an actual wave energy harvester. A flywheel energy storage system was utilized in order to provide an improved power output from the system, even with the intermittent input of force exerted by ocean waves. A series of laboratory prototypes were developed to analyze parameters that are important to the success of the point absorb mechanical system. By introducing a velocity-based load control scheme in conjunction with flywheel energy storage, it was seen that the average power output by the prototype was increased. The generator load is controlled via a relay switch that removes electrical resistance from the generator--this sacrifices time during which power is drawn from the system, but also allows the buoy to move with less resistance. A simulation model was developed in order to analyze the theoretical wave absorber system and optimize the velocity threshold parameters used in the load control. Results indicate that the power output by the system can be substantially improved through the use of a flywheel energy storage control scheme that engages and disengages the electrical load based on the rotational velocity of the flywheel system. The results of the optimization are given for varying-sized generator systems input into the simulation in order to observe the associated trends.<br>ID: 030646228; System requirements: World Wide Web browser and PDF reader.; Mode of access: World Wide Web.; Thesis (M.S.M.E.)--University of Central Florida, 2011.; Includes bibliographical references (p. 111-114).<br>M.S.M.E.<br>Masters<br>Mechanical and Aerospace Engineering<br>Engineering and Computer Science<br>Mechanical Engineering; Computer Aided Mechanical Engineering Track
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Ku, Daniel C. (Daniel Chung-Ming) 1985. "Methodology, morphology, and optimization of carbon nanotube growth for improved energy storage in a double layer capacitor." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/63028.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 77-80).<br>The goal of this thesis is to optimize the growth of carbon nanotubes (CNTs) on a conducting substrate for use as an electrode to improve energy density in a double-layer capacitor. The focus has been on several areas, such as substrate material, growth conditions, catalyst variations, and thin-film deposition techniques in order to achieve growth of a high density, vertically-aligned carbon nanotube array suitable for use as an electrode. This thesis describes the methodology of modifying a significant number of parameters in order to achieve all of the targeted electrode specifications, with the exception of nanotube density. The successful growth of a CNT array on an aluminum foil substrate marks an important milestone for realizing a future commercial product.<br>by Daniel C. Ku.<br>S.M.
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Komaragiri, Vivek Chakravarthy. "Application of decision diagrams for information storage and retrieval." Master's thesis, Mississippi State : Mississippi State University, 2002. http://library.msstate.edu/etd/show.asp?etd=etd-04082002-144345.

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Chen, Feng. "On Performance Optimization and System Design of Flash Memory based Solid State Drives in the Storage Hierarchy." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1280537880.

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Barrett, Emily Lord. "The Investigation and Optimization of a Two-Heat-Pump System Incorporating Thermal Storage for Shaping Residential Heating Load." PDXScholar, 2016. http://pdxscholar.library.pdx.edu/open_access_etds/3025.

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Portland General Electric has proposed coupling one or more water tanks with two heat pumps in order to perform load-shifting in residential customer heating and cooling applications. By using the water tanks as a thermal storage unit, this project attempts to partially decouple energy consumption from generation to provide peak demand reduction and to better facilitate the integration of variable renewable energy resources. A scoping study was performed to evaluate the potential impact of this project if implemented in single family homes in Portland, Oregon. This study revealed that the system could provide meaningful savings in the cost of electricity to both the customer and utility. Additionally, an optimization algorithm was developed to dictate system operation and to maximize gains to the utility. Evolutionary algorithms were explored in an attempt to increase the effectiveness of the algorithm's search in limited computation time. Ultimately, an evolution strategy was selected as the most suitable based on tests run in winter and spring months. A genetic algorithm was then developed to handle fixed-speed heat pump operation for compatibility with an alpha-system prototype that has been developed by the research team.
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Mihailovic, Nemanja. "A Cost Benefit Analysis of Using a Battery Energy Storage System (BESS) Represented by a Unit Commitment Model." Scholar Commons, 2018. https://scholarcommons.usf.edu/etd/7548.

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This thesis aims to provide a general overview of a cost and benefit analysis of incorporating a battery energy storage system within unit commitment model. The deregulation of the electricity market in the U.S. has only been around for the last two decades. With renewable energy and energy storage systems becoming less expensive, a decentralized market scheme is becoming more popular and plausible. The scope of this work is to provide a fundamental understanding of unit commitment and a cost analysis of applying a battery energy storage system to an already established power system. A battery energy storage system (BESS) was placed within a unit commitment schematic and modeled for a 7 day/168 hour forecast. Three models were generated, two with and one without the battery energy storage device (BESS). The comparison between the three systems was conducted to produce a visual economic justification to the feasibility of a BESS.
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Books on the topic "Computer Storage Optimization"

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Grappone, Jennifer. Search Engine Optimization. John Wiley & Sons, Ltd., 2008.

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Grappone, Jennifer. Search engine optimization: An hour a day. Wiley Pub., 2008.

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Stützle, Thomas. Learning and Intelligent Optimization: Third International Conference, LION 3, Trento, Italy, January 14-18, 2009. Selected Papers. Springer-Verlag Berlin Heidelberg, 2009.

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T, Feagin, Overland D, University of Houston--Clear Lake. Research Institute for Computing and Information Systems., and Lyndon B. Johnson Space Center., eds. Communications and tracking expert systems study. Research Institute for Computing and Information Systems, University of Houston--Clear Lake, 1987.

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Nikil, Dutt, and Nicolau Alexandru, eds. Memory issues in embedded systems-on-chip: Optimizations and exploration. Kluwer Academic, 1999.

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Pedram, Massoud, Yanzhi Wang, Younghyun Kim, and Naehyuck Chang. Computer-Aided Design and Optimization of Hybrid Energy Storage Systems. Now Publishers, 2013.

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Search Engine Optimization. John Wiley & Sons, Ltd., 2006.

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Grappone, Jennifer, and Gradiva Couzin. Search Engine Optimization. Wiley & Sons, Incorporated, John, 2008.

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Choi, Baek-Young, Sejun Song, and Daehee Kim. Data Deduplication for Data Optimization for Storage and Network Systems. Springer London, Limited, 2016.

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Choi, Baek-Young, Sejun Song, and Daehee Kim. Data Deduplication for Data Optimization for Storage and Network Systems. Springer, 2018.

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Book chapters on the topic "Computer Storage Optimization"

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Cohen, Albert. "Parallelization via constrained storage mapping optimization." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/bfb0094913.

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Yang, Tsai-Chen, and Pao-Ann Hsiung. "Model Predictive Optimization for Energy Storage-Based Smart Grids." In Communications in Computer and Information Science. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0755-3_12.

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Yan, Junzhi, Bo Yang, Li Su, and Shen He. "Storage Optimization for Certificates in Blockchain Based PKI System." In Communications in Computer and Information Science. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6478-3_8.

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Czepirski, Leszek, and Mieczyslaw Bałys. "Optimization of Adsorptive Storage Systems for Natural Gas." In The Kluwer International Series in Engineering and Computer Science. Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-1375-5_27.

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Lv, Zaibing, Cheng Zhang, and Futian Wang. "Cost Optimization Strategy for Long-Term Storage of Scientific Workflow." In Communications in Computer and Information Science. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-0118-0_12.

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Dong, Yong. "Power Optimization of Parallel Storage System for Applications with Checkpointing." In Recent Advances in Computer Science and Information Engineering. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25789-6_35.

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Bennæs, Anders, Martin Skogset, Tormod Svorkdal, et al. "Optimization of a Ship-Based Logistics System for Carbon Capture and Storage." In Lecture Notes in Computer Science. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-16579-5_4.

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Da-zhi, Pan, Liu Zhi-bin, Chen You-jun, and Ding Xian-feng. "Realization of the Minimum Cost Spanning Tree’s Storage and Optimization in Prim Algorithm." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23214-5_56.

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Zhu, Jian-hong, Kang Li, Renji Xu, Juping Gu, Lei Zhang, and Chenxiang Sun. "Energy Storage Capacity Optimization for Deviation Compensation in Dispatching Grid-Connected Wind Power." In Communications in Computer and Information Science. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-7210-1_10.

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Ma, Zhaohui, and Yan Yang. "Optimization Strategy of OpenFlow Flow Table Storage Based on the Idea of “Betweenness Centrality”." In Communications in Computer and Information Science. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-2777-7_14.

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Conference papers on the topic "Computer Storage Optimization"

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Jianan Liang, Xinjie Zhang, and Dongsheng Yin. "Storage performance optimization of virtual machine." In 2011 International Conference on Computer Science and Service System (CSSS). IEEE, 2011. http://dx.doi.org/10.1109/csss.2011.5974569.

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He, Ping, William A. McGahan, and John A. Woollam. "Optimization of Quadralayer Structures for Various Magneto-Optical Recording Materials." In Optical Data Storage. Optica Publishing Group, 1991. http://dx.doi.org/10.1364/ods.1991.wc5.

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Computer simulation of magneto-optical responses as a function of wavelength (300 - 800 nm), thicknesses, and material were made, based on the scattering matrix formulation for the calculation of optical and magneto-optical response of multilayer systems.1 Results from the following MO materials systems are presented: bismuth substituted garnets, TbFeCo, PtMnSb, and NiMnSb. Silicon nitride and silicon carbide were the dielectrics used in the simulations, and aluminum was assumed for the reflector. The optimum structure for each of these materials systems has been found. The Kerr rotation, ellipticity, reflectance, and figures of merit for recording were calculated.
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Zhang, Xiao, and Xiao-nan Zhao. "Storage System Optimization in Data-Intensive Environment." In 2011 International Conference on Computer and Management (CAMAN). IEEE, 2011. http://dx.doi.org/10.1109/caman.2011.5778806.

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Parker, M. R., A. Sriharan, B. A. Diard, and P. G. Crump. "Computer optimization of SNR in magneto-optical double storage layers." In International Magnetics Conference. IEEE, 1989. http://dx.doi.org/10.1109/intmag.1989.690295.

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Loncar, Petra, and Sven Gotovac. "Software-Defined Storage Optimization of Distributed ALICE Resources." In 2020 International Conference on Software, Telecommunications and Computer Networks (SoftCOM). IEEE, 2020. http://dx.doi.org/10.23919/softcom50211.2020.9238270.

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Hossain, Kaium, and Shanto Roy. "A Data Compression and Storage Optimization Framework for IoT Sensor Data in Cloud Storage." In 2018 21st International Conference of Computer and Information Technology (ICCIT). IEEE, 2018. http://dx.doi.org/10.1109/iccitechn.2018.8631929.

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Wu, Wenjing, Huiyi Liu, Liting Duan, and Siying Xu. "SequenceFile Storage Optimization Method Based on Pile Structure." In 2021 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA). IEEE, 2021. http://dx.doi.org/10.1109/icaica52286.2021.9498062.

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Lafta, Zahraa Sabbar, and Muhammad Ilyas. "Privacy Preserving Homomorphic Encryption In Cloud Storage." In 2022 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA). IEEE, 2022. http://dx.doi.org/10.1109/hora55278.2022.9800069.

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Noon, Nan Noon, Janusz R. Getta, and Tianbing Xia. "Optimization Query Processing for Multi-tiered Persistent Storage." In 2021 IEEE 4th International Conference on Computer and Communication Engineering Technology (CCET). IEEE, 2021. http://dx.doi.org/10.1109/ccet52649.2021.9544285.

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Xie, Tao, and Yao Sun. "A Novel Disk Layout Optimization for Networked Storage Systems." In 2007 16th International Conference on Computer Communications and Networks. IEEE, 2007. http://dx.doi.org/10.1109/icccn.2007.4317922.

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