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Journal articles on the topic 'Data storage and retrieval'

Author: Grafiati

Published: 4 June 2021

Last updated: 17 June 2025

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1

Kalisman, Michael, and Amir Kalisman. "Data Storage and Retrieval." Clinics in Plastic Surgery 13, no. 3 (1986): 529–44. http://dx.doi.org/10.1016/s0094-1298(20)31578-9.

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Yin, Xishuang, and Yi Feng. "Data Storage Architecture and Retrieval Based on Water Conservancy Data and Computer Technologies." International Journal of Agricultural and Environmental Information Systems 16, no. 1 (2025): 1–17. https://doi.org/10.4018/ijaeis.373123.

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The reasonable storage and retrieval of spatial data in rivers and lakes can promote the development of river and lake management and protection projects. In order to efficiently store and retrieve river and lake spatial data, this study adopts river and lake data and computer technology to design a data storage architecture and retrieval method based on river and lake spatial data types. The design of the structured data storage architecture adopts relational databases and document databases with spatial indexing characteristics. Use a geospatial data abstraction library to read and write ras

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Hao, Jianying, Yuhong Ren, Yuanying Zhang, et al. "Non-interferometric phase retrieval for collinear phase-modulated holographic data storage." Optical Review 27, no. 5 (2020): 419–26. http://dx.doi.org/10.1007/s10043-020-00611-x.

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Abstract Because of its simple optical system setup and robust noise tolerance, non-interferometric phase retrieval is an important technique for phase-modulated holographic data storage. Usually, the iterative algorithm of non-interferometry needs hundreds of iteration numbers to retrieve phase accurately, the data transfer rate decreases severely. Strong constraints such as adding embedded data into the phase data page can reduce the iteration numbers, but this method decreases the code rate severely. In this paper, we proposed the advanced non-interferometric phase retrieval method based on

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Dhulavvagol, Praveen M., Akhilesh Gadagkar, K. J. Ateeth, Gururaj Hegade, Ritik Poonia, and S. G. Totad. "Optimised Image Storage and Retrieval on Hadoop." ITM Web of Conferences 53 (2023): 03001. http://dx.doi.org/10.1051/itmconf/20235303001.

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With the exponential growth of data, it is difficult to efficiently store and retrieve data using traditional methods. There is a need to optimize the storage and to efficiently retrieve relevant data matching the user query. Traditional methods lack optimized storage and to effectively retrieve data. To overcome these limitations, in this project, we propose a distributed architecture framework to optimize memory usage and to effectively retrieve relevant data using Content-Based Image Retrieval (CBIR). The experimental results show that the proposed model enhances storage performance and ret

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Arunarani, Ar, and D. Manjula Perkinian. "Intelligent Techniques for Providing Effective Security to Cloud Databases." International Journal of Intelligent Information Technologies 14, no. 1 (2018): 1–16. http://dx.doi.org/10.4018/ijiit.2018010101.

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Cloud databases have been used in a spate of web-based applications in recent years owing to their capacity to store big data efficiently. In such a scenario, access control techniques implemented in relational databases are so modified as to suit cloud databases. The querying features of cloud databases are designed with facilities to retrieve encrypted data. The performance with respect to retrieval and security needs further improvements to ensure a secured retrieval process. In order to provide an efficient secured retrieval mechanism, a rule- and agent-based intelligent secured retrieval

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Jiang, Haifeng, and Chang Wan. "Realization of Dynamic Interface and High Performance Data Retrieval." Computer and Information Science 10, no. 4 (2017): 16. http://dx.doi.org/10.5539/cis.v10n4p16.

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This paper introduces a method to realize dynamic interface, and designs a database storage model based on XML field technology to realize convenient data storage, any combination condition retrieval function and how to improve the retrieval speed in this kind of storage model. Usually a business system needs to provide information entry and retrieval functions, software designers have to design the appropriate entry items, input interface and retrieval functions for each business system and spend too much time on the repetitive works. And later engineers have to maintain the changing needs of

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Perez, J. A., I. Soto, H. Kaschel, I. Jiron, P. Adasme, and J. Denardin. "Data Storage and Retrieval on Nanoparticles." IEEE Latin America Transactions 15, no. 7 (2017): 1238–43. http://dx.doi.org/10.1109/tla.2017.7959341.

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Ali, M., N. Q. Soomro, H. Ali, A. Awan, and M. Kirmani. "Distributed File Sharing and Retrieval Model for Cloud Virtual Environment." Engineering, Technology & Applied Science Research 9, no. 2 (2019): 4062–65. https://doi.org/10.5281/zenodo.2648029.

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Cloud-based storage services are multiplying and are being adapted mostly for data storage. At the same time, many potential problems pertaining to data storage and security are being addressed. This research provides the architecture for splitting user data and the solution in retrieving different data chunks, stored on different cloud storages. By doing this, not only the load on a single server is reduced but security and storage are efficiently used. Data would be stored and retrieved in slices, hence the chances of data forgery are diminishing. File processing will be faster as split part

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9

S., Sharmila Selvi. "STORAGE OPTIMIZATION OF REPOSITORIES USING DATA MINING AND BIG DATA." GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES 6, no. 5 (2019): 516–18. https://doi.org/10.5281/zenodo.3234982.

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Software Configuration Management (SCM) deals with various changes and evolution in the software. Each software comprises of thousands of versions. Individual versions need to be stored again and again. Every software keeps on evolving so we need to keep track on each evolution. Software engineer uses mining techniques to store and retrieve these kinds of data’s. This research paper deals with the design, and implementation of an efficient storage management for SCM repositories that facilitates a developer’s to store revisions of software changes using Map reduce Techniques. The m

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Vegesna, Rohith Varma. "Designing an Archival System for Long-Term Fuel System Data Analysis." International Scientific Journal of Engineering and Management 03, no. 09 (2024): 1–3. https://doi.org/10.55041/isjem02155.

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The increasing volume of fuel transaction data necessitates efficient long-term archival solutions to enable historical analysis, regulatory compliance, and anomaly detection. Traditional storage methods may become inefficient due to high storage costs and data retrieval latencies, especially as fuel stations generate continuous data streams. This paper proposes an archival system designed to store and retrieve long-term fuel transaction data efficiently, ensuring optimized performance without unnecessary overhead. Leveraging tiered storage models, metadata indexing, and cloud- based solutions

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11

Dipti, Rao* Muzammil Hasan. "SECURE MULTIMEDIA DATA STORAGE IN CLOUD COMPUTING." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 6, no. 4 (2017): 391–95. https://doi.org/10.5281/zenodo.581553.

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Data is the most significant entity to every being. It is the sole ingredient of human and non – human communication in all forms, be it electronic, digital, verbal or written. And because of its importance, we adopt stringent measures to secure the storage of data and ensure its authorized access at different levels so that its usability and integrity are maintained. Security of any data deals both with its storage and retrieval. We may apply robust cryptographic algorithms in order to encode the data and/or implement several authentication checks to verify the genuineness of user attempting

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Riad, Khaled, and Lishan Ke. "Secure Storage and Retrieval of IoT Data Based on Private Information Retrieval." Wireless Communications and Mobile Computing 2018 (November 18, 2018): 1–8. http://dx.doi.org/10.1155/2018/5452463.

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The fast growth of Internet-of-Things (IoT) strategies has actually presented the generation of huge quantities of information. There should exist a method to conveniently gather, save, refine, and also provide such information. On the other hand, IoT data is sensitive and private information; it must not be available to potential attackers. We propose a robust scheme to guarantee both secure IoT data storage and retrieval from the untrusted cloud servers. The proposed scheme is based on Private Information Retrieval (PIR). It stores the data onto different servers and retrieves the requested

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13

Han, Yunghsiang S., Soji Omiwade, and Rong Zheng. "Progressive Data Retrieval for Distributed Networked Storage." IEEE Transactions on Parallel and Distributed Systems 23, no. 12 (2012): 2303–14. http://dx.doi.org/10.1109/tpds.2012.67.

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14

Hwang, Euiseok, Pilsang Yoon, Haksun Kim, Jooyoun Park, Jongyong Park, and Yeon June Kang. "Channel Data Retrieval in Page-Based Holographic Data Storage." Japanese Journal of Applied Physics 45, no. 2B (2006): 1285–87. http://dx.doi.org/10.1143/jjap.45.1285.

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15

Layne, Richard, and Martin Wheatley. "New data storage and retrieval systems for JET data." Fusion Engineering and Design 60, no. 3 (2002): 333–39. http://dx.doi.org/10.1016/s0920-3796(02)00029-7.

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16

Chen, Hong Ling, and Xing Po Ma. "Adaptive Information Brokerage in Wireless Sensor Networks with Virtual Rings." Applied Mechanics and Materials 687-691 (November 2014): 3044–47. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.3044.

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We study the problem of information brokerage in wireless sensor networks, where each sensor node can be an information producer or an information consumer, or both an information consumer and information producer. Some sensor nodes in the sensor networks can be selected out as the storage nodes, where the producers can store their data and the consumers can retrieve the data they are interested in. Which node/nodes should be chosen as the storage node/nodes is a challenging problem, because many factors such as the data generating rates of the producers and the query frequencies of the consum

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17

Chen, Ruixian, Jinyu Wang, Shaodong Zhang, et al. "Image segmentation of phase-modulated holographic data storage based on deep learning." Optics Express 32, no. 20 (2024): 35002. http://dx.doi.org/10.1364/oe.536783.

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Phase retrieval based on data-driven deep learning (DL) is a suitable decoding method for phase-modulated holographic data storage (HDS). Once the DL network is trained, the phase can be directly retrieved from the corresponding diffraction intensity image with high data transfer rate and low bit error rate. Traditional data-driven DL-based phase retrieval requires a large number of known samples for training, which is usually laborious for practical applications such as HDS. In the paper, we propose an image segmentation method based on image features, leading to about 54 times reduction in t

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18

Farida Ali Guechi and Ramdane Maamri. "Implementation of Secure Data Storage and Retrieval Approach." International Journal of Organizational and Collective Intelligence 12, no. 4 (2022): 1–21. http://dx.doi.org/10.4018/ijoci.312224.

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Implementation of a data storage and retrieval approach to achieve the best results is a challenge. The approach is proposed where access control is assured and a minimum of data information is revealed. On the other side special features of every cloud in a multi-cloud storage system make implementation more complicated. In this paper, the authors will present important problems, solutions, algorithms, comparison results, and details of the implementation of secure data storage and retrieval approach in a multi-cloudIoT system.

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19

Ali, M., N. Q. Soomro, H. Ali, A. Awan, and M. Kirmani. "Distributed File Sharing and Retrieval Model for Cloud Virtual Environment." Engineering, Technology & Applied Science Research 9, no. 2 (2019): 4062–65. http://dx.doi.org/10.48084/etasr.2662.

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Cloud-based storage services are multiplying and are being adapted mostly for data storage. At the same time, many potential problems pertaining to data storage and security are being addressed. This research provides the architecture for splitting user data and the solution in retrieving different data chunks, stored on different cloud storages. By doing this, not only the load on a single server is reduced but security and storage are efficiently used. Data would be stored and retrieved in slices, hence the chances of data forgery are diminishing. File processing will be faster as split part

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20

Yu, Caoyi, Niansong Mei, Chong Du, and Haotian Luo. "Blockchain Data Scalability and Retrieval Scheme Based on On-Chain Storage Medium for Internet of Things Data." Electronics 12, no. 6 (2023): 1454. http://dx.doi.org/10.3390/electronics12061454.

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The combination of blockchain and internet of things (IoT) technology realizes reliable storage of IoT data. However, the data stored on the blockchain (on-chain) face the problem of poor scalability and inefficient retrieval. In this paper, the on-chain data scalability schemes based on transactions and smart contracts are first proposed. Subsequently, on the basis of the above on-chain data scalability scheme based on transactions, an on-chain data index based on skip lists is proposed to improve the retrieval efficiency. The experimental results show that both the on-chain data scalability

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21

Abburu, Sunitha, and Nitant Dube. "Satellite Parametric Description to Ontology Concepts and Semantic Classification of Satellite Data." International Journal on Semantic Web and Information Systems 12, no. 2 (2016): 53–75. http://dx.doi.org/10.4018/ijswis.2016040103.

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Current satellite data retrieval systems retrieves data using latitude, longitude, date, time and sensor parameters like wind, cloud etc. To achieve concept based satellite data retrieval like Storm, Hurricane, Overcast and Frost etc., requires ontological concept descriptions using satellite observation parameters and concept based classification of satellite data. The current research work has designed and implemented a two phase methodology to achieve this. The phase 1 defines ontology concepts through satellite observation parameters and phase 2 describes ontology concept based satellite d

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22

Qin, Xuebin, Jingtao Huo, Jing Zhang, Lang Liu, Pai Wang, and Lihong Dong. "Research on Monitoring and Early Warning of the Mine Backfill System Based on Blockchain Technology." Applied Sciences 13, no. 1 (2022): 196. http://dx.doi.org/10.3390/app13010196.

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At present, the mine filling system is a mostly automated operation process, and it has many problems, such as centralized data storage and low safety performance. Aiming at solving the above problems, this paper proposes a mine filling overlimit warning system based on blockchain to achieve the functions of an equipment operation overlimit warning, data storage, and data retrieval. Firstly, the original data model is trained based on transfer learning to obtain the overlimit early warning model and predict the overlimit of equipment operation. Then, the interplanetary file system (IPFS) stora

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23

Yu, Xiaomin, Huiqiang Wang, Hongwu Lv, and Junqiang Fu. "An Optimization Technique of the 3D Indoor Map Data Based on an Improved Octree Structure." Mathematical Problems in Engineering 2020 (July 10, 2020): 1–13. http://dx.doi.org/10.1155/2020/4315850.

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The construction and retrieval of indoor maps are important for indoor positioning and navigation. It is necessary to ensure a good user experience while meeting real-time requirements. Unlike outdoor maps, indoor space is limited, and the relationship between indoor objects is complex which would result in an uneven indoor data distribution and close relationship between the data. A data storage model based on the octree scene segmentation structure was proposed in this paper initially. The traditional octree structure data storage model has been improved so that the data could be backtracked

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24

Ma, Hongchao, Yi Man, Xiao Xing, Zihan Zhuo, and Mo Chen. "IOTA-Based Data Encryption Storage and Retrieval Method." Journal of Quantum Computing 3, no. 3 (2021): 97–105. http://dx.doi.org/10.32604/jqc.2021.016775.

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25

Yang, Runmin, Jingjing Ma, Shu Zhang, Yu Zheng, Lusheng Wang, and Daming Zhu. "mzMD: visualization-oriented MS data storage and retrieval." Bioinformatics 38, no. 8 (2022): 2333–40. http://dx.doi.org/10.1093/bioinformatics/btac098.

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Abstract Motivation Drawing peaks in a data window of an MS dataset happens at all time in MS data visualization applications. This asks to retrieve from an MS dataset some selected peaks in a data window whose image in a display window reflects the visual feature of all peaks in the data window. If an algorithm for this purpose is asked to output high-quality solutions in real time, then the most fundamental dependence of it is on the storage format of the MS dataset. Results We present mzMD, a new storage format of MS datasets and an algorithm to query this format of a storage system for a s

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26

Varnovskiy, N. P., S. A. Martishin, M. V. Khrapchenko та A. V. Shokurov. "Cloud Data Storage and Private Information Retrieval Аlgorithms". Programming and Computer Software 50, № 6 (2024): 425–34. http://dx.doi.org/10.1134/s0361768824700294.

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27

Gemmell, Jim, and Stavros Christodoulakis. "Principles of delay-sensitive multimedia data storage retrieval." ACM Transactions on Information Systems 10, no. 1 (1992): 51–90. http://dx.doi.org/10.1145/128756.128758.

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28

Heanue, J. F., M. C. Bashaw, and L. Hesselink. "Volume Holographic Storage and Retrieval of Digital Data." Science 265, no. 5173 (1994): 749–52. http://dx.doi.org/10.1126/science.265.5173.749.

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29

STINSON, STEPHEN C. "Erasable Optical Media Eyed For Data Storage, Retrieval." Chemical & Engineering News 66, no. 42 (1988): 30–37. http://dx.doi.org/10.1021/cen-v066n042.p030.

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30

., Shashi Kant Gupta. "SECURE DATA STORAGE AND RETRIEVAL IN THE CLOUD." International Journal of Research in Engineering and Technology 03, no. 22 (2014): 35–43. http://dx.doi.org/10.15623/ijret.2014.0322008.

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31

Kunii, T. L., Y. Shinagawa, R. M. Paul, M. F. Khan, and A. A. Khokhar. "Issues in storage and retrieval of multimedia data." Multimedia Systems 3, no. 5-6 (1995): 298–304. http://dx.doi.org/10.1007/bf01832145.

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32

Spiegler, Israel, and Rafi Maayan. "Storage and retrieval considerations of binary data bases." Information Processing & Management 21, no. 3 (1985): 233–54. http://dx.doi.org/10.1016/0306-4573(85)90108-6.

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33

Wei, Boan, Jianqin Zhang, Chaonan Hu, and Zheng Wen. "A Clustering Visualization Method for Density Partitioning of Trajectory Big Data Based on Multi-Level Time Encoding." Applied Sciences 13, no. 19 (2023): 10714. http://dx.doi.org/10.3390/app131910714.

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The proliferation of the Internet and the widespread adoption of mobile devices have given rise to an immense volume of real-time trajectory big data. However, a single computer and conventional databases with limited scalability struggle to manage this data effectively. During the process of visual rendering, issues such as page stuttering and subpar visual outcomes often arise. This paper, founded on a distributed architecture, introduces a multi-level time encoding method using “minutes”, “hours”, and “days” as fundamental units, achieving a storage model for trajectory data at multi-scale

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Rani, Shama, and Jaiteg Singh. "Getting Bulk Data Through Google: An empirical study." Journal of Technology Management for Growing Economies 7, no. 2 (2016): 39–48. https://doi.org/10.15415/jtmge.2016.72006.

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To store the information in a database is one of the major tasks. The efficient storage of data is important for future use. Information retrieval is a method of gathering information related to input queries from the various sources or stored databases. To retrieve the information, a search engine plays an important role. A web search engine creates an index to match queries. The quality of information is improved with the help of search engine. For retrieving the information, a search engine comprises some modules such as query processor, a searching and matching function, document processor

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35

D, Pratiba, Shobha G, and Vijaya Lakshmi P.S. "Efficient Data Retrieval From Cloud Storage Using Data Mining Technique." International Journal on Cybernetics & Informatics 4, no. 2 (2015): 271–79. http://dx.doi.org/10.5121/ijci.2015.4226.

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Chakrawati, Jain, and Avinash Sharma Prof. "Retrieval Process in Cloud Computing An Assessment." International Journal of Trend in Scientific Research and Development 2, no. 4 (2018): 1706–9. https://doi.org/10.31142/ijtsrd14474.

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This paper presents the survey on data storage and retrieval in cloud computing. In this paper the study on scope and security issues related to data storage and information retrieval in cloud computing is done. Data storage and retrieval with data security is typical issue in today's scenario. The main objective of cloud computing is to enables users with limited computational resources to outsource their large computation workloads to the cloud. The integrity and confidentiality of the data uploaded by the user is ensured doubly by not only encrypting it but also providing access to the

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Wang, Yajun, Shengming Cheng, Xinchen Zhang, Junyu Leng, and Jun Liu. "Block Storage Optimization and Parallel Data Processing and Analysis of Product Big Data Based on the Hadoop Platform." Mathematical Problems in Engineering 2021 (December 31, 2021): 1–14. http://dx.doi.org/10.1155/2021/3839800.

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The traditional distributed database storage architecture has the problems of low efficiency and storage capacity in managing data resources of seafood products. We reviewed various storage and retrieval technologies for the big data resources. A block storage layout optimization method based on the Hadoop platform and a parallel data processing and analysis method based on the MapReduce model are proposed. A multireplica consistent hashing algorithm based on data correlation and spatial and temporal properties is used in the parallel data processing and analysis method. The data distribution

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38

Xu, Yong Kang, You Qiao Zhao, and Song Feng Lu. "Research and Implementation on Compression, Encryption, Storage and Retrieval System for Massive Data." Applied Mechanics and Materials 519-520 (February 2014): 41–48. http://dx.doi.org/10.4028/www.scientific.net/amm.519-520.41.

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A compression, encryption, storage and retrieval system for massive data is proposed and designed which can be used in these enterprises and institutions in which the business data, which need be protected, increases rapidly. In the system, XML file format is adapted as the intermediate switching format so that the detail of the multiple types of files can be omitted. A special index supporting compression and encryption is presented in the paper. In the process, the documents are stored in the server after compressed and encrypted; an end-user can retrieve the need documents efficiently by he

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Feng, Hangwei, Jinlin Wang, and Yang Li. "An Efficient Blockchain Transaction Retrieval System." Future Internet 14, no. 9 (2022): 267. http://dx.doi.org/10.3390/fi14090267.

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In the era of the digital economy, blockchain has developed well in various fields, such as finance and digital copyright, due to its unique decentralization and traceability characteristics. However, blockchain gradually exposes the storage problem, and the current blockchain stores the block data in third-party storage systems to reduce the node storage pressure. The new blockchain storage method brings the blockchain transaction retrieval problem. The problem is that when unable to locate the block containing this transaction, the user must fetch the entire blockchain ledger data from the t

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Garima, Anand. "DATA SECURITY TECHNIQUE IN CLOUD COMPUTING." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 7, no. 8 (2018): 538–44. https://doi.org/10.5281/zenodo.1402460.

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Cloud computing is the delivery of computing services over the Internet. The platform of cloud computing gives peoples the opportunity of sharing and storing resources and information among the people across the globe. Most of organizations, individual and end users are making use of such online storage services to store their important information for the backup purpose. This new paradigm brings about many new security challenges. At present ensuring security in cloud computing platform has become one of the most significant concerns for the researchers. Many any new frameworks and technologi

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Yao, Zhixin, Jianqin Zhang, Taizeng Li, and Ying Ding. "A Trajectory Big Data Storage Model Incorporating Partitioning and Spatio-Temporal Multidimensional Hierarchical Organization." ISPRS International Journal of Geo-Information 11, no. 12 (2022): 621. http://dx.doi.org/10.3390/ijgi11120621.

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Trajectory big data is suitable for distributed storage retrieval due to its fast update speed and huge data volume, but currently there are problems such as hot data writing, storage skew, high I/O overhead and slow retrieval speed. In order to solve the above problems, this paper proposes a trajectory big data model that incorporates data partitioning and spatio-temporal multi-perspective hierarchical organization. At the spatial level, the model partitions the trajectory data based on the Hilbert curve and combines the pre-partitioning mechanism to solve the problems of hot writing and stor

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Ruwei, Huang, Gui Xiaolin, Yu Si, and Zhuang Wei. "Study of privacy-preserving framework for cloud storage." Computer Science and Information Systems 8, no. 3 (2011): 801–19. http://dx.doi.org/10.2298/csis100327029r.

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In order to implement privacy-preserving, efficient and secure data storage and access environment of cloud storage, the following problems must be considered: data index structure, generation and management of keys, data retrieval, treatments of change of users? access right and dynamic operations on data, and interactions among participants. To solve those problems, the interactive protocol among participants is introduced, an extirpation-based key derivation algorithm (EKDA) is designed to manage the keys, a double hashed and weighted Bloom Filter (DWBF) is proposed to retrieve the encrypte

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43

Levine, Harold G. "Principles of Data Storage and Retrieval for Use in Qualitative Evaluations." Educational Evaluation and Policy Analysis 7, no. 2 (1985): 169–86. http://dx.doi.org/10.3102/01623737007002169.

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In spite of increased interest in recent years in the mechanics of qualitative evaluation, few evaluators or other qualitative researchers have addressed the related issues of qualitative data storage-retrieval and data reduction-analysis. Generalized procedures for these tasks, which are generally known within the field of anthropology, have never been systematically examined or codified. This paper borrows from developments in information and library science to construct general principles of data storage and retrieval for the field-based investigator. The five principles that are examined a

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Cui, Min, and Yipeng Wang. "EC-Kad: An Efficient Data Redundancy Scheme for Cloud Storage." Electronics 14, no. 9 (2025): 1700. https://doi.org/10.3390/electronics14091700.

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To address the issues of fault tolerance and retrieval efficiency in cloud storage space data, we propose an efficient cloud storage solution based on erasure codes. A cloud storage system model is designed to use erasure codes to distribute the encoded original data files across various nodes of the cloud storage system in a decentralized manner. The files are decoded by the receiver to complete data recovery and ensure high availability of the data files while optimizing redundant computing overhead during data storage, thereby improving the stability of encoding and decoding and reducing th

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Sangat, Prajwol, Maria Indrawan-Santiago, and David Taniar. "Sensor data management in the cloud: Data storage, data ingestion, and data retrieval." Concurrency and Computation: Practice and Experience 30, no. 1 (2017): e4354. http://dx.doi.org/10.1002/cpe.4354.

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46

Saikeerthana, R., and A. Umamakeswari. "Secure Data Storage and Data Retrieval in Cloud Storage using Cipher Policy Attribute based Encryption." Indian Journal of Science and Technology 8, S9 (2015): 318. http://dx.doi.org/10.17485/ijst/2015/v8is9/65600.

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47

Deepika, M., and I. Antonitte Vinoline. "An Integrated Warehouse System using AS/RS (Automated Storage and Retrieval System) Technology." Indian Journal Of Science And Technology 18, no. 13 (2025): 1038–45. https://doi.org/10.17485/ijst/v18i13.178.

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Objectives: To examine and justify the significance of Automated Storage and Retrieval System technology in minimizing warehouse inventory costs and enhancing storage efficiency for improved retailer operations. Methods: Automated Storage and Retrieval Systems is examined in the warehouse and analysed between the two methods namely i) with Automated Storage and Retrieval System technology ii) without Automated Storage and Retrieval System technology. The proposed methods were implemented and analyzed to evaluate their effectiveness in reducing warehouse inventory costs and optimizing storage s

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Sharma, Seemu, and Seema Bawa. "CBDR: An efficient storage repository for cultural big data." Digital Scholarship in the Humanities 35, no. 4 (2019): 893–903. http://dx.doi.org/10.1093/llc/fqz083.

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Abstract Cultural data and information on the web are continuously increasing, evolving, and reshaping in the form of big data due to globalization, digitization, and its vast exploration, with common people realizing the importance of ancient values. Therefore, before it becomes unwieldy and too complex to manage, its integration in the form of big data repositories is essential. This article analyzes the complexity of the growing cultural data and presents a Cultural Big Data Repository as an efficient way to store and retrieve cultural big data. The repository is highly scalable and provide

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Alyousif, Aya, and Ali Yassin. "Improving Performance of Searchable Symmetric Encryption Through New Information Retrieval Scheme." Iraqi Journal for Electrical and Electronic Engineering 20, no. 1 (2023): 68–77. http://dx.doi.org/10.37917/ijeee.20.1.7.

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Searchable symmetric encryption (SSE) is a robust cryptographic method that allows users to store and retrieve encrypted data on a remote server, such as a cloud server, while maintaining the privacy of the user's data. The technique employs symmetric encryption, which utilizes a single secret key for both data encryption and decryption. However, extensive research in this field has revealed that SSE encounters performance issues when dealing with large databases. Upon further investigation, it has become apparent that the issue is due to poor locality, necessitating that the cloud server acce

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Chen, Ruixian, Jianying Hao, Changyu Yu, et al. "Dynamic sampling iterative phase retrieval for holographic data storage." Optics Express 29, no. 5 (2021): 6726. http://dx.doi.org/10.1364/oe.419630.

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