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1

Sergeant, Anne M. A., and Carl S. Sergeant. "Hidden costs of data storage." Journal of Corporate Accounting & Finance 21, no. 5 (2010): 41–47. http://dx.doi.org/10.1002/jcaf.20610.

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Lysetskyi, Yu M., and S. V. Kozachenko. "Software-defined data storage systems." Mathematical machines and systems 1 (2021): 17–23. http://dx.doi.org/10.34121/1028-9763-2021-1-17-23.

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Every year the amount of generated data grows exponentially which entails an increase in both the number and capacity of data storage systems. The highest capacity is required for data storage systems that are used to store backups and archives, file storages with shared access, testing and development environments, virtual machine storages, corporate or public web services. To solve such tasks, nowadays manufacturers offer three types of storage systems: block and file storages which have already become a standard used for implementing IT infrastructures, and software-defined storage systems.
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Zhang, Ling, and Shuai Shuai Zhu. "Data Dispersal for Large Storage Systems." Applied Mechanics and Materials 644-650 (September 2014): 2334–37. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.2334.

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Data dispersal mechanism is a group of basic working protocols for oceans of data processing and it plays an important role in enhancing system error correction and avoiding storage device failure. The data recovery availability of the client is the main design goal of data dispersal algorithms. The system storage and computing costs are also important factors for a data dispersal algorithm. In this paper, we discussed how to disperse data with the special properties as well as with acceptable system costs. We developed a universal approach to measure storage node availability based on state v
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Krumm, Niklas, and Noah Hoffman. "Practical Cost Analysis of Genomic Data in the Cloud." American Journal of Clinical Pathology 152, Supplement_1 (2019): S2—S3. http://dx.doi.org/10.1093/ajcp/aqz112.004.

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Abstract Background The growth of clinical NGS testing, together with new CAP checklist items stating that read-level (raw) NGS data must be retained for a minimum of 2 years, has prompted laboratories to reevaluate their NGS data storage solutions. In this context, cloud-based storage has several advantages, such as low per-GB prices, scalability, and minimal fixed costs; nonetheless, several perceived disadvantages, including increased complexity and security/regulatory considerations, have hindered adoption. Furthermore, despite the ostensibly simple usage-based pricing plans, practical cos
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Mrs., T. Arunambika*1 &. Dr. P. Senthil Vadivu2. "A SURVEY ON DATA PLACEMENT STRATEGY AND ALGORITHMS USING IN CLOUD DATA STORAGE." GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES 6, no. 5 (2019): 406–11. https://doi.org/10.5281/zenodo.3175134.

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<strong>C</strong>loud computing platform can provide infinite storage capacity, computing ability as well as information services; it now has become the popular new application platform for both individuals and enterprises. The storage capacity of a data center is limited. Therefore, how to place data slices in appropriate data center proves to be an important factor influencing the platform ability. The data placement strategy we design in this paper takes the cooperation costs among data slices into account. It lowers the distributed transaction costs as much as possible, especially the cos
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Immidisetti, Venkata Raman. "Data Tiering on Cloud Volumes ONTAP to Optimize Costs in Azure." International Journal of Multidisciplinary Research and Growth Evaluation. 1, no. 4 (2020): 55–58. https://doi.org/10.54660/.ijmrge.2020.1.4.55-58.

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Cloud Volumes ONTAP (CVO) is an enterprise-grade, software-defined storage solution developed by NetApp that extends the robust data management capabilities of the ONTAP operating system to cloud environments such as Microsoft Azure. One of the primary challenges encountered by organizations utilizing cloud storage is cost optimization, given the substantial price variations across different storage tiers based on performance and access frequency. Data tiering within Cloud Volumes ONTAP functions as a strategic mechanism to address this issue by dynamically migrating data between high-performa
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Narmadha, T., J. Gowrishankar, M. Ramkumar, and K. Vengatesan. "Cloud Data Center Based Dynamic Optimizing Replica Migration." Journal of Computational and Theoretical Nanoscience 16, no. 2 (2019): 576–79. http://dx.doi.org/10.1166/jctn.2019.7772.

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Cloud Storage Providers (CSPs) over topographically scattered data stores furnishing a few storage classes with various costs. An imperative issue looked by application providers is the means by which to misuse value contrasts crosswise over data stores to limit the financial cost of utilizations that incorporate problem area objects that are acquired much of the time and spot objects that are regularly becoming to far less. This financial cost comprises of reproduction, creation, storage, Put, Get, and potential migration costs. To advance such costs, we initially propose the ideal arrangemen
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Ramakrishnan, Mr R. "Reducing Latency and Storage Costs in Cloud Applications Through Advanced Data Management." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem49547.

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ABSTRACT-Junk files, including outdated backups, redundant document versions, and orphaned objects, accumulate in cloud storage, leading to inefficiencies in data retrieval, increased latency, and higher storage costs. As cloud applications grow in scale, managing and optimizing storage resources becomes crucial for maintaining performance and reducing operational overhead. The problem of unnecessary files taking up valuable space is especially critical in cloud environments where efficient resource management is essential for smooth operations. This project proposes a solution to optimize clo
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Womac, Alvin R., Mitch D. Groothuis, Kelly Tiller, Sam W. Jackson, and Clay Dye. "Low-Moisture Switchgrass Bulk-Format Logistics Costs Based on Engineering Data." Transactions of the ASABE 61, no. 2 (2018): 341–54. http://dx.doi.org/10.13031/trans.12631.

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Abstract. Logistics costs that spanned harvest, transport, storage, preprocessing, and year-round delivery of 371,870 dMg year-1 of milled, low-moisture switchgrass (SG) to a local biorefinery were determined for bulk-format versus round-bale systems. Separate spreadsheet analyses were conducted for three diesel fuel prices ($0.53 L-1, $0.92 L-1, and $1.32 L-1) because of the wide range of fuel prices during the project. A detailed analysis scenario identified a common harvest period, equipment annual use, other equipment uses, and protected SG storage on gravel pad, along with equipment perfo
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Krumm, Niklas, and Noah Hoffman. "Practical estimation of cloud storage costs for clinical genomic data." Practical Laboratory Medicine 21 (August 2020): e00168. http://dx.doi.org/10.1016/j.plabm.2020.e00168.

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Rathod, Subhash Gulabrao, Mangesh D. Salunke, Hemantkumar B. Jadhav, Deepika Amol Ajalkar, Dinesh Banurao Satre, and Devyani Bonde. "Role Based Secure Data Access Control for Cost Optimized Cloud Storage Using Data Fragmentation While Maintaining Data Confidentiality." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 7s (2023): 316–23. http://dx.doi.org/10.17762/ijritcc.v11i7s.7005.

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The paper proposes a role-based secure data access control framework for cost-optimized cloud storage, addressing the challenge of maintaining data security, privacy, integrity, and availability at lower cost. The proposed framework incorporates a secure authenticity scheme to protect data during storage or transfer over the cloud. The framework leverages storage cost optimization by compressing high-resolution images and fragmenting them into multiple encrypted chunks using the owner's private key. The proposed approach offers two layers of security, ensuring that only authorized users can de
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Irma Nurfitri Handayani and Ruki Harwahyu. "A Survey High Performance Storage in Data Center." Journal of Scientech Research and Development 6, no. 1 (2024): 1179–88. https://doi.org/10.56670/jsrd.v6i1.410.

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According to statistics, by 2025, It will be storing approximately 160 zettabytes of data. This increase causes data centers to be fast in innovating, to meet user needs. Currently, most data centers still use traditional storage mechanisms. The rapid growth of enterprises and customers requires access to storage that is easy to access, innovates and more dynamic in management, reduces costs in development and maintenance, and requires increased scalability. In this survey discuss past and ongoing uses of storage to increase high performance storage technology and storage system
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Han, Yan. "Cloud storage for digital preservation: optimal uses of Amazon S3 and Glacier." Library Hi Tech 33, no. 2 (2015): 261–71. http://dx.doi.org/10.1108/lht-12-2014-0118.

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Purpose – The purpose of this paper is to use cloud storage in digital preservation by analyzing the pricing and data retrieval models. The author recommends strategies to minimize the costs and believes cloud storage is worthy of serious consideration. Design/methodology/approach – Few articles have been published to show the uses of cloud storage in libraries. The cost is the main concern. An overview of cloud storage pricing shows a price drop once every one or one-and-a-half years. The author emphasize the data transfer-out costs and demonstrate a case study. Comparisons and analysis of S3
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Kambhampati, Viswambher, Andy van den Dobbelsteen, and Joep Schild. "Moving Beyond Diesel Generators: Exploring Renewable Backup Alternatives for Data Centers." Journal of Physics: Conference Series 2929, no. 1 (2024): 012008. https://doi.org/10.1088/1742-6596/2929/1/012008.

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Abstract This study investigates sustainable alternatives to diesel generators for data centre backup power, focusing on renewable diesel (HVO), Hydrogen energy storage (HES), batteries (Lithium-ion and Sodium Sulfur) and Compressed Air Energy Storage (CAES). As environmental scrutiny of data centres grows, the need for cleaner energy sources intensifies. Our research assesses various storage technologies’ energy performance metrics, environmental impacts, and economic feasibility. HVO is a seamless substitute for conventional diesel, compatible with existing infrastructure and less carbon-int
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Alekseev, A., A. Kiryanov, A. Klimentov, et al. "Data Handling Optimization in Russian Data Lake Prototype." Journal of Physics: Conference Series 2438, no. 1 (2023): 012021. http://dx.doi.org/10.1088/1742-6596/2438/1/012021.

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Abstract CERN experiments are preparing for the HL-LHC era, which will bring an unprecedented volume of scientific data. These data will need to be stored and processed by thousands of physicists, but expected resource growth is nowhere near the extrapolated requirements of existing models, in terms of both storage volume and compute power. Opportunistic CPU resources such as HPCs and university clusters can provide extra CPU cycles, but there is no opportunistic storage. In this article, we will present the main architectural ideas, deployment details, and test results, with emphasis on our r
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Sreenu, Maddipudi. "SAP HANA Database Data storage management using Native Storage Extension and Near Line Storage." International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences 11, no. 4 (2023): 1–6. https://doi.org/10.5281/zenodo.14381599.

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SAP HANA provides powerful data storage and management capabilities, addressing the challenges of high data volumes across different temperature data&mdash;hot, warm, and cold. This paper explores SAP HANA&rsquo;s Native Storage Extension (NSE) and Near-Line Storage (NLS) as effective solutions for managing multi-temperature data, enhancing performance, and optimizing storage costs. By implementing these technologies, businesses can ensure that mission-critical data is stored in high-performance memory (hot data), while less critical data is moved to lower-cost storage (warm and cold data) wit
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Dr.A.Shaji, George. "Digital Hoarding: The Rising Environmental and Personal Costs of Information Overload." Partners Universal Multidisciplinary Research Journal (PUMRJ) 01, no. 02 (2024): 51–67. https://doi.org/10.5281/zenodo.12802575.

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As "tidying up" fads tackle physical clutter, a massive crisis of digital hoarding is unfolding unchecked. This paper exposes the rising environmental, economic, personal, and data security costs of information overload via endless emails, unused apps, outdated files, and exponentially growing photo/cloud storage. The practical uses of digital storage are phenomenal, despite its ethereal and cheap appearance. There will be over 375 billion emails exchanged daily by 2025, with 35% of them going unread. Fifty percent of the apps on the typical smartphone are useless. Outdated files from years ag
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Baladari, Venkata. "Intelligent Tier-Based Data Management: A Predictive Approach to Cloud Storage Cost Optimization." International Journal of Science and Research (IJSR) 12, no. 8 (2023): 2583–86. https://doi.org/10.21275/SR23089114850.

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Cloud storage has become an essential component of modern data management, but increasing storage costs present a significant challenge for organizations. Conventional tier-based storage systems necessitate manual distribution, resulting in potential inefficiencies and increased expenses. This study presents a forecasting model for intelligent data tiering, utilizing machine learning to automate storage selections based on access frequency. Utilizing historical usage patterns, the model automatically categorizes data into three storage tiers: hot, warm, or cold, thereby balancing cost-effectiv
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Meikshan, Vladimir, and Natalia Teslya. "Selection of optimal data placement using cloud infrastructure." Proceedings of the Russian higher school Academy of sciences, no. 2 (July 21, 2021): 34–42. http://dx.doi.org/10.17212/1727-2769-2021-2-34-42.

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Benefits of using cloud technology are obvious, their application is expanding, as a result, it determines the steady growth of demand. Cloud computing has acquired particular relevance for large companies connected with Internet services, retailing, logistics that generate large volume of business and other information. The use of cloud technologies allows organizing the joint consumption of resources, solving the problems of storing and transferring significant amounts of data. Russian consumer cooperation refers to large territory distributed organizations actively forming their own digital
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Tong, Yulai, Jiazhen Liu, Hua Wang, et al. "Sieve: A Learned Data-Skipping Index for Data Analytics." Proceedings of the VLDB Endowment 16, no. 11 (2023): 3214–26. http://dx.doi.org/10.14778/3611479.3611520.

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Modern data analytics services are coupled with external data storage services, making I/O from remote cloud storage one of the dominant costs for query processing. Techniques such as columnar block-based data organization and compression have become standard practices for these services to save storage and processing cost. However, the problem of effectively skipping irrelevant blocks at low overhead is still open. Existing data-skipping efforts maintain lightweight summaries (e.g., min/max, histograms) for each block to filter irrelevant data. However, such techniques ignore patterns in real
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Klenk, Juergen, Dina Mikdadi, Bhavani Singh, et al. "Abstract 1085: Analyzing economic storage solutions for cancer research data." Cancer Research 85, no. 8_Supplement_1 (2025): 1085. https://doi.org/10.1158/1538-7445.am2025-1085.

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Abstract Purpose: The National Cancer Institute’s (NCI) Cancer Research Data Commons (CRDC) is a cloud-based data ecosystem that allows researchers to share and access clinical, genomic, proteomic, and imaging data. CRDC currently houses more than 10 petabytes (PB) of data (predominantly genomic). The volume of genomic data in CRDC has more than doubled since 2022 from 3.7 PB to 8.8 PB. To address the escalating data storage costs, CRDC must identify economic genomic data storage/compression strategies to achieve long-term sustainability. Methods: To evaluate the impact of genomic compression
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Sambu, Patach Arrojula. "Efficient Event Grouping Algorithm for Mobile Analytics: Reducing Data Footprint." European Journal of Advances in Engineering and Technology 10, no. 1 (2023): 124–29. https://doi.org/10.5281/zenodo.13919609.

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The rapid growth in mobile applications has led to an exponential increase in the number of events generated and transmitted for analytics purposes. This surge in data volume significantly impacts data costs and performance for clients, while also demanding more resources for backend processing. In this paper, we propose an innovative approach to mitigate these challenges by reducing the footprint of events through efficient grouping and redundancy elimination. Our method involves aggregating related events into predefined buckets and optimizing storage by removing redundant data, retaining on
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Bommannan, Sri, Prabakaran P, Gokulraj S, and Ilavarasi S. "Duplicate Detection on Cloud Data with Re-Encryption Based Data Sharing." International Research Journal of Computer Science 11, no. 04 (2024): 257–65. http://dx.doi.org/10.26562/irjcs.2024.v1104.20.

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Cloud data storage has gained immense popularity in recent years due to its scalability and accessibility. However, the efficient management of data in the cloud, especially with the ever-increasing volume of data, remains a significant challenge. Data deduplication is a crucial technique to reduce storage costs and enhance data management efficiency. It also concerns the secure cloud data storage and sharing. Here implement a novel approach to de duplication-based cloud data storage using chunk-based partitioning. In this approach, data is divided into fixed-size chunks, and a deduplication m
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Researcher. "DATA MIGRATION TO CLOUD - STRATEGIES, CHALLENGES, AND BEST PRACTICES." DATA MIGRATION TO CLOUD - STRATEGIES, CHALLENGES, AND BEST PRACTICES 15, no. 5 (2024): 1084–92. https://doi.org/10.5281/zenodo.14027912.

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This paper presents a comprehensive overview of data migration to cloud computing environments, addressing its growing importance in the modern digital landscape. We explore the advantages and challenges of migrating applications and data to the cloud, emphasizing the crucial role of storage and processing systems in large-scale, high-performance applications. The study examines various aspects of data migration, including strategies, methodologies, categories, and associated risks. Our research highlights the potential cost implications of migration, stressing the importance of following best
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Xie, Jiong, Zhen Chen, Jianwei Liu, et al. "Ganos." Proceedings of the VLDB Endowment 15, no. 12 (2022): 3483–95. http://dx.doi.org/10.14778/3554821.3554838.

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Recently, the trend of developing digital twins for smart cities has driven a need for managing large-scale multidimensional, dynamic, and scene-oriented spatial data. Due to larger data scale and more complex data structure, queries over such data are more complicated and expensive than those on traditional spatial data, which poses challenges to the system efficiency and deployment costs. The existing spatial databases have limited support in both data types and operations. Therefore, a new-generation spatial database with excellent performance and effective deployment costs is needed. This
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Lopez-Carmona, Miguel A., Ivan Marsa-Maestre, la Hoz Enrique de, and Juan R. Velasco. "Using RFID to Enhance Security in Off-Site Data Storage." Sensors 10, no. 9 (2010): 8010–27. https://doi.org/10.5281/zenodo.160022.

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Off-site data storage is one of the most widely used strategies in enterprises of all sizes to improve business continuity. In medium-to-large size enterprises, the off-site data storage processes are usually outsourced to specialized providers. However, outsourcing the storage of critical business information assets raises serious security considerations, some of which are usually either disregarded or incorrectly addressed by service providers. This article reviews these security considerations and presents a radio frequency identification (RFID)-based, off-site, data storage management syst
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Gokulkannan, K., M. Parthiban, Jayanthi S, and Manoj Kumar T. "Cost effective cloud-based data storage scheme with enhanced privacy preserving principles." Scientific Temper 15, no. 02 (2024): 2104–15. http://dx.doi.org/10.58414/scientifictemper.2024.15.2.21.

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As the convergence of the internet of things (IoT) and cloud computing continues to reshape data management paradigms, ensuring the integrity of vast datasets becomes a critical concern. This research introduces an innovative solution for large-scale IoT-cloud systems, presenting an efficient and secure multi-owner batch integrity checking scheme. The proposed system leverages streamlined cryptographic operations to enhance efficiency and security. The study comprehensively evaluates the proposed system’s proficiency, durability, and validity, focusing on key factors such as computational cost
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Valente, Domingos S. M., Daniel M. de Queiroz, Paulo C. Corrêa, Luis C. da Silva, and Sônia M. L. R. do Vale. "A decision support system for cost determination in grain storage facility operations." Engenharia Agrícola 31, no. 4 (2011): 735–44. http://dx.doi.org/10.1590/s0100-69162011000400012.

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Many research works have being carried out on analyzing grain storage facility costs; however a few of them had taken into account the analysis of factors associated to all pre-processing and storage steps. The objective of this work was to develop a decision support system for determining the grain storage facility costs and utilization fees in grain storage facilities. The data of a CONAB storage facility located in Ponta Grossa - PR, Brazil, was used as input of the system developed to analyze its specific characteristics, such as amount of product received and stored throughout the year, h
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Taebnia, Mehdi, Marko Heikkilä, Janne Mäkinen, Jenni Kiukkonen-Kivioja, Jouko Pakanen, and Jarek Kurnitski. "A Qualitative Control Approach to Reduce Energy Costs of Hybrid Energy Systems: Utilizing Energy Price and Weather Data." Energies 13, no. 6 (2020): 1401. http://dx.doi.org/10.3390/en13061401.

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Nowadays, many buildings are equipped with various energy sources. The challenge is how to efficiently utilize their energy production. This includes decreasing the share and costs of external energy—usually electrical energy delivered from the grid. The following study presents a qualitative approach with a combined control to solve the problem. The approach is demonstrated using a simulated residential building equipped with a hybrid energy system: a thermal energy storage combined with an electrical heater, a geothermal heat pump and a solar thermal collector. Consequently, the share of ren
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Sivananda, Reddy Julakanti, Satya Kiranmayee Sattiraju Naga, and julakanti Rajeswari. "Optimizing Storage Formats for Data Warehousing Efficiency." International Journal on Recent and Innovation Trends in Computing and Communication 9, no. 5 (2021): 71–78. https://doi.org/10.5281/zenodo.14715353.

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Data warehousing has become a critical aspect of modern business intelligence and data management. As organizations accumulate vast amounts of structured and unstructured data, the efficiency of data storage formats in a data warehouse directly impacts processing speed, scalability, and cost-effectiveness. This research aims to explore and evaluate various storage formats used in data warehousing, focusing on optimization techniques that can enhance storage efficiency, reduce query time, and lower operational costs. By examining the characteristics of different storage formats, including row-b
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Eren, Haluk, Özgür Karaduman, and Muharrem Tuncay Gençoğlu. "Security Challenges and Performance Trade-Offs in On-Chain and Off-Chain Blockchain Storage: A Comprehensive Review." Applied Sciences 15, no. 6 (2025): 3225. https://doi.org/10.3390/app15063225.

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Blockchain-based data storage methods offer strong data integrity, decentralized security, and transparent access control but also face scalability challenges, high computational costs, and complex data management. This study provides a comprehensive review of on-chain, off-chain, and hybrid storage architectures, analyzing their security vulnerabilities, performance trade-offs, and industry-specific applications. On-chain data storage ensures immutability, data integrity, and high security by storing data directly on the blockchain; however, it is associated with high transaction costs and sc
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Hazela, Bramah, Shashi Kant Gupta, Nupur Soni, and Ch Naga Saranya. "Securing the Confidentiality and Integrity of Cloud Computing Data." ECS Transactions 107, no. 1 (2022): 2651–63. http://dx.doi.org/10.1149/10701.2651ecst.

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Cloud Service Providers (CSPs) are becoming increasingly popular as the amount of available digital data continues to grow at an exponential rate. A new set of benefits and economies made possible by cloud technologies in terms of bandwidth, computing, storage, and transmission costs, which will all reduce the overall costs for data storage for the company, which provide customers with convenient and efficient storage services. For the protection of the Cloud Client (CC) data in the cloud, several different security models are available. In order to verify that CSPs and the CC are in complianc
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Chen, Yanqiu. "Advancing Data Resilience: An In-Depth Study of Pyramid Codes for Fault Tolerance and Repair Cost Optimization." ITM Web of Conferences 73 (2025): 03020. https://doi.org/10.1051/itmconf/20257303020.

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In the digital era, distributed storage systems are essential for managing vast volumes of data generated by cloud computing, big data, and the Internet of Things. These systems face challenges such as scalability, fault tolerance, and cost control. Pyramid Codes have emerged as an effective solution, enhancing fault tolerance and reducing repair costs. This paper presents a thorough analysis of Pyramid Codes, examining their structure, performance, and advantages over traditional Reed-Solomon Codes. The study delves into fault tolerance mechanisms, demonstrating Pyramid Codes’ ability to hand
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Vurukonda, Naresh, B. Thirumala Rao, and B. Tirapathi Reddy. "A Secured Cloud Data Storage with Access Privileges." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 5 (2016): 2338. http://dx.doi.org/10.11591/ijece.v6i5.10820.

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&lt;p&gt;In proposed framework client source information reinforcements off-site to outsider distributed storage benefits to decrease information administration costs. In any case, client must get protection ensure for the outsourced information, which is currently safeguarded by outsiders. To accomplish such security objectives, FADE is based upon an arrangement of cryptographic key operations that are self-kept up by a majority of key supervisors that are free of outsider mists. In unmistakable, FADE goes about as an overlay framework that works flawlessly on today's distributed storage admi
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Vurukonda, Naresh, B. Thirumala Rao, and B. Tirapathi Reddy. "A Secured Cloud Data Storage with Access Privileges." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 5 (2016): 2338. http://dx.doi.org/10.11591/ijece.v6i5.pp2338-2344.

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&lt;p&gt;In proposed framework client source information reinforcements off-site to outsider distributed storage benefits to decrease information administration costs. In any case, client must get protection ensure for the outsourced information, which is currently safeguarded by outsiders. To accomplish such security objectives, FADE is based upon an arrangement of cryptographic key operations that are self-kept up by a majority of key supervisors that are free of outsider mists. In unmistakable, FADE goes about as an overlay framework that works flawlessly on today's distributed storage admi
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Smith, Anne E., David Cohan, and Frank Selker. "A MODEL FOR MANAGING UNDERGROUND STORAGE TANKS." International Oil Spill Conference Proceedings 1987, no. 1 (1987): 599–604. http://dx.doi.org/10.7901/2169-3358-1987-1-599.

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ABSTRACT The potential costs of underground tank leaks provide companies with a solid incentive to take action to reduce leak risks. However, a cost-effective risk management strategy is difficult to identify when faced with the uncertainties in the occurrence, nature, and timing of costly incidents. A decision support model based on the techniques of decision analysis has been developed to help managers choose the best course of action. The model works by balancing the known costs of preventive and mitigating actions with the uncertain costs of tank leaks. The model uses tank- and site-specif
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Yuan, Zhu, Xueqiang Lv, Yunchao Gong, Boshan Liu, Haixiang Yang, and Xindong You. "Text Semantics-Driven Data Classification Storage Optimization." Applied Sciences 14, no. 3 (2024): 1159. http://dx.doi.org/10.3390/app14031159.

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Data classification storage has emerged as an effective strategy, harnessing the diverse performance attributes of storage devices to orchestrate a harmonious equilibrium between energy consumption, cost considerations, and user accessibility. The traditional strategy of solely relying on access frequency for data classification is no longer suitable for today’s complex storage environment. Diverging from conventional methods, we explore from the perspective of text semantics to address this issue and propose an effective data classification storage method using text semantic similarity to ext
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38

S, Janakiraman. "Cloud Clean: Cloud Storage Space Sustainability using Data Life Cycle Guard Scheme." International Journal for Research in Applied Science and Engineering Technology 13, no. 6 (2025): 165–72. https://doi.org/10.22214/ijraset.2025.71988.

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Junk files, including outdated backups, redundant document versions, and orphaned objects, accumulate in cloud storage, leading to inefficiencies in data retrieval, increased latency, and higher storage costs. As cloud applications grow in scale, managing and optimizing storage resources becomes crucial for maintaining performance and reducing operational overhead. The problem of unnecessary files taking up valuable space is especially critical in cloud environments where efficient resource management is essential for smooth operations. This project proposes a solution to optimize cloud data m
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KUMAR, Mr M. A. R., and Mrs SRILATHA PULI. "FINDING DATA DEDUPLICATION USING CLOUD." YMER Digital 21, no. 05 (2022): 136–42. http://dx.doi.org/10.37896/ymer21.05/17.

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Data grows at the emotional rate of 50% per time, and 75% of the digital world is a copy1 Although keeping multiple clones of data is necessary to guarantee their availability and high continuity and the quantum of data redundancy is inordinate. By keeping a single dupe of repeated data, data deduplication is one of the most promising results to reduce the storage costs, and improve users experience by saving network bandwidth and reducing provisory time. However, this result must now solve many security issues to be fully satisfying. In this project we target the attacks from malicious client
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Lopes, Cristina, and Ana Oliveira. "Minimization of Costs with Picking and Storage Operations." Systems 12, no. 5 (2024): 158. http://dx.doi.org/10.3390/systems12050158.

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This work presents two mixed-integer programming models that intend to minimize the costs of the picking and storage operation through better planning and organization of the places occupied by the products in the warehouse. A large customer that stores frozen goods in a Portuguese cold chain logistics company was selected for the analysis of the allocation of the products in the warehouse and of the corresponding outbound movements. Data with 8525 movements that occurred during 2021 were collected for 228 different product references. For this case study, the products that had a picking place
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Cao, Xinyue, Zhangjie Fu, and Xingming Sun. "A Privacy-Preserving Outsourcing Data Storage Scheme with Fragile Digital Watermarking-Based Data Auditing." Journal of Electrical and Computer Engineering 2016 (2016): 1–7. http://dx.doi.org/10.1155/2016/3219042.

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Cloud storage has been recognized as the popular solution to solve the problems of the rising storage costs of IT enterprises for users. However, outsourcing data to the cloud service providers (CSPs) may leak some sensitive privacy information, as the data is out of user’s control. So how to ensure the integrity and privacy of outsourced data has become a big challenge. Encryption and data auditing provide a solution toward the challenge. In this paper, we propose a privacy-preserving and auditing-supporting outsourcing data storage scheme by using encryption and digital watermarking. Logisti
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42

Wright, Richard, Ant Miller, and Matthew Addis. "The Significance of Storage in the “Cost of Risk” of Digital Preservation." International Journal of Digital Curation 4, no. 3 (2009): 104–22. http://dx.doi.org/10.2218/ijdc.v4i3.125.

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As storage costs drop, storage is becoming the lowest cost in a digital repository – and the biggest risk. We examine current modelling of costs and risks in digital preservation, concentrating on the Total Cost of Risk when using digital storage systems for preserving audiovisual material. We review the vital role of storage and show how planning for long-term preservation of data should consider the risks involved in using digital storage technology. Gaps in information necessary for accurate modelling – and planning – are presented. We call for new functionality to support recovery of files
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43

Ali, Zainab. "FeRAM: A Paradigm of Advanced Data Storage Technology." International Journal for Research in Applied Science and Engineering Technology 11, no. 12 (2023): 1684–91. http://dx.doi.org/10.22214/ijraset.2023.57682.

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Abstract: FeRAM, or Ferroelectric Random Access Memory, is a memory technology that combines the benefits of flash memory and RAM. It uses a ferroelectric substance that remains polarized even when electricity is switched off, allowingit to store data without constant power. The goal of FeRAM study is to comprehend its fundamental concepts, identify its distinctive features, and investigate its possible uses in ferroelectric material analysis, polarization dynamics, and system integration, among other areas of electrical equipment. FeRAM's potential is constrained by density and production cos
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Toto, Irwan Moses, Parma Hadi Rantelinggi, and Marlinda Sanglise. "Nextcloud Storage Design as E-Learning Data Storage Media in SMA Negeri 2 Manokwari." JISTECH: Journal of Information Science and Technology 12, no. 1 (2023): 52–58. http://dx.doi.org/10.30862/jistech.v12i1.199.

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Conventional learning systems in general have difficulty in distributing teaching materials which certainly require costs, giving assignments to students that burden the teacher himself in the collection of assignments and the process of assessing assignments, subject matter whose storage security in memory/flashdisk is not guaranteed so that with the nextcloud storage media which is cloud storage and integrated with e-learning applications, has features that are in accordance with the learning environment and easy to use both teachers and students. The system will be built using Moodle on hos
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45

Srinivasa Sunil Chippada, Shekhar Agrawal, and Rahul Vats. "Data lakehouse implementation: A journey from traditional data warehouses." World Journal of Advanced Engineering Technology and Sciences 15, no. 1 (2025): 311–32. https://doi.org/10.30574/wjaets.2025.15.1.0224.

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This comprehensive article explores the evolution and implementation of modern data lakehouse architectures, which combine the best elements of data lakes and data warehouses to address contemporary data challenges. The article draws on extensive case studies and empirical evidence across multiple industries to document the transformation from traditional data storage systems to more flexible, scalable lakehouse solutions. Through detailed analysis of real-world implementations, the article examines critical technical challenges in schema evolution management, data quality at scale, and metada
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46

Hou, Gaopan, Jianfeng Ma, Jiayi Li, and Chen Liang. "Audit Outsourced Data in Internet of Things." Security and Communication Networks 2021 (May 8, 2021): 1–11. http://dx.doi.org/10.1155/2021/6662135.

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With the increase in network transmission rates, the Internet of Things (IoT) has gradually become a trend. Users can upload the data generated by the device to the cloud database to save local storage space, thereby reducing local storage costs. Because uploading data to the cloud loses physical control of the data, an audit is required. Traditional audit protocols are not completely suitable for lightweight devices in the IoT. This paper proposes a new type of audit protocol suitable for lightweight devices with weak computing power. This protocol transfers part of the computation of data ta
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Konakalla, Kiran. "Effective Archival of Salesforce Stale Data: A Strategy for System Optimization and Cost Efficiency." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 10 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem32667.

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This paper explores the importance of archiving stale data in Salesforce and how implementing an ongoing archival process helps maintain accurate, up-to-date information while optimizing system performance and reducing storage costs. As businesses generate vast amounts of data daily, the accumulation of outdated information can slow system operations, increase storage costs, and lead to data inaccuracies. The paper will outline best practices for Salesforce data archival, including soft archival strategies, hard deletion, data backup procedures, and integration precautions. Examples of account
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Varri, Uma Sankararao. "Privacy-Preserving Ciphertext-Policy Attribute-Based Search over Encrypted Data in Cloud Storage." Journal of Computer Science and Technology 23, no. 1 (2023): e07. http://dx.doi.org/10.24215/16666038.23.e07.

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Cloud storage is one of the cloud computing services which allows data users to store their data remotely to the cloud. Thus, most individuals, institutions, and organizations are outsourcing their data to the cloud. Most popular cloud-based storage services are Amazon S3, Google Drive, Microsoft Azure, Apple iCloud, Dropbox, etc. Cloud storage service brings significant benefits to data owners, say, (1) reducing capital and management costs (2) reducing cloud users’ burden of storage management and equipment maintenance, (3) avoiding investing a large amount of hardware, (4) accessing data ov
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Athreya, Mr Rakshith P., and Dr Kanta D. Devangavi. "Feature Matching Search Mechanism Over Encrypted Cloud Data." International Journal for Research in Applied Science and Engineering Technology 11, no. 7 (2023): 1619–23. http://dx.doi.org/10.22214/ijraset.2023.54920.

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Abstract: In recent years, there has been a lot of research done on encrypted search technologies. Creating indexes with separate keywords has led to high storage costs and poor search accuracy, which has made the issue urgently need to be solved as more and more data is being stored in the cloud. So, for encrypted cloud data, we provide a novel feature matching ranked search method (FMRSM) in this study. This approach builds indexes using the feature score algorithm (FSA), which enables multiple keywords to be mapped to an index dimension after being taken from a page as a feature. As a resul
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Mozzherin, Dmitry, and Deborah Paul. "Preservation strategies for biodiversity data." Biodiversity Information Science and Standards 7 (August 22, 2023): e111453. https://doi.org/10.3897/biss.7.111453.

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We are witnessing a fast proliferation of biodiversity informatics projects. The data accumulated by these initiatives often grows rapidly, even exponentially. Most of these projects start small and do not foresee the data achitecture challenges of their future. Organizations may lack the necessary expertise and/or money to strategically address the care and feeding of this expanding data pile. In other cases, individuals with the expertise to address these needs may be present, but lack the power or status or possibly the bandwidth to take effective actions. Over time, the data may increase i
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