23 papers · ranked by Valyu relevance
Shurui Gao, Weidong Meng
Because the distributed storage system is based on network technology, it can store data in multiple independent low-cost physical storage devices, and it is also suitable for large-capacity storage, so it has become more and more popular. Today, common applications of distributed storage systems include cloud storage…
Dante D. Sánchez‐Gallegos, J. L. González-Compeán, Maxime Gonthier, Valérie Hayot‐Sasson + 5 more
Dante D. Sanchez-Gallegos ∗ , J. L. Gonzalez-Compean† , Maxime Gonthier‡ , Valerie Hayot-Sasson‡ J. Gregory Pauloski‡ , Haochen Pan‡ , Kyle Chard‡ , Jesus Carretero ∗ , and Ian Foster‡ ∗ Department of Computer Science University Carlos III of Madrid, Leganes, Spain Email: dantsanc@pa.uc3m.es †Cinvestav Tamaulipas, Cd.…
Srimugunthan, K. Gopinath
— For large scale distributed storage systems, flash memories are an excellent choice because flash memories consume less power, take lesser floor space for a target throughput and provide faster access to data. In a traditional distributed filesystem, even distribution is required to ensure load-balancing, balanced…
Shaoming Pan, Yongkai Li, Zhengquan Xu, Yanwen Chong + 1 more
Declustering techniques are widely used in distributed environments to reduce query response time through parallel I/O by splitting large files into several small blocks and then distributing those blocks among multiple storage nodes. Unfortunately, however, many small geospatial image data files cannot be further…
Robert Primmer
In this paper we look at the growth of distributed object stores (DOS) and examine the underlying mechanisms that guide their use and development. Our focus is on the fundamental principles of operation that define this class of system, how it has evolved, and where it is heading as new markets expand beyond the use…
Anindita Mondal, Madhupa Sanyal, Ari Kusumastuti, Hrishav Bakul Barua + 1 more
'Hrishav Bakul Barua' 'Kartick Chandra Mondal'] Today's era is the digitized era. Managing such generated big data is an important factor for data scientists. Day by day, it increases the demand for big data storage systems. Different organizations are involved in providing storage-related services. They follow the…
Ajay Kumar, Seema Bawa
Big data storage management is one of the most challenging issues for Grid computing environments, since large amount of data intensive applications frequently involve a high degree of data access locality. Grid applications typically deal with large amounts of data. In traditional approaches high-performance computing…
Shubham Malhotra
A Case Study of GFS, HDFS, and MinIO Authors: ['Shubham Malhotra'] Abstract—Distributed File Systems (DFS) are essential for managing vast datasets across multiple servers, offering benefits in scalability, fault tolerance, and data accessibility. This paper presents a comprehensive evaluation of three prominent…
Alfredo Barron, Dante D. Sanchez-Gallegos, Diana Carrizales-Espinoza, J. L. Gonzalez-Compean + 2 more
'J. L. Gonzalez-Compean' 'Miguel Morales-Sandoval' 'Shih-Chia Huang'] Cloud storage has become a keystone for organizations to manage large volumes of data produced by sensors at the edge as well as information produced by deep and machine learning applications. Nevertheless, the latency produced by geographic…
Feng Liu, Cheng-yi Yang, Jie Yang, De-li Kong + 3 more
'Jia-yin Qi' 'Zhi-bin Li'] As a distributed storage scheme, the blockchain network lacks storage space has been a long-term concern in this field. At present, there are relatively few research on algorithms and protocols to reduce the storage requirement of blockchain, and the existing research has limitations such as…
Mirko Zichichi, Stefano Ferretti, Víctor Rodríguez-Doncel, Pietro Manzoni + 2 more
'Pietro Manzoni' 'Claudio Palazzi' 'Ombretta Gaggi'] Big Tech companies operating in a data-driven economy offer services that rely on their users’ personal data and usually store this personal information in “data silos” that prevent transparency about their use and opportunities for data sharing for public interest.…
Xiaoluo Huang, Yu Wang, Jiaxin Xu, Ziang Nie + 5 more
DNA data storage offers a viable strategy to address the impending data explosion. Early attempts to harness DNA as a storage medium have encountered scalability limitations, largely due to the complexity of codec algorithms, the generation of biochemically harmful sequences and lack of a robust architecture. We…
Jaclyn M Smith, Melvin Lathara, Hollis Wright, Brian Hill + 3 more
The affordability of next-generation genomic sequencing and the improvement of medical data management have contributed largely to the evolution of biological analysis from both a clinical and research perspective. Precision medicine is a response to these advancements that places individuals into better-defined…
Adnan Tahir, Fei Chen, Habib Ullah Khan, Zhong Ming + 3 more
'Shah Nazir' 'Muhammad Shafiq'] As the expenses of medical care administrations rise and medical services experts are becoming rare, it is up to medical services organizations and institutes to consider the implementation of medical Health Information Technology (HIT) innovation frameworks. HIT permits health…
Klaithem Al Nuaimi, Nader Mohamed, Mariam Al Nuaimi, Jameela Al-Jaroodi
'Jameela Al-Jaroodi'] We present a novel approach to solve the cloud storage issues and provide a fast load balancing algorithm. Our approach is based on partitioning and concurrent dual direction download of the files from multiple cloud nodes. Partitions of the files are saved on the cloud rather than the full files…
Davi R. Ortega, Catherine M. Oikonomou, H. Jane Ding, Prudence Rees-Lee + 2 more
Three-dimensional electron microscopy techniques like electron tomography provide valuable insights into cellular structures, and present significant challenges for data storage and dissemination. Here we explored a novel method to publicly release more than 11,000 such datasets, more than 30 TB in total, collected by…
Authors not listed
Machine learning models are transforming data-driven research across scientific disciplines, yet their deployment as accessible and reliable web services remains a significant challenge. We introduce the NERDD framework, a scalable, maintainable, and secure microservices platform designed to support the sustainable…
Julia Steinberg, Haim Sompolinsky
A long standing challenge in biological and artificial intelligence is to understand how new knowledge can be constructed from known building blocks in a way that is amenable for computation by neuronal circuits. Here we focus on the task of storage and recall of structured knowledge in long-term memory. Specifically…
Alyssa Kramer Morrow, George Zhixuan He, Frank Austin Nothaft, Eric Tongching Tu + 3 more
The decreasing cost of DNA sequencing over the past decade has led to an explosion of available sequencing datasets, leaving us with terabytes to petabytes of data to explore and analyze. It is critical for analysts in research and clinical settings to be able to develop new data-driven hypotheses from these datasets…
Authors not listed
Raman spectroscopy is an increasingly powerful and fast-growing analytical technique across diverse disciplines, from materials science and chemistry to biology and medicine, thanks to advances in Raman instrumentation and greatly supported by the flourishing of chemometrics and artificial intelligence (AI). However…
Yann Garniron, Thomas Applencourt, Kevin Gasperich, Anouar Benali + 15 more
Quantum Package is an open-source programming environment for quantum chemistry specially designed for wave function methods. Its main goal is the development of determinant-driven selected configuration interaction (sCI) methods and multi-reference second-order perturbation theory (PT2). The determinant-driven…
Authors not listed
Next Generation Risk Assessment (NGRA) promotes animal-free, exposure-informed, and hypothesis-driven approaches to chemical safety assessment. In silico tools, such as quantitative structure-activity relationship (QSAR) models, are valuable new approach methodologies (NAMs) for use in NGRA. However, the practical…
Yann Garniron, Thomas Applencourt, Kevin Gasperich, Anouar Benali + 15 more
Quantum Package is an open-source programming environment for quantum chemistry specially designed for wave function methods. Its main goal is the development of determinant-driven selected configuration interaction (sCI) methods and multi-reference second-order perturbation theory (PT2). The determinant-driven…