Data Storage Management Research Articles

HDF5 in the exascale era: Delivering efficient and scalable parallel I/O for exascale applications

Accurately modeling real-world systems requires scientific applications at exascale to generate massive amounts of data and manage data storage efficiently. However, parallel input and output (I/O) faces challenges due to new application workflows and the state-of-the-art memory, interconnect, and storage architectures considered in exascale designs. The storage hierarchy has expanded with node-local persistent memory, solid-state storage, and traditional disk and tape-based storage, thus requiring efficiency at each layer and much more efficient data movement among these layers. This paper discusses how the ExaHDF5 project improved the I/O performance and data management for exascale architectures by enhancing HDF5, a widely used parallel I/O library. The team developed an Asynchronous I/O Virtual Object Layer (VOL) connector that allowed overlapping I/O with computation. They also created a Cache VOL to complement asynchronous I/O by incorporating fast storage layers, such as burst buffer and node-local storage, into the parallel I/O workflow through caching and staging data. Additionally, the team enabled data aggregation and I/O at the node level by using a Subfiling Virtual File Driver (VFD). To demonstrate superior I/O performance with HDF5 at exascale, the ExaHDF5 team collaborated with several exascale applications. In this paper, we show I/O performance improvements for three applications: Cabana (a particle-based simulation library), EQSIM (a regional earthquake simulation software), and E3SM (a climate system modeling library).

Location-aware job scheduling for IoT systems using cloud and fog

The rapid growth of Internet of Things (IoT) applications generates vast volumes of high-speed data streams from numerous devices. Cloud computing solutions often handle and manage this data; however, for certain applications, the latency introduced by transmitting data from edge devices to the cloud may be unacceptable. This issue is exacerbated by the bandwidth constraints of public networks, which become significant barriers in large-scale IoT implementations. Consequently, effective resource management, service management, data storage, and power management require more robust infrastructure and complex protocols. An "intelligent gateway" based on fog computing can enhance the efficient utilization of cloud and network resources. Resource planning and management in a fog-cloud environment significantly impact system performance, particularly latency. This problem is known to be NP-hard. This paper addresses the challenge of lifetime optimization for scheduling data-intensive tasks in fog and cloud-based IoT systems. Initially, we propose an Integer Linear Programming (ILP) optimization model to frame the problem. Subsequently, we introduce a heuristic method named Data-Locality Aware Job Scheduling in Fog-Cloud (DLSFC), which is derived from the proposed formulation. The effectiveness of DLSFC is evaluated across various system characteristics, with results demonstrating that DLSFC achieves solutions within 85 % of the ideal outcome provided by the LP solver.

Recent Advances in Intraoral Scanners.

Intraoral scanners (IOSs) have emerged as a cornerstone technology in digital dentistry. This article examines the recent advancements and multifaceted applications of IOSs, highlighting their benefits in patient care and addressing their current limitations. The IOS market has seen a competitive surge. Modern IOSs, featuring continuous image capture and advanced software for seamless image stitching, have made the scanning process more efficient. Patient comfort with IOS procedures is favorable, mitigating the discomfort associated with conventional impression taking. There has been a shift toward open data interfaces, notably enhancing interoperability. However, the integration of IOSs into large dental institutions is slow, facing challenges such as compatibility with existing health record systems and extensive data storage management. IOSs now extend beyond their use in computer-aided design and manufacturing, with software solutions transforming them into platforms for diagnostics, patient communication, and treatment planning. Several IOSs are equipped with tools for caries detection, employing fluorescence technologies or near-infrared imaging to identify carious lesions. IOSs facilitate quantitative monitoring of tooth wear and soft-tissue dimensions. For precise tooth segmentation in intraoral scans, essential for orthodontic applications, developers are leveraging innovative deep neural network-based approaches. The clinical performance of restorations fabricated based on intraoral scans has proven to be comparable to those obtained using conventional impressions, substantiating the reliability of IOSs in restorative dentistry. In oral and maxillofacial surgery, IOSs enhance airway safety during impression taking and aid in treating conditions such as cleft lip and palate, among other congenital craniofacial disorders, across diverse age groups. While IOSs have improved various aspects of dental care, ongoing enhancements in usability, diagnostic accuracy, and image segmentation are crucial to exploit the potential of this technology in optimizing patient care.

Full Stack Web Development

Full-stack development encompasses the comprehensive design and implementation of both client-side and server-side components of web applications. Utilizing HTML for structuring content, CSS for styling and layout, and JavaScript for dynamic interactivity, developers create engaging and responsive user interfaces. On the server side, PHP serves as a robust scripting language for handling back-end logic, including data processing and application flow. Coupled with MongoDB, a NoSQL database, developers manage data storage and retrieval efficiently, leveraging its flexibility for complex data structures. This synergy of technologies empowers developers to build scalable and high-performance applications that meet modern web standards. Index Terms—Web Development, Html, CSS, JavaScript, React, Php MongoDB.

A cross-chain-based approach for secure data sharing and interoperability in electronic health records using blockchain technology

In most healthcare facilities, Electronic Health Records (EHRs) have changed paper-based medical records in the healthcare industry. Nevertheless, there are issues with credibility, management, and secure data storage with the existing EHR frameworks. In order to fill this, this work establishes a cross-chain approach for EHR record sharing that is based on the interoperability of EHRs. Different entities, like patients, healthcare providers, Government Agencies (GA), blockchain, and ledger are included in the proposed system. Several processes including initialization, registration process, agreement and verification process, bank fund transfer and certificate generation, health record exchange among two hospitals, and secret key generation, are used to implement the newly developed authentication approach. In addition, the key is obtained from the interior layers of Deep Residual SpinalNet (Deep RSNet), which is utilized to encrypt the EHR records. The Deep RSNet is the integration of Deep Residual Network (DRN) and SpinalNet. The investigation of the developed technique exposes the supremacy of the Deep RSNet model by achieving minimal values of response time, memory usage, and normalized variance of 53.677 sec, 2.682 MB, and 1.346 respectively.

Traffic and transportation management data storage terminal based on Internet of Things

Traditional data storage models are inadequate in the face of the growing demand for big data in transportation and transportation management. Its poor horizontal scalability makes it difficult to deal with the growth of massive data; on the other hand, its complex management makes it challenging to achieve unified management and effective resource utilization due to the differences in equipment from different manufacturers. In order to effectively store and manage this huge amount of information, it is urgent to rely on advanced technical tools. In this context, while ensuring data security and simplifying data management, it is also necessary to meet the terminal’s demand for high real-time performance, and these factors jointly promote the continuous attention and improvement of data storage terminal performance. This paper proposes a Hadoop solution based on distributed computing. As a distributed system infrastructure, Hadoop allows users to develop distributed programs without a deep understanding of distributed details, fully using the high-speed computing and storage capabilities of Hadoop clusters, which is especially suitable for big data processing tasks on the Internet of Things (IoT) platform. The experimental results show that for a 10 GB data file, the traditional terminal (Terminal 1) can store 7.8 GB, while the Hadoop-based terminal (Terminal 2) can store 9.9 GB. For 50 GB of data files, Terminal 1 and Terminal 2 can store 40.4 GB and 49.8 GB of data respectively. These results show that Hadoop terminals have significant advantages in processing large-scale data, especially in terms of data storage efficiency, and can use storage resources more effectively to meet the high-performance requirements of traffic and transportation management for data storage terminals.

Telehealth Support System Using Wireless Technologies: The Case of Ethiopia

The explosion of wireless technologies including wireless networks, large flat displays, sensors, personal digital assistants (PDA), smartphones, and embedded devices are playing a great role in the communication and service delivery of daily life. Nowadays it is possible to extend different applications such as providing voice calls, remote consultation, remote discussion, remote health service, access other applications, and so on wirelessly to anywhere in the world over short or long distances. In consideration of the various advantages of wireless technologies, in this work, the aim to explore the use of wireless technologies in the health domain for remote health domain. The main objective of this work is to design and implement a telehealth support system that helps improve the quality of the existing health system. The system allows health professionals to have adequate access to patients, to medical information, to give health-related services remotely, remote consultation, and remote education to patients/people anywhere and anytime. This telehealth support system is developed using a Java programming language with different editions for different purposes such as J2EE to develop both server-side and client-side applications of the system, JSP to design the web interface for the server-side application of the system, J2ME CLDC/MIDP platform which ships with J2ME wireless toolkit emulator to develop and demonstrate MIDlet applications on the target small computing device, and MySQL database for data storage management.

Organization Efficiency Enhancement by DNA Technologies

This research investigates the augmentation of organizational efficiency through the integration of DNA technologies. By leveraging advancements in biotechnology, this study explores novel approaches to enhance processes related to data storage, computation, and information management within organizational frameworks. The utilization of DNA as a storage medium and computational substrate presents opportunities to address scalability challenges and improve overall efficiency. Through case studies and experimental validations, we elucidate the potential impact of DNA technologies on organizational workflows, offering insights into the transformative possibilities for information processing and storage in the evolving landscape of enterprises. Here we evaluate DNA traits by various DNA technologies and create/modify whole space of organizational premises such as office exterior and interior and structures such in such way to accelerate productivity & functioning of overall organisation processes.

Multilevel Anti-counterfeiting Barcode with Enhanced Information Encryption Based on Stimulus-Responsive Digital Polymers.

In response to the escalating challenges of counterfeiting due to technological and socioeconomic advancements, a novel trilevel anti-counterfeiting Quick Response (QR) code system has been developed. This system integrates digital polymers with QR code and stimulus-responsive chromophores, i.e., rhodamine B (RB), rhodamine 6G (R6G), and spiropyran (SP), to provide a sophisticated security solution. This advanced barcode remains concealed until specific stimuli reveal it and can be scanned by a smartphone, enabling first and second level anti-counterfeiting. For the third level of security, the encrypted information within the digital polymers can only be deciphered using tandem mass spectrometry. This innovative approach not only enhances security features but also offers reversible visibility and a complex verification process. This trilevel system surpasses traditional single-level anti-counterfeiting methods and holds significant potential for future applications in protecting brand authenticity and managing data storage, contributing new concepts and techniques to the field of high-security anti-counterfeiting materials.

Deduplication on Encrypted Data in Cloud Computing

Cloud storage is a crucial component of cloud computing, allowing users to expand their storage without upgrading their equipment and overcome resource constraints. Cloud users' data is always encrypted before being outsourced to ensure their security and privacy. However, encrypted data may result in a significant waste of cloud resources. Storage complicates data sharing among authorized users. We continue to face issues with encrypted data storage and deduplication. Traditional deduplication strategies are designed for certain application settings where data owners or cloud servers have full control over the process. They cannot meet data owners' varying requests based on data sensitivity. This study proposes a flexible data storage management method that combines deduplication and access control across various Clouds. Service Providers (CSP). We assess its performance through security analyses, comparisons, and implementations. The results demonstrate security, effectiveness, and efficiency for actual applications.

Blockchain Technology for Integrating Electronic Records of Digital Healthcare System

Background: In most healthcare facilities, the shift from paper-based medical records to electronic health records (EHRs) has taken place. However, there are issues with credibility, management, and secure data storage with the existing EHR systems. In the healthcare industry, interoperability and user control over personal data are also major challenges. Block chain technology has become a potent tool that can provide immutability, security, and user control over records that are saved; yet, its potential usage in EHR systems is still not well understood. Objectives: This research attempts to close this knowledge gap by developing an EHR framework that is built on blockchain technology and is compatible with many national and international EHR standards, including HL7 and HIPAA. Methods: In order to investigate the state of the art in the field of EHRs, including blockchain-based EHR implementations, a systematic literature review is the study approach used. Results: The report analyzes numerous national and international EHR standards, identifies the interoperability needs based on these standards, and outlines the interoperability challenges in the current blockchain-based EHR frameworks. Without the requirement for centralized systems, the suggested framework can give the healthcare industry safer ways to exchange health information while also offering the features of immutability, security, and user control over stored records. Conclusion: This work contributes to the understanding of Blockchain technology's potential application in EHR frameworks and offers an interoperable Blockchain-based EHR framework that can meet the requirements outlined in multiple national and international EHR standards.

ApIsoT: An IoT Function Aggregation Mechanism for Detecting Varroa Infestation in Apis mellifera Species

In recent years, the global reduction in populations of the Apis mellifera species has generated a worrying deterioration in the production of essential foods for human consumption. This phenomenon threatens food security, as it reduces the pollination of vital crops, negatively affecting the health and stability of ecosystems. The three main factors generating the loss of the bee population are industrial agriculture, climate changes, and infectious diseases, mainly those of parasitic origin, such as the Varroa destructor mite. This article proposes an IoT system that uses accessible, efficient, low-cost devices for beekeepers in developing countries to monitor hives based on temperature, humidity, CO2, and TVOC. The proposed solution incorporates nine-feature aggregation as a data preprocessing strategy to reduce redundancy and efficiently manage data storage on hardware with limited capabilities, which, combined with a machine learning model, improves mite detection. Finally, an evaluation of the energy consumption of the solution in each of its nodes, an analysis of the data traffic injected into the network, an assessment of the energy consumption of each implemented classification model, and, finally, a validation of the solution with experts is presented.

StructMesh: A storage framework for serverless computing continuum

Computing continuum is becoming a solution for organizations to process and analyze data for supporting decision-making processes. In this context, serverless paradigm is arising as a solution to manage continuum computing. However, the management of data storage still represents an obstacle for integrating continuum computing and serverless paradigms into a single solution, as this has to be performed transparently to users through multiple infrastructures. This paper presents StructMesh, a storage framework for serverless continuum systems. This framework is based on a processing plane where functions are managed as patterns, and a data plane based on storage meshes that represent maps of storage resources available in a given infrastructure. The logical interconnection of storage meshes enables organizations to integrate storage resources into a single unified storage service, which creates data exchange channels for continuum processing throughout multiple infrastructures. These meshes include load-balancing and data allocation/location algorithms for transparently and automatically managing the inputs/outputs of functions throughout these channels, as well as non-functional requirement schemes for organizations to manage sensitive data. We developed a framework prototype that harmonizes processing serverless functions with storage functions for building serverless pipeline services. A case study was conducted by using these services for processing meteorological and earth observation data throughout multiple infrastructures. The evaluation revealed the efficiency of StructMesh when managing data through fog and cloud infrastructures. It also showed the feasibility of StructMesh to create and enable continuum data exchange channels for serverless pipelines.

Use of the FallAkte Plus System as an IT Infrastructure for the North Rhine-Westphalian General Practice Research Network: Mixed Methods Usability Study.

Primary care research networks can generate important information in the setting where most patients are seen and treated. However, this requires a suitable IT infrastructure (ITI), which the North Rhine-Westphalian general practice research network is looking to implement. This mixed methods research study aims to evaluate (study 1) requirements for an ITI and (study 2) the usability of an IT solution already available on the market, the FallAkte Plus (FA+) system for the North Rhine-Westphalian general practice research network, which comprises 8 primary care university institutes in Germany's largest state. In study 1, a survey was conducted among researchers from the institutes to identify the requirements for a suitable ITI. The questionnaire consisted of standardized questions with open-ended responses. In study 2, a mixed method approach combining a think-aloud approach and a quantitative survey was used to evaluate the usability and acceptance of the FA+ system among 3 user groups: researchers, general practitioners, and practice assistants. Respondents were asked to assess the usability with the validated system usability scale and to test a short questionnaire on vaccination management through FA+. In study 1, five of 8 institutes participated in the requirements survey. A total of 32 user requirements related primarily to study management were identified, including data entry, data storage, and user access management. In study 2, a total of 36 participants (24 researchers and 12 general practitioners or practice assistants) were surveyed in the mixed methods study of an already existing IT solution. The tutorial video and handouts explaining how to use the FA+ system were well received. Researchers, unlike practice personnel, were concerned about data security and data protection regarding the system's emergency feature, which enables access to all patient data. The median overall system usability scale rating was 60 (IQR 33.0-85.0), whereby practice personnel (median 82, IQR 58.0-94.0) assigned higher ratings than researchers (median 44, IQR 14.0-61.5). Users appreciated the option to integrate data from practices and other health care facilities. However, they voted against the use of the FA+ system due to a lack of support for various study formats. Usability assessments vary markedly by professional group and role. In its current stage of development, the FA+ system does not fully meet the requirements for a suitable ITI. Improvements in the user interface, performance, interoperability, security, and advanced features are necessary to make it more effective and user-friendly. Collaborating with end users and incorporating their feedback are crucial for the successful development of any practice network research ITI.

A Classification of Cloud Services and Their Security Assessment in the Healthcare Industry

The role of cloud-based services in healthcare settings is crucial in the 21st century. This paper discusses their advantages and tools in hospitals, clinics, and diagnostic centers, categorizing existing applications and services into data storage, computing power, networking, PaaS, SaaS, data analytics, business intelligence, and project management. It also provides an in-depth analysis of security and risk assessment issues in cloud-based services, supported by case studies. Additionally, it includes a comparative risk analysis diagram of secured versus non-secured cloud systems in healthcare. Finally, the paper concludes with recommendations for future work. Key Words: Healthcare facilities, diagnostic centers, cloud services, information technology systems, security, risk analysis.

Enhanced Machine Learning for Cloud Computing Electricity Cost Prediction

Cloud computing is becoming popular in the tech industry as it offers convenient computing without the need to buy physical hardware. Instead, companies provide these services using their own computers and servers powered by electricity. However, running these data centers consumes a lot of energy, and with rising electricity prices, minimizing energy usage has become a big challenge. One way to tackle this is by efficiently managing data storage and scheduling tasks. In this article, we suggest using an advanced machine learning model called Extreme Gradient Boosting (XGBoost) to predict electricity prices and optimize data storage, helping to reduce energy costs in data centers

Efficient Data Storage Management and Reducing Deduplication in Cloud Computing

Efficient Data Storage Management and Reducing Deduplication in Cloud Computing

DATA FINDING, SHARING AND DUPLICATION REMOVAL IN THE CLOUD

Deduplication involves eliminating duplicate or redundant data to reduce stored data volume, commonly used in data backup, network optimization, and storage management. However, traditional deduplication methods have limitations with encrypted data and security. The primary objective of this project is to develop new distributed deduplication systems that offer increased reliability. In these systems, data chunks are distributed across the Hadoop Distributed File System (HDFS), and a robust key management system is utilized to ensure secure deduplication with slave nodes. Instead of having multiple copies of the same content, deduplication removes redundant data by retaining only one physical copy and referring other instances to that copy. The granularity of deduplication can vary, ranging from an entire file to a data block. The MD5 and 3DES algorithms are used to enhance the deduplication process. The proposed approach in this project is the Proof of Ownership (POF) of the file. With this method, deduplication can effectively address the issues of reliability and label consistency in HDFS storage systems. The proposed system has successfully reduced the cost and time associated with uploading and downloading data, while also optimizing storage space. Key Words: Cloud computing, data storage, file checksum algorithms, computational infrastructure, duplication.

BIM implementation for Nigeria’s polytechnic built environment undergraduates: challenges and possible measures from stakeholders

PurposeStudies show that building information modelling (BIM) technology can improve construction productivity regarding the design, construction and maintenance of a project life cycle in the 21st century. Revit has been identified as a frequently used tool for delivering BIM in the built environment. Studies about BIM technology via Revit are scarce in training middle-level workforce higher education institutions. Thus, this study aims to investigate the relevance of BIM technology and offer measures to promote digitalisation in Nigeria’s built environment polytechnic undergraduates via Revit.Design/methodology/approachGiven the unexplored nature of training the middle-level workforce in Nigeria, 37 semi-structured virtual interviews were conducted across Nigeria, and saturation was achieved. The participants were knowledgeable about construction-related BIM. The researchers used a thematic analysis for the collected data and honed them with secondary sources.FindingsImproved visualisation of design, effective and efficient work productivity, automatic design and quantification, improved database management and collaboration and data storage in the centrally coordinated model, among others, emerged as BIM’s benefits. BIM technology via Revit is challenging, especially in Nigeria’s polytechnic education curriculum. The 24 perceived issues were grouped into government/regulatory agencies-related, polytechnic management-related and polytechnic undergraduate students-related hindrances in Nigeria’s built environment.Research limitations/implicationsThis study is limited to BIM implications for Nigeria’s built environment polytechnic undergraduates.Originality/valueThis study contributes to the literature paucity in attempting to uncover perceived issues hindering the implementation of BIM technology via Revit in training Nigeria’s built environment polytechnic undergraduates via a qualitative approach.

Blockchain-Based Data Storage for Internet of Things Networks

Consensus mechanisms are fundamental to blockchain technology, ensuring network integrity and the orderly progression of transactions. However, the predominant proof of work method, while widely adopted, has raised concerns regarding its energy-intensive nature and lack of scalability. In response, this research explores alternative consensus methods tailored to participants' engagement in blockchain storage activities. We conducted a comprehensive review of existing approaches, examining their reusability and efficacy. Concurrently, we observed a growing demand for distributed storage solutions driven by escalating data volumes. Our investigation identified areas for improvement in existing storage blockchains, motivating the development of our own system, BlockStock. This protocol, meticulously designed, aims to enhance intelligent data storage management reliably and robustly. Through rigorous performance evaluations, including assessments of power consumption, throughput, and data transfer times, BlockStock demonstrates superior efficacy and cost-effectiveness. These findings underscore its significance as a notable advancement in blockchain-based storage solutions, offering a promising avenue for future research and application.