Data Storage Services Research Articles

Development of the automated data management system for radiation monitoring of forests

Since the system of radiation control in forestry was formed even before the mass introduction of information technologies, data processing in radiation monitoring retains the approaches conditioned by the traditional, paper-based document management. The aim of this project is to develop a unified automated system for collection, control and analysis of data from radiation monitoring of forests in the Russian Federation. The system is based on the use of the unified software ‘SpectraLineBG’ for spectrometric devices, on the creation of a cloud data storage server, and the development of a software environment for storing and processing of the obtained material. The system allows to check the accuracy of all the obtained results of measurements and to make their subsequent correction. The described method of data collection is universal for spectrometric studies and can be used not only in forestry, but also in any organization involved in radiation control of the environment. Using the accumulated material, the system allows to analyze the distribution and the dynamics of radionuclides in space and time, to calculate the coefficients of the transition of radionuclides from soil to vegetation for one or more species in different areas.

Decision Making Models on the Market of Cloud Services

Introduction. Optimization can be applied in developing profitability management tools for a cloud service broker working according to a certain business model. On behalf of the managing telecommunications holding company (telecommunications operator), this broker integrates, aggregates and configures software and data storage services of third-party Internet software vendors. Such a broker receives only fixed commissions from this company, based on the subscription fee, but does not pay royalties to an Internet software vendor and does not receive payments from the sale of service packages. The purpose. The cloud broker faces the problem of limited human resources required to carry out the relevant legal, technical and economic activities. In addition, the broker faces the problem of uncertainty in sales, service prices, the share of resource use, or the risk of losing operational and financial goals. Results. To run a broker?s business efficiently, one needs to find services and their bundles that increase profitability and reduce financial risk by solving certain optimization problems. Information on such services is needed to support negotiations on fixed and variable commissions, as well as to prioritize services and their packages to be provided. Thus, for the cloud services broker, both profitability management tools and services portfolio development tools are useful. In general, a cloud service broker is an organization that negotiates the relationships between cloud service clients and Internet software vendors. Cloud broker can be created on the basis of different business models regarding the type of service (platform, infrastructure, software), type of clients (enterprise, household), functions performed (identity management, accounting, billing, location, etc.), the degree of rebranding, measures of aggregation of services and other criteria. Conclusions. Different cloud brokers have different attitudes to choice of important solutions for their businesses. Solutions can relate to pricing, capacity planning and utilization in combination with service quality, security, scalability and other issues. Keywords: optimization, portfolio, uncertainty, Boolean variables, revenue generation.

ETWatch cloud: APIs for regional actual evapotranspiration data generation

Increased model complexity and data quantities have raised the computing power requirement for efficient evapotranspiration (ET) estimation. A cloud-based service is presented to encapsulate and publish the ETWatch modeling algorithms as web application programming interfaces (APIs) in a consistent style to provide extensible model calculation service and data storage service in a cloud platform for water managers and stakeholders. The prototype system, named ETWatch Cloud allows users to rapidly and easily set up an ET generation project for any region of interest by invoking APIs directly to produce ET data using a web browser or local integrated development environment. The case study demonstrates that ETWatch Cloud can provide a highly scalable and interoperable ET generation tool for stakeholders from ET community, helping to facilitate the application of remote sensing-based ET algorithms for water management in hydrology sector.

Publicly verifiable outsourced data migration scheme supporting efficient integrity checking

With the rapid development of cloud storage, an increasing number of data owners prefer to store their large-scale data on the remote cloud for greatly reducing the burden of maintaining the data by themselves. Since different cloud storage service providers offer distinct quality of data storage services, secure outsourced data migration becomes a fundamental requirement for data owners to change their cloud storage service providers. As a result, how to guarantee the correctness and integrity of the outsourced data blocks when they are being migrated from one semi-trusted cloud host to another becomes a primary concern of data owners. To solve this problem, we propose a blockchain-based publicly verifiable data migration scheme supporting efficient data integrity checking for cloud storage in this paper. Specifically, the data owner can dynamically change the cloud storage service providers and securely migrate the outsourced data from one cloud host to another, without retrieving the transferred data from the original cloud host, and checking the transferred data integrity in the target cloud host. By making use of blockchain, our proposed scheme can simultaneously achieve data migration and integrity checking without interacting with a third party auditor, thus avoiding the problems of service interruption and privacy leakage caused by the single-point-of-failure of the third party auditor, which is much better than the previous schemes. Meanwhile, our proposed scheme is provable secure in the random oracle model. Finally, we also develop a prototype implementation of our proposed scheme and compare the efficiency with some existing schemes. The experimental result demonstrates that our proposed scheme is more efficient and practical.

Studi Literatur Keamanan dan Privasi Data Sistem Cloud Computing Pada Platform Google Drive

In today's era, we can do mobilization activities anytime and anywhere. Especially with the cloud computing system that makes it easy to interact from one computer to another without consuming a lot of money. This allows us to access data and information from computers or accounts that are connected. Google Drive is a data storage and synchronization service provided by Google. Where every user can use cloud computing in the form of file sharing and editing collaboration. The purpose of this paper is to find out how the challenges and solutions for data security and user privacy are on the Google Drive platform.

Attribute-Based encryption mechanism with Privacy-Preserving approach in cloud computing

Native hardware and code maintenance are not burdened by a cloud computing infrastructure that provides customers with the abilité to remote storage and use the cloud dominance applications on request. Although cloud storage draws additional exposure to those opportunities than ever before, it also introduces outsourced information of innovative and challenging security threats. Up to now an overly wide range of strategies has been projected to deal with this drawback to confirm info protection and credibility in cloud computing, but all of them have their own intrinsic limits. The structured Ciphers text-policy attributes model mostly based on the algorithmic rule for hidden writing (CP-ABE) with a data structure for improving quantifiable and adaptation will be provided during this project. In order to avoid unwanted data access and integrity, the database server is completely removed. The metrics of efficiency suggest that the theme is cost efficient in handling the information so that it is kept within the data storage servers and greatly decreases the time of processing.

Web Based UCloud Application Using CodeIgniter Framework

Internet-based data storage services or called the cloud are becoming a global technology trend, the cloud that offers unlimited scalability is becoming very reliable. Educational institutions such as Qamarul Huda Badaruddin University are always constrained by poor data management because there is no centralized data storage area that can be accessed together. With the presence of UCloud, data management problems can be resolved. Designed using the web-based CodeIgniter framework, Ucloud has been successfully implemented and optimally utilized by the academic community, so that data can be managed properly.

Modified SeDaSc system for efficient data sharing in the cloud

SummaryOrganizations tend to store their sensitive data on trusted cloud data storage server to protect it from outside security attacks. However, storing data on the cloud has serious security issues like data misuse from the cloud vendors themselves and attacks from outsources. In this manner, the organizations tend to encrypt their data before storing it in the cloud to protect against the misuse from the cloud vendors and other outer attacks. This article offers an enhancement to Secure Data Sharing in the Cloud (SeDaSc) system in terms of enhancing security metrics related to data privacy and disk storage handling. In the proposed system, the cryptographic server (CS) has been treated a semi‐trusted entity by not giving direct access to the data directly. The data encryption is carried at the client side. While, the keys generation and other related cryptographic operations as the access control list (ACL) management are carried at the CS. The client generates the hash of the file needed to be shared in the cloud and then sends such hash to the CS. Then, the CS uses the hash to generate the cryptographic key and sends it to the client for encryption process. Further, the proposed system achieves better disk management by only updating the ACL in case of uploading the same file more than once. The CS stores generated key hash and whenever receives a new file, the CS compares the hash of the generated key with other stored hashes. The hash computation in key generation in the proposed system makes the key generation process varies with data size in compare with the key generation process in SeDaSc that is independent on data size. Furthermore, in the case of identical hashes, the ACL will only be updated. Therefore, the identical files neither will be encrypted nor uploaded to cloud twice. The proposed system has been represented mathematically and graphically using high level petri net model and simulated by python language environment.

Active auditing Services for Storing and Securing the Data in the Cloud

Cloud computing paradigm is a variation on the long vision of computing as utilisation of resources, in which data owners can host all data tenuously in the cloud and access high-quality software products on demand from a mutual pool of configurable computing resources. We create a secure storage system to alleviate data owners' burdens and to remove their substantial control over storage reliability and security, we develop a secure data storage services with high service-level requirements. Our proposed one involves three favors: the cloud server, data owner and TPA. The pros and cons of cloud computing are examined in this paper and then we put a set of analytically and cryptographically desirable properties allowing large data storage security audit services to become a authenticity. Active auditing is required to check the dynamic data integrity. But it's not easy to do an audit effectively, since data is complex in the cloud. To fail the auditing process, server will implement replay attack and forge attack. Modification, insertion and deletion comprise the complex operations. The owner sends the update message to the auditor any time the complex operation is performed. Built on the techniquepart structure, random case and Dynamic-Hash Table(DHT), our audit service can support validated improvements to externalise the data, and timely abnormal detection.

KRanTi: Blockchain‐based farmer's credit scheme for agriculture‐food supply chain

AbstractThe advent of agro‐industrialization has helped the agricultural food supply chain (AFSC) in introducing ease and innovation to other facets. In addition, Blockchain (BC) technology is revolutionizing each distributed data‐related application by adding authentication and trust among the system's stakeholders. Inspired by the above‐mentioned argument, this article proposes a system, KRanTi, to promote the supply chain of agricultural food by BC embedding across the 5G network. The 5G network upgrades the data connectivity by enhancing network infrastructure efficiency. In KRanTi, we present an efficient credit system that enables associated farmers to purchase the requisite agricultural raw product of higher quality without the pressure of instant payment. A score‐based farm‐food quality assurance system is then proposed, which guarantees optimal quality grading. Trust, transparency, and traceability are preserved through the implementation of Smart Contracts (SC) distributed across public Ethereum BC. The cost‐effective off‐line data storage service in AFSC is offered through the use of the Inter‐Planetary File System (IPFS), a shared storage system to hold all data from stakeholders. Results show that the efficiency of the proposed scheme KRanTi is improved compared with traditional schemes with metrics such as less than 1 millisecond latency with 99.99% reliability compared with LTE with 5G, scalability, packet failure ratio, BC performance, cost‐quality ratio, and data storage contrast.

A-DECS: Enhanced collaborative edge–edge data storage service for edge computing with adaptive prediction

Due to the rapid development of IoT and 5G technologies, end-users of the Internet are generating a sea of data, which burdens the cloud cores and data centers. The urgent traffic demand causes a bad quality of experience in the traditional reactive networks. With the improvement of hardware, the edge of the Internet can share some responsibility for cloud servers. In small-scale scenarios, offload computing and storage tasks to edge nodes can help improve the user experience and utilize resources of the edge networks. In this paper, we propose a collaborative edge–edge data storage service with adaptive prediction called A-DECS based on our previous work DECS (Zhou and Chen, 2020) in local area scenarios. It manages nodes in the edge network and fully utilizes the limited resources in the cluster. A-DECS picks the most appropriate node to offload tasks. It can also proactively replicate popular data and generate forwarding rules in advance. A-DECS can reduce the read latency of cold-start and sudden peak flow situations. We compare it to state-of-the-art research. This experiment result proves that A-DECS is more suitable for edge clusters due to its lower latency and better resource utilization.

Construction and Research of Digital Archives Cloud Platform Based on Big Data Management

Cloud computing has the characteristics of super computing power, low cost and high security, as well as providing powerful data storage and network services. In the commercial field, it has begun to take shape. This paper attempts to introduce cloud computing technology into the construction of digital archives, analyzes the possibility and reality of the application of cloud computing technology services in the service and management of digital archives from the common point of view of cloud computing services and digital archives, and puts forward the corresponding ways of cloud computing application in digital archives. This paper analyzes and integrates all kinds of risks that digital archives may face under the cloud computing environment, and establishes the security evaluation index system including the security elements of information system and cloud computing technology. In this paper, fuzzy comprehensive evaluation method is used to evaluate the mathematical model of cloud digital archives security evaluation system, and a set of security evaluation system suitable for cloud digital archives is proposed.

Fine Grained Decentralized Access Control With Provable Data Transmission and User Revocation in Cloud

Cloud computing started a new era for IT enterprises. It allows the movement of application from local to remote location, massive data storage. Owner has access to centralized or decentralized data storage server, where data management handled by remote vendor. But, the heterogeneous and dynamic nature of cloud introduces security challenges. Among them, access control and integrity checking are most important which incur high consideration. Attribute-based encryption is one of the access control technique which allows integration of access policies, attributes, and encrypted data. In this paper, a new fine-grained decentralized data access control technique with user revocation has been proposed. Here, service provider is responsible for verifying the user authenticity. The proposed schema supports integrity checking and user revocation. The integrity checking proof validates that the user data is intact and revocation mechanism will help to revoke the user in linear time. Moreover, the proposed access control and authentication schemes are decentralized and comparable to other approaches.

Analysis of land data acquisition and management and their challenges in Ethiopia

This study aimed to assess the current land data acquisition system, data sharing mechanism and major challenges in Ethiopia. A total of 26 institutions working mainly on land data collection, management, dissemination, and use were purposively selected. Data were collected from these institutions using face-to-face interviews, focus group discussions and observations. Besides, international standards were reviewed. The data were analysed using descriptive statistics and qualitative techniques. The results showed that all the surveyed institutions have some land data produced by themselves or other institutions. However, the data is not in compliance with any of the geospatial data standards. Moreover, some institutions do not have clear information about the source and accuracy of their data holding. Data storage systems, e.g., data warehouses and server were practiced by some institutions. Data duplication, lack of data sharing protocol and limited cooperation between institutions are the major challenges of land data management in Ethiopia.

Comments to Jean-Claude Burgelman's article Politics and Open Science: How the European Open Science Cloud Became Reality (the Untold Story)

Comments to Jean-Claude Burgelman's article <i>Politics and Open Science: How the European Open Science Cloud Became Reality (the Untold Story)</i>

Application of Cloud Computing in Education Management Informatization Construction

In recent years, with the rapid development and continuous optimization of computer network information technology, cloud computing technology has already developed from the experimental initial stage to the stage of large-scale computer enterprise application and campus LAN universal application. And driven by scientific and technological innovation, cloud computing provides users with better and safer data management, calculation, storage and other services because of its unique resource sharing and convenient management and maintenance, which has attracted wide attention and favor from all walks of life. The emergence of cloud computing technology has ignited new thinking for our education and teaching. If computer multimedia and Internet, as the previous round of technologies, have brought about changes in teaching presentation, teaching resource acquisition and education transmission, the new technologies based on cloud computing will not only continue to deepen the previous educational changes, but also bring more profound fission to education. Under the guidance of new technology, the ever-changing and innovative “future education” will be more fascinating, and provide us with a broader development space for the construction of educational informationization. With the help of the service advantages of cloud computing, combined with the modern teaching concept, it can be applied to information teaching, which is just conducive to improving the teaching level of higher vocational education and realizing efficient teaching work. At present, most universities in China use cloud computing for teaching management, breaking the traditional mode of university resource management, fully combining with contemporary advanced concepts and technologies, and keeping pace with the times.

RETRACTED: Design of Russian corpus based on embedded system and cloud computing

Russian Learner Corpus (Radio Link) first corpus and foreign language learners , and there is a noticeable difference between traditional speakers. Russian Student Texts Corpus (CoRST) Language Lab is a computational and program for holes initiated by corpus. It will be a collection of Russian texts written by students of different Russian universities. Its main goal is to study language changes and mark language deviations. CoRST is provided with Metalanguage, morphology, and error specifications. Usually, an error part is marked with incorrect labels because it can be fixed in many ways. Also, corpus offers a search by spelling and construction compounds for two possible descriptive factors. Cost growth prospects need two calculations and methods—CoRST and legal and comparative statistical analysis of NRC language events. The define predictive methods for problem formulation and adjustment of the calculation model. The purpose of this work is to explain the answer to this problem. Combine sophisticated computing and computing prototype strategies to provide a flexible execution framework for cloud embedded or mobile devices as a test; an accreditation system developed. Cloud computing allows for advantages such as smooth performance, shortened development time, simpler embedded systems, and is considered impossible. Cloud computing functionality and performance is a collection of potential hardware and software remote server groups Centralized data storage and transfer Data services Online access to prediction resources.

Informatyka kryminalistyczna w kontekście usług przechowywania danych w chmurze obliczeniowej

The role and capabilities of digital forensics in the cloud computing environment still remain an unsolved and insufficiently explored scientific area. The growing popularity of cloud-based data storage services makes recovery of evidence on the Internet a major challenge for forensic IT exminers. Existing legal barriers in most cases prevent direct access to cloud stored resources for the purpose of recovering data. In many situations, assistance from foreign law enforcement and judicial authorities is required. Findings made during forensic IT analysis that allow reconstructing user’s activities and indicate the act of taking advantage of cloud computing data storage is a justification for undertaking international cooperation. Therefore, it is important to know potential sources of information that enable the reconstruction of the activity of the user in cloud computing services, as well as the awareness of the current state of knowledge and scientific research in this field.

Heuristic Edge Server Placement in Industrial Internet of Things and Cellular Networks

Rapid developments in industry 4.0, machine learning, and digital twins have introduced new latency, reliability, and processing restrictions in Industrial Internet of Things (IIoT) and mobile devices. However, using current information and communications technology (ICT), it is difficult to optimally provide services that require high computing power and low latency. To meet these requirements, mobile-edge computing is emerging as a ubiquitous computing paradigm that enables the use of network infrastructure components such as cluster heads/sink nodes in IIoT and cellular network base stations to provide local data storage and computation servers at the edge of the network. However, optimal location selection for edge servers within a network out of a very large number of possibilities, such as to balance workload and minimize access delay, is a challenging problem. In this article, the edge server placement problem is addressed within an existing network infrastructure obtained from Shanghai Telecom's base station data set that includes a significant amount of call data records and locations of actual base stations. The problem of edge server placement is formulated as a multiobjective constraint optimization problem that places edge servers strategically to balance between the workloads of edge servers and reduce access delay between the industrial control center/cellular base stations and edge servers. To search randomly through a large number of possible solutions and selecting those that are most descriptive of optimal solution can be a very time-consuming process, therefore, we apply the genetic algorithm and local search algorithms (hill climbing and simulated annealing) to find the best solution in the least number of solution space explorations. Experimental results are obtained to compare the performance of the genetic algorithm against the above-mentioned local search algorithms. The results show that the genetic algorithm can quickly search through the large solution space as compared to local search optimization algorithms to find an edge placement strategy that minimizes the cost function.

Comparative Analysis of Database Query Storage Performance Between Stored Procedure and Function

This research was conducted to measure the data storage time carried out by the DBMS on data that has been prepared with an increasing number of data, the data provided is consistent student data which will be stored with Stored Procedure and Function. This study uses the action research method which has 4 stages, starting with planning, action, observation and reflection. From the results of the experiments that have been carried out, it appears that Stored Procedure is able to outperform Function in data storage time. The data provided are 2 different types of data, each of which consists of 500, 2500, 4500 and 6500 data stages. This study also compares data storage that is differentiated by the computer between the data provider computer and the data storage computer or server, the result of which is the Stored Procedure. able to outperform Function in data storage speed.