Provide Data Storage Research Articles

Machine Learning Algorithms for Automatic Anomalies Detection in Data Storage Systems Operation

Data storage reliability and availability play important role for a wide range of services and business processes. Manufacturers provide data storage systems that resistant to hardware and software failures but not for all cases. Well-timed detection of these failures help to recover the system faster and prevent the failures before they occur. In this work a range of machine learning and time series analysis algorithms for failures detection is considered. The algorithms are applied and compared on the real data storage system. Preliminary results show that binary classification methods demonstrate high failure detection and low false alarm rates. Time series prediction based approach shows similar results and outperforms one-class classification methods.

Development of a Compatible, Low Cost and High Accurate Conservation Remote Sensing Technology for the Hygrothermal Assessment of Historic Walls

This article aims to properly assess the hygrothermal properties of walls located in historic buildings, this study discloses the development of a remote sensing technology compatible with an in-situ measurement implemented in Palazzo Tassoni (Italy). As required by the international recommendations adapted to cultural heritage (CH), this monitoring system balances CH conservation, performance aspects and economic costs using an integrated multidisciplinary approach. Electronics for measurement of environmental parameters is composed of sensor measurements, data acquisition system and data storage and communication system. Data acquisition system, equipped with standard modbus-rtu interface, is designed to run standalone and it is based on two cloned single board PCs to reduce the possibility of data loss. In order to reduce the costs, RaspberryPI single board PCs were chosen. These run a C/C++ software based on standard modbus library and designed to implement multi-client server TCP/IP to allow communication with other devices. Storage and communication systems are based on an industrial PC; it communicates with sensor measurements’ system through a modbus-TCPIP bridge. PC runs a Labview software to provide data storage on a local database and graphical user interface to properly see all acquired data. Herein, some sensing options and approaches of measurement are described, unveiling different possible ways of enhancing the retrofit of CH with adapted technology.

Practical Attribute-Based Multi-Keyword Search Scheme in Mobile Crowdsourcing

Cloud-based mobile crowdsourcing has been an attractive solution to provide data storage and share services for resource-limited mobile devices in a privacy-preserving manner, but how to enable mobile users to issue search queries and achieve fine-grained access control over ciphertexts simultaneously is still a big challenge for various circumstances. Although the ciphertext-policy attribute-based keyword search technology combining attribute-based encryption with searchable encryption has become a hot research topic, it just deals with equivalent attributes rather than more practical attribute comparisons, like “greater than” or “less than.” In this paper, we devise a practical cryptographic primitive called attribute-based multi-keyword search scheme to support comparable attributes through utilizing 0-encoding and 1-encoding. Formal security analysis proves that our scheme is selectively secure against chosen-keyword attack in generic bilinear group model and extensive experiments using real-world dataset demonstrate that our scheme can drastically decrease both computational and storage costs.

Enforcing authorizations while protecting access confidentiality1

Cloud computing is the reference paradigm to provide data storage and management in a convenient and scalable manner. However, moving data to the cloud raises several issues, including the confidentiality of data and of accesses that are no more under the direct control of the data owner. The shuffle index has been proposed as a solution for addressing these issues when data are stored at an external third party. In this paper, we extend the shuffle index with support for access control, that is, for enforcing authorizations on data. Our approach is based on the use of selective encryption and on the organization of data and authorizations in two shuffle indexes. Owners regulate access to their data through authorizations that allow different users to access different portions of the data, while, at the same time, the confidentiality of accesses is guaranteed. The proposed approach also supports update operations over the outsourced data collection (i.e., insertion, removal, and update) as well as of the access control policy (i.e., grant and revoke). Also, our approach protects the nature of each access operation, making revoke operations and resource removal operations indistinguishable by the storing server and/or observing users.

VD-IT2, Virtual Disk Cloning on Disk Arrays Using a Type-2 Fuzzy Controller

Disk arrays provide data storage by combining sets of disks into one or more virtual disks (VDs) utilizing specialized control algorithms. A VD is a partition of such combined storage capacity perceived by the user as a physical disk. VD cloning is a data protection technique that copies the data from one VD to another. A typical problem with VD cloning is that it delays user reads and writes, i.e., increases response times. This paper presents VD- Interval Type 2 (IT2), an effective IT2 fuzzy logic control (IT2 FLC) approach to VD cloning that dramatically reduces the response time delay. The VD-IT2 cloning scheme is capable of balancing two adversely affecting processes: VD cloning and user read/write response times. This IT2 FLC-based approach regulates throughput of VD cloning with regards to the user request activity. The VD-IT2 solves the increased delay in user reads and write during cloning by adjusting the time interval between cloning requests. The contribution of this paper is two-fold. First, a novel formula for planning of data backups is presented. The data backup formula predicts the fraction of replicated data blocks in a combined (clone and snap) replication. Second, a novel IT2 FLC scheme reduces response time of user reads/writes in half. The VD-IT2 was tested on an Itanium workstation with 120 disks and proved 50% reduction of user latencies within a short period of time (high response time of 60 ms was reduced to half, within 30 s only), on an average basis.

Minimum-Cost Cloud Storage Service Across Multiple Cloud Providers

Many cloud service providers (CSPs) provide data storage services with datacenters distributed worldwide. These datacenters provide different get/put latencies and unit prices for resource utilization and reservation. Thus, when selecting different CSPs’ datacenters, cloud customers of globally distributed applications (e.g., online social networks) face two challenges: 1) how to allocate data to worldwide datacenters to satisfy application service level objective (SLO) requirements, including both data retrieval latency and availability and2) how to allocate data and reserve resources in datacenters belonging to different CSPs to minimize the payment cost. To handle these challenges, we first model the cost minimization problem under SLO constraints using the integer programming. Due to its NP-hardness, we then introduce our heuristic solution, including a dominant-cost-based data allocation algorithm and an optimal resource reservation algorithm. We further propose three enhancement methods to reduce the payment cost and service latency: 1) coefficient-based data reallocation; 2) multicast-based data transferring; and 3) request redirection-based congestion control. We finally introduce an infrastructure to enable the conduction of the algorithms. Our trace-driven experiments on a supercomputing cluster and on real clouds (i.e., Amazon S3, Windows Azure Storage, and Google Cloud Storage) show the effectiveness of our algorithms for SLO guaranteed services and customer cost minimization.

Data verification tasks scheduling based on dynamic resource allocation in mobile big data storage

Mobile cloud storage services bring convenient data accessing and sharing for mobile users while their data are outsourced into the remote cloud data storage space. They also pose the potential threat of data being deleted intentionally, data loss or corruption being held back by the data storage provider. Currently, the data integrity verification being executed by trusted public third-party verifiers in remote data storage has already become one of the primary technologies to solve this problem. However, the technology neglects the waste of resource caused by the invalid verification due to the data verifiers’ limited capability and unlimited verification tasks. The authors propose a task scheduling algorithm of data verification based on dynamic resource allocation to reasonably evaluate the number of accepted tasks by the verifiers, and optimize the execution time of tasks and the amount of data storage provider’s rented resource. The simulation results show that the proposed algorithm can exert the efficiency of the data verifiers’ resource to the utmost extent by minimizing the task loss rate and the wastage of rented resource, i.e., both them achieve to 0.

A Survey on various Load balancing Algorithms in Cloud Computing

In modern era cloud computing has bloomed into the greatest platform which provides storage of data at very low cost and is also available over the internet without any time constraint. But cloud computing also has some critical issues such as security, load balancing and fault tolerance ability. In this paper, the focus is on various load balancing approaches. Load balancing can be defined as the process of smart distribution of load throughout the different nodes of a server so as to attain optimal resource utilization. The process of Load balancing is required when a single node is overloaded, in such a situation; the process of balancing the load is undertaken which evenly distributes the load to the other ideal nodes. The load balancing algorithms have broadly been classified into Static load balancing and Dynamic load balancing. In this paper a survey of various load balancing algorithms are presented.

Personal health records in the Netherlands: potential user preferences quantified by a discrete choice experiment.

To identify groups of potential users based on their preferences for characteristics of personal health records (PHRs) and to estimate potential PHR uptake. We performed a discrete choice experiment, which consisted of 12 choice scenarios, each comprising 2 hypothetical PHR alternatives and an opt-out. The alternatives differed based on 5 characteristics. The survey was administered to Internet panel members of the Dutch Federation of Patients and Consumer Organizations. We used latent class models to analyze the data. A total of 1,443 potential PHR users completed the discrete choice experiment. We identified 3 latent classes: "refusers" (class probability 43%), "eager adopters" (37%), and "reluctant adopters" (20%). The predicted uptake for the reluctant adopters ranged from 4% in the case of a PHR with the worst attribute levels to 68% in the best case. Those with 1 or more chronic diseases were significantly more likely to belong to the eager adopter class. The data storage provider was the most decisive aspect for the eager and reluctant adopters, while cost was most decisive for the refusers. Across all classes, health care providers and independent organizations were the most preferred data storage providers. We identified 3 groups, of which 1 group (more than one-third of potential PHR users) indicated great interest in a PHR irrespective of PHR characteristics. Policymakers who aim to expand the use of PHRs will be most successful when health care providers and health facilities or independent organizations store PHR data while refraining from including market parties.

Data Protection Techniques for Building Trust in Cloud Computing

Cloud computing has played much important role in comparison to other fields of IT, in providing Data storage, Data security, Quality of Services (QoS) etc. In the last few years, it had emerged and evolved so quickly due to its number of facilities and advantages to the organizations and end users. Many data security factors have also increased due to this fast evolution of cloud in the IT industry. Therefore several security models and trust establishing techniques have been deployed and are been in execution for providing more security to the data, especially the sensitive data. Despite of that much security, many of the models/techniques lacks in one or more security threat measures. In this paper a new model have been designed and proposed which introduces Security Aware Cloud. First the trust of the user or organization is established successfully on cloud than the security to the data is granted through privacy and encryption module. Level of quality of service and security are achieved under the Contract Trust layer while the Authentication and Key Management are covered under Internal Trust layer. For critical data privacy and encryption, Homomorphism mechanism is used. By the use of proposed trust and security model, we can enhance Return on Investment factor in the cloud for the data security and service provided by it.

Resolving privacy-preserving relationships over outsourced encrypted data storages

Due to the numerous advantages in terms of cost reduction, usability, and flexibility, today we are witnessing the adoption of solutions where individuals and enterprises prefer to outsource (part of) their private information or assets for processing to third parties. Yet, such adoption will not become a complete success unless outsourced data storages reliably guarantee the privacy of sensitive information. With this aim in mind, some data storage providers offer the possibility of encrypting assets, achieving a remarkable degree of privacy, but at the expense of usability. At best, advanced cryptographic primitives can be directly implemented over the encrypted data to allow its owners to perform certain operations, such as keyword-based searches, on the side of the data storages. The paper at hand proposes a novel approach based on fully homomorphic encryption to correlate encrypted pieces of data in outsourced data storages. The goal was to enrich searchable encryption solutions by transparently adding related keywords to a given query, yet preventing the data storages to know the outsourced information, the received query, the resulting response, or the relationship between queries and responses. The conducted experiments show that nowadays, the main bottleneck resides in the inefficiency of the existing fully homomorphic encryption algorithms. Nevertheless, our proposal is not tied to any particular algorithm, thereby allowing users to select the most efficient in terms of computing time.

Research of Security Strategy of Cloud Storage

Cloud storage is a new extension and developed concept on the base of the cloud computing, aiming at providing data storage and transaction access service. On the base of the analysis of the basic concept of cloud storage, make the research and analysis on the safety of cloud storage. For the unauthorized access, data leakage, data access breakdown and other security problems, poses some security policies, including a challenge-response cloud storage identity authentication, encryption storage based on key associated with the username and a fast data recovery service which is parallel with data access. Hope cloud storage can provide a service of confidential, reliable and authentication.

A dual-direction technique for fast file downloads with dynamic load balancing in the Cloud

File downloads make up a large percentage of the Internet traffic to satisfy various clients using distributed environments for their Cloud, Grid and Internet applications. In particular, the Cloud has become a popular data storage provider and users (individuals and corporates) are relying heavily on it to keep their data. Furthermore, most cloud data servers replicate their data storage infrastructures and servers at various sites to meet the overall high demands of their clients and increase availability. However, most of them do not use that replication to enhance the download performance per client. To make use of this redundancy and to enhance the download speed, we introduce a fast and efficient concurrent technique for downloading large files from replicated Cloud data servers and traditional FTP servers as well. The technique, DDFTP utilizes the availability of replicated files on distributed servers to enhance file download times through concurrent downloads of file blocks from opposite directions in the files. DDFTP does not require coordination between the servers and relies on the in-order and reliability features of TCP to provide fast file downloads. In addition, DDFTP offers efficient load balancing among multiple heterogeneous data servers with minimal overhead. As a result, we can maximize network utilization while maintaining efficient load balancing on dynamic environments where resources, current loads and operational properties vary dynamically. We implemented and evaluated DDFTP and experimentally demonstrated considerable performance gains for file downloads compared to other concurrent/parallel file/data download models.

Enhancing Privacy in Cloud Service Provider Using Cryptographic Algorithm

Cloud Computing provides the way to share the distributed resources and services that belong to different organizations and sites. Even though it having benefits, but it posses security problems. All types of users who require the secure transmission or storage of data in network. While, the data transmission on the internet or over any networks are vulnerable to the hacker attacks. We are in great need of encrypting the owner data. Our paper aims to give the cloud data storage models and data security in cloud computing system. Here we propose a efficient method for providing data storage security in cloud computing using RSA algorithm. In this algorithm some important security services included such as key generation, encryption and decryption that are provided in cloud computing system.

A middleware approach for outsourcing data securely

Businesses that provide data storage facilities on the internet (IDP) have exploded recently. Such businesses provide the following benefits to end users: a) anytime, anywhere access to data; b) low cost; and c) good quality of service. Examples of data storage providers include Amazon S3 service, Windows SkyDrive, Nirvarnix, etc.Users face two challenges in utilizing the storage infrastructures of the IDPs: a) Heterogeneity: Different IDPs provide different interfaces to application developers to store and fetch data with them due to lack of accepted standards; and b) Security: Data outsourced to IDPs is vulnerable to attacks from the internet thieves and from malicious employees of IDPs.In this paper, we present the design of iDataGuard, which is a client side interoperable security middleware that adapts to the heterogeneity of interfaces of IDPs and enforces security constraints on outsourced data. This significantly simplifies the effort for application development. To combat heterogeneity, iDataGuard incorporates an abstract service model that can be easily customized to individual IDPs. To address the security challenges, iDataGuard supports a security model that protects the confidentiality and integrity of outsourced data. We propose a novel indexing technique that allows search on the encrypted data stored at the IDPs. We illustrate the feasibility/efficacy of iDataGuard by implementing the middleware and executing it on two of the popular IDPs, Amazon S3 service and Gmail.com.

An Approach to Data Confidentiality Protection in Cloud Environments

In current cloud computing systems, because users’ data is stored and processed by computing systems managed and operated by various service providers, users are concerned with the risks of unauthorized usage of their sensitive data by various entities, including service providers. The current cloud computing systems protect users’ data confidentiality from all entities, except service providers. In this paper, an approach is presented for improving the protection of users’ data confidentiality in cloud computing systems from all entities, including service providers. The authors’ approach has the following features: (1) separation of cloud application providers, data processing service providers and data storage providers, (2) anonymization of users’ identities, (3) grouping cloud application components and distributing their execution to distinct cloud infrastructures of data processing service providers, and (4) use of data obfuscation and cryptography for protecting the sensitive data from unauthorized access by all entities, including service providers. The proposed approach ensures that users’ sensitive data can be protected from their service providers even if the users do not have full cooperation from their service providers.

MobiHealthcare System: Body Sensor Network Based M-Health System for Healthcare Application

M-health, which is known as the practice of medical and public health supported by mobile devices such as mobile phones and PDAs for delivering medical and healthcare services, is currently being heavily developed to keep pace with the continuously rising demand for personalized healthcare. To this end, the MobiHealthcare system, which provides a personalized healthcare based on body sensor network, is developed. The system includes various body sensors to collect physiological signals specifically for different requirements, a cell phone to facilitate the joint processing of spatially and temporally collected medical data from different parts of the body for resource optimization and systematic health monitoring, a server cluster with great data storage capacity, powerful analysis capabilities to provide data storage, data mining and visualization. Compared with existing M-Health system, the MobiHealthcare system is characteristics of low coupling and powerful parallel computing capabilities. Various healthcare applications have been implemented in the proposed system to demonstrate its effectiveness in providing a powerful platform.

The MUNI Photometric Archive

AbstractIn the 1990s of the last century, CCD cameras became more reachable. Due to many advantages of CCD cameras, astronomers began using them as the primary detector for photometry of stellar objects. A typical observatory, which operates one telescope at a time, obtained 0.5 TB of raw data during two decades, that means one million about 500 kB-sized files. There are several observatories in the Czech Republic and Slovakia (taking into account all scientific, public as well as private ones). A rough estimate of the total amount of this photometric data is 10 TB, which could be a very interesting source of observational data. Unfortunately, these data are not available online. These data are stored in observatory archives in arbitrary format. Often it is not even possible to find requested data. We have decided to change this state by establishing a common archive of raw photometric data, which would be available online together with tools for searching, listing etc. We already defined the data format, file and directory structure of our archive. We developed sophisticated tools for archive maintenance as well. Our goal is to provide data storage with simple and straightforward access and we are ready to interconnect with the VO right after the IVOA Photometry Data Model will be released.

Zero Data Remnance Proof in Cloud Storage

In a cloud environment where Storage is offered as a service, a client stores his data with a provider and pays as per the usage. Once the contract ends, the client, as the data owner, may like to see, due to privacy reasons and otherwise that the data is properly shredded in the provider storage. In this paper we propose a scheme for Zero Data Remnance Proof (ZDRP) – a comprehensive proof given by the cloud data storage provider as regards to zero data remnance post the SLA period. In absence of such shredding the provider can consume the data to his benefit without coming in legal framework. The proof of data destruction can be achieved together by clauses in the SLA and a comprehensive destruction-verifier algorithm. The implementation of this can be achieved by appropriate modification of the data updation mechanisms provided by open source cloud providers.

Development of a Kidney TeleUltrasound Consultation System

This paper presents the development of kidney TeleUltrasound consultation system. The TeleUltrasound system provides an innovative design that aids the acquisition, archiving, and dissemination of medical data and information over the internet as its backbone. The system provides data sharing to allow remote collaboration, viewing, consultation, and diagnosis of medical data. The design is layered upon a standard known as Digital Imaging and Communication in Medicine (DICOM). The DICOM standard defines protocols for exchanging medical images and their associated data. The TeleUltrasound system is an integrated solution for retrieving, processing, and archiving images and providing data storage management using Structured Query Language (SQL) database. Creating a web-based interface is an additional advantage to achieve global accessibility of experts that will widely open the opportunity of greater examination and multiple consultations. This system is equipped with a high level of data security and its performance has been tested with white, black, and gray box techniques. And the result was satisfactory. The overall system has been evaluated by several radiologists in Malaysia, United Arab Emirates, and Sudan, the result is shown within this paper.