Commercial and Distributed Storage Systems

2013 ◽  
pp. 1-8 ◽  
Author(s):  
Spyridon V. Gogouvitis ◽  
Athanasios Voulodimos ◽  
Dimosthenis Kyriazis
Keyword(s):  
Data Storage ◽  
Cloud Storage ◽  
Storage Systems ◽  
Distributed Storage ◽  
End Users ◽  
Digital Environment ◽  
Storage Solutions ◽  
Distributed Storage Systems ◽  
Promising Solution ◽  
New Generation

Distributed storage systems are becoming the method of data storage for the new generation of applications, as it appears a promising solution to handle the immense volume of data produced in today’s rich and ubiquitous digital environment. In this chapter, the authors first present the requirements end users pose on Cloud Storage solutions. Then they compare some of the most prominent commercial distributed storage systems against these requirements. Lastly, the authors present the innovations the VISION Cloud project brings in the field of Storage Clouds.

Confidential Data Storage Systems for Wearable Platforms

2018 ◽  
pp. 65-83
Author(s):  
Mingzhong Wang ◽  
Don Kerr
Keyword(s):  
Data Storage ◽  
Flash Memory ◽  
Cloud Storage ◽  
Storage Systems ◽  
Storage System ◽  
Security And Privacy ◽  
Storage Solutions ◽  
Confidential Data ◽  
Wearable Products ◽  
Confidentiality Protection

With the features of mobility, reality augmentation, and context sensitivity, wearable devices are widely deployed into various domains. However, the sensitivity of collected data makes security and privacy protection one of the first priority in the advancement of wearable technologies. This chapter provides a study on encryption-based confidentiality protection for data storage systems in wearable platforms. The chapter first conducts a review to storage solutions in consumer wearable products and explores a two-tier, local flash memory and remote cloud storage, storage system in wearable platforms. Then encryption-based confidentiality protection and implementation methods for both flash memory and remote cloud storage are summarized. According to the interaction and integration of these two components, a categorization of confidential storage systems in wearable platforms is proposed. In addition, the benefits and selection criteria for each category are also discussed.

Confidential Data Storage Systems for Wearable Platforms

2016 ◽  
pp. 74-97
Author(s):  
Mingzhong Wang ◽  
Don Kerr
Keyword(s):  
Data Storage ◽  
Flash Memory ◽  
Cloud Storage ◽  
Storage Systems ◽  
Storage System ◽  
Security And Privacy ◽  
Storage Solutions ◽  
Confidential Data ◽  
Wearable Products ◽  
Confidentiality Protection

With the features of mobility, reality augmentation, and context sensitivity, wearable devices are widely deployed into various domains. However, the sensitivity of collected data makes security and privacy protection one of the first priority in the advancement of wearable technologies. This chapter provides a study on encryption-based confidentiality protection for data storage systems in wearable platforms. The chapter first conducts a review to storage solutions in consumer wearable products and explores a two-tier, local flash memory and remote cloud storage, storage system in wearable platforms. Then encryption-based confidentiality protection and implementation methods for both flash memory and remote cloud storage are summarized. According to the interaction and integration of these two components, a categorization of confidential storage systems in wearable platforms is proposed. In addition, the benefits and selection criteria for each category are also discussed.

scholarly journals PRELIMINARY STUDY ON APPLICATION OF MAX PLUS ALGEBRA IN DISTRIBUTED STORAGE SYSTEM THROUGH NETWORK CODING

2016 ◽  
Vol 4 (1) ◽  
Author(s):  
Agus Maman Abadi ◽  
Musthofa Musthofa ◽  
Emut Emut
Keyword(s):  
Network Coding ◽  
Data Storage ◽  
Algebraic Structure ◽  
Storage Systems ◽  
Distributed Storage ◽  
Storage System ◽  
Distributed Data Storage ◽  
Erasure Code ◽  
Distributed Storage Systems ◽  
Set Up

The increasing need in techniques of storing big data presents a new challenge. One way to address this challenge is the use of distributed storage systems. One strategy that implemented in distributed data storage systems is the use of Erasure Code which applied to network coding. The code used in this technique is based on the algebraic structure which is called as vector space. Some studies have also been carried out to create code that is based on other algebraic structures such as module.  In this study, we are going to try to set up a code based on the algebraic structure which is a generalization of the module that is semimodule by utilizing the max operations and sum operations at max plus algebra. The results of this study indicate that the max operation and the addition operation on max plus algebra cannot be used to establish a semimodule code, but by modifying the operation "+" as "min", we get a code based on semimodule. Keywords:   code, distributed storage systems, network coding, semimodule, max plus algebra

scholarly journals CERN Disk Storage Services: Report from last data taking, evolution and future outlook towards Exabyte-scale storage

2020 ◽  
Vol 245 ◽  
pp. 04038 ◽  
Author(s):  
Luca Mascetti ◽  
Maria Arsuaga Rios ◽  
Enrico Bocchi ◽  
Joao Calado Vicente ◽  
Belinda Chan Kwok Cheong ◽  
...  
Keyword(s):  
Data Storage ◽  
Cloud Storage ◽  
Large Scale ◽  
Storage Systems ◽  
Distributed Storage ◽  
General Purpose ◽  
Easy Access ◽  
It Use ◽  
File Storage ◽  
Block Storage

The CERN IT Storage group operates multiple distributed storage systems to support all CERN data storage requirements: the physics data generated by LHC and non-LHC experiments; object and file storage for infrastructure services; block storage for the CERN cloud system; filesystems for general use and specialized HPC clusters; content distribution filesystem for software distribution and condition databases; and sync&share cloud storage for end-user files. The total integrated capacity of these systems exceeds 0.6 Exabyte. Large-scale experiment data taking has been supported by EOS and CASTOR for the last 10+ years. Particular highlights for 2018 include the special HeavyIon run which was the last part of the LHC Run2 Programme: the IT storage systems sustained over 10GB/s to flawlessly collect and archive more than 13 PB of data in a single month. While the tape archival continues to be handled by CASTOR, the effort to migrate the current experiment workflows to the new CERN Tape Archive system (CTA) is underway. Ceph infrastructure has operated for more than 5 years to provide block storage to CERN IT private OpenStack cloud, a shared filesystem (CephFS) to HPC clusters and NFS storage to replace commercial Filers. S3 service was introduced in 2018, following increased user requirements for S3-compatible object storage from physics experiments and IT use-cases. Since its introduction in 2014N, CERNBox has become a ubiquitous cloud storage interface for all CERN user groups: physicists, engineers and administration. CERNBox provides easy access to multi-petabyte data stores from a multitude of mobile and desktop devices and all mainstream, modern operating systems (Linux, Windows, macOS, Android, iOS). CERNBox provides synchronized storage for end-user’s devices as well as easy sharing for individual users and e-groups. CERNBox has also become a storage platform to host online applications to process the data such as SWAN (Service for Web-based Analysis) as well as file editors such as Collabora Online, Only Office, Draw.IO and more. An increasing number of online applications in the Windows infrastructure uses CIFS/SMB access to CERNBox files. CVMFS provides software repositories for all experiments across the WLCG infrastructure and has recently been optimized to efficiently handle nightlybuilds. While AFS continues to provide general-purpose filesystem for internal CERN users, especially as $HOME login area on central computing infrastructure, the migration of project and web spaces has significantly advanced. In this paper, we report on the experiences from the last year of LHC RUN2 data taking and evolution of our services in the past year.. We will highlight upcoming changes and future improvements and challenges.

scholarly journals A survey on trade-off between storage and repair traffic in distributed storage systems

2018 ◽  
Vol 7 (2.8) ◽  
pp. 379
Author(s):  
D Sowmia ◽  
B Muruganantham
Keyword(s):  
Cloud Storage ◽  
Storage Systems ◽  
Distributed Storage ◽  
Large Data ◽  
Future Research ◽  
Access To Information ◽  
Storage Model ◽  
Distributed Storage Systems ◽  
Data Objects ◽  
Online Storage

Distributed storage systems give dependable access to information through excess spread over independently unreliable hubs. Application scenarios incorporate server farms, distributed capacity frameworks, and capacity in remote systems. This paper gives a study on the cloud storage model of networked online storage where data is stored in virtualized pools of storage which are generally hosted by third parties. Hosting companies operate large data centersand people who require their data to be encouraged buy or lease accumulating limit from them. The server cultivate overseers, outside of anyone's ability to see, virtualize the advantages according to the necessities of the customer and reveal them as limit pools, which the customers would themselves have the capacity to use to store records or data objects. . The data is stored across various locations, when the user wants to retrieve them, it could be done by any of the encryption methods. At last, in view of existing procedures, promising future research bearings are recommended.

Analysis of a Stochastic Model of Replication in Large Distributed Storage Systems

2017 ◽  
Vol 45 (1) ◽  
pp. 51-51
Author(s):  
Wen Sun ◽  
Véronique Simon ◽  
Sébastien Monnet ◽  
Philippe Robert ◽  
Pierre Sens
Keyword(s):  
Stochastic Model ◽  
Storage Systems ◽  
Distributed Storage ◽  
Distributed Storage Systems
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