OPTIMIZING THE STORAGE SPACE AND COST WITH RELIABILITY ASSURANCE BY REPLICA REDUCTION ON CLOUD STORAGE SYSTEM

Data storage is one of the significant cloud services available to the cloud users. Since the magnitude of information outsourced grows extremely high, there is a need of implementing data deduplication technique in the cloud storage space for efficient utilization. The cloud storage space supports all kind of digital data like text, audio, video and image. In the hash-based deduplication system, cryptographic hash value should be calculated for all data irrespective of its type and stored in the memory for future reference. Using these hash value only, duplicate copies can be identified. The problem in this existing scenario is size of the hash table. To find a duplicate copy, all the hash values should be checked in the worst case irrespective of its data type. At the same time, all kind of digital data does not suit with same structure of hash table. In this study we proposed an approach to have multiple hash tables for different digital data. By having dedicated hash table for each digital data type will improve the searching time of duplicate data.

Download Full-text

Performance and Time Improvement of LT Codes-based Cloud Storage

10.21203/rs.3.rs-598840/v1 ◽

2021 ◽

Author(s):

Nastaran Chakani ◽

Seyed Masoud Mirrezaei ◽

Ghosheh Abed Hodtani

Keyword(s):

Degree Distribution ◽

Cloud Storage ◽

Storage System ◽

Data Retrieval ◽

Storage Space ◽

Improve Performance ◽

Lt Codes ◽

Storage Performance ◽

Decoding Efficiency ◽

Cloud Storage Services

Abstract Outsourcing data on the cloud storage services has already attracted great attention due to prospect of rapid data growth and storing efficiencies for customers. The coding-based cloud storage approach can offer more reliable and faster solution with less storage space in comparison with replication-based cloud storage. LT codes as a famous member of rateless codes family can improve performance of storage systems utilizing good degree distributions. Since degree distribution plays key role in LT codes performance, recently introduced Poisson Robust Soliton Distribution (PRSD) and Combined Poisson Robust Soliton Distribution (CPRSD) motivate us to investigate LT codes-based cloud storage system. So, we exploit LT codes with new degree distributions in order to provide lower average degree and higher decoding efficiency, specifically when receiving fewer encoding symbols, comparing with popular degree distribution, Robust Soliton Distribution (RSD). In this paper, we show that proposed cloud storage outperforms traditional ones in terms of storage space and robustness encountering unavailability of encoding symbols, due to compatible properties of PRSD and CPRSD with cloud storage essence. Furthermore, modified decoding process based on required encoding symbols behavior is presented to reduce data retrieval time. Numerical results confirm improvement of cloud storage performance.

Download Full-text

Based on Cloud-Technology Data Storage Security

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.556-562.6179 ◽

2014 ◽

Vol 556-562 ◽

pp. 6179-6183

Author(s):

Zhi Gang Chai ◽

Ming Zhao ◽

Xiao Yu

Keyword(s):

Cloud Computing ◽

Data Storage ◽

Cloud Storage ◽

Rapid Development ◽

Storage System ◽

Storage Space ◽

It Industry ◽

Storage Security ◽

The Cost ◽

Space Requirements

With the rapid development of information technology, the extensive use of cloud computing promotes technological change in the IT industry. The use of cloud storage industry is also one solution to the problem of an amount of data storing, which is traditionally large, and unimaginably redundant. The use of cloud computing in the storage system connects the user's data with network clients via the Internet. That is to say, it not only solves a lot of data storage space requirements in request, but also greatly reduces the cost of the storage system. But in the application of cloud storage, there are also many problems to be solved, even to some extent which has hindered the development of cloud storage. Among these issues, the most concerning one is cloud storage security. The following passages discuss the problem and propose a solution to it.

Download Full-text

Machine learning-driven automatic storage space recommendation for object-based cloud storage system

Complex & Intelligent Systems ◽

10.1007/s40747-021-00517-4 ◽

2021 ◽

Author(s):

Anindita Sarkar Mondal ◽

Anirban Mukhopadhyay ◽

Samiran Chattopadhyay

Keyword(s):

Machine Learning ◽

Feature Selection ◽

Big Data ◽

Cloud Storage ◽

Recommendation System ◽

Storage System ◽

Sparse Learning ◽

Storage Space ◽

Object Based ◽

Selection Algorithms

AbstractAn object-based cloud storage system is a storage platform where big data is managed through the internet and data is considered as an object. A smart storage system should be able to handle the big data variety property by recommending the storage space for each data type automatically. Machine learning can help make a storage system automatic. This article proposes a classification engine framework for this purpose by utilizing a machine learning strategy. A feature selection approach wrapped with a classifier is proposed to automatically predict the proper storage space for the incoming big data. It helps build an automatic storage space recommendation system for an object-based cloud storage platform. To find out a suitable combination of feature selection algorithms and classifiers for the proposed classification engine, a comparative study of different supervised feature selection algorithms (i.e., Fisher score, F-score, Lll21) from three categories (similarity, statistical, sparse learning) associated with various classifiers (i.e., SVM, K-NN, Neural Network) is performed. We illustrate our study using RSoS system as it provides a cloud storage platform for the healthcare data as experimental big data by considering its variety property. The experiments confirm that Lll21 feature selection combined with K-NN classifier provides better performance than the others.

Download Full-text

DeyPoS-homomorphism authenticated tree (HAT) for multi-user locality in cloud storage

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i2.31.13427 ◽

2018 ◽

Vol 7 (2.31) ◽

pp. 141

Author(s):

M Muthu Selvam ◽

K Mariappan ◽

G V. Sriramakrishnan ◽

G Suseendran

Keyword(s):

Cloud Storage ◽

Storage System ◽

Cloud System ◽

Storage Space ◽

Research Article ◽

Cloud Server ◽

Dynamic Proofs ◽

The Creation ◽

Client System ◽

The Way

The technology PoS (Dynamic Proof of storage) is a cryptographic primordial allows a abuser to test the reliability of subcontracted documents and effectively replace documents in the cloud storage system. Despite the fact that investigators have projected several dynamic proofs of storage designs in distinct client settings, hassle in the multi-client settings have now not been examined adequately. In sensible multi-client cloud server storage space wishes a cozy client part cross client system of deduplication, it permits client toward bypass importing manner as well as gain instantly the rights of the files, while different vendors of the same files hold uploaded to the cloud system server. In the direction of familiarity not a bit of prevailing dynamic Proof of Storages can guide this system. This research article we are bring the model of dynamic proof of storage in deduplicatable system and endorse a green creation known as Dedupicatable Dynamic Proof of Storage (DeyPoS), on the way to attain DeyPoS and comfy reduplication concurrently in cross client. Taking into account confront of formation assortment and personal blot creation make use of a new tool called HAT (Homomorphic Authenticated Tree). Also verify precautions of creation and the hypothetical, investigational outcomes shows that the creation is green in use.

Download Full-text

A Multi-Server Erasure Code Algorithm Based on the Degree of Restriction

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.717.789 ◽

2013 ◽

Vol 717 ◽

pp. 789-793

Author(s):

Jun Wei Ge ◽

Ai Hua Miao ◽

Yi Qiu Fang

Keyword(s):

System Performance ◽

Cloud Storage ◽

Storage System ◽

Erasure Codes ◽

Storage Space ◽

High Recovery ◽

Erasure Code ◽

Code Algorithm ◽

Cloud Storage Environment ◽

Multi Server

Erasure codes received extensive attention in the cloud storage system because of its effective on saving storage space,However, due to the high recovery-overhead of erasure code, its application has been limited in these storage systems.For these problems,in this paper,we presents A multi-server Erasure code algorithm based on the degree of restriction to reduce the recovery-overhead from the restriction of date and parity's degree,and enhance the system performance to a certain extent ,ensure the reliability of the data of the cloud storage environment.

Download Full-text