• Journal of Korea Multimedia Society
• /
• v.15 no.8
• /
• pp.1048-1058
• /
• 2012

This paper proposes the DDMPF(Distributed Data Management Protocol using FAT) which prevents data loss and keeps the security of self-organized storages by comprising a client, a storage server, and a verification server in clouding environment. The DDMPF builds a self-organized storage server, solves data loss by decentralizing the partitioned data in it in contrast to the centralized problem and the data loss caused by the storage server problems of existing clouding storages, and improves the efficiency of distributed data management with FAT(File Allocation Table). And, the DDMPF improves the reliability of data by a verification server's verifying the data integrity of a storage server, and strengthens the security in double encryption with a client's private key and the system's master key using EC-DH algorithm. Additionally, the DDMPF limits the number of verification servers and detects the flooding attack by setting the TS(Time Stamp) for a verification request message and the replay attack by using the nonce value generated newly, whenever the verification is requested.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.6
• /
• pp.2606-2626
• /
• 2016

This article investigates the distributed data storage problem in the space information network (SIN) using distributed fountain codes. Since space nodes in the SIN are resource-limited, in order to reduce energy consumption while improving the storage reliability, an efficient distributed storage based on fountain codes and probabilistic broadcasting (DSFPB) strategy is proposed. In the proposed strategy, source packets are disseminated among the entire network according to probabilistic broadcasting (PBcast), and the final degree distribution is close to the desired robust soliton distribution (RSD), this is benefited from the appropriate packets encoding procedure of the proposed strategy. As presented by the analysis and simulations, the total cost of data dissemination is greatly reduced compared with existing representative strategies, while improving the decoding performance.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.12
• /
• pp.4508-4530
• /
• 2021

Today distributed data storage service are being widely used. However lack of proper means of security makes the user data vulnerable. In this work, we propose a Randomized Block Size (RBS) model for secure data storage in distributed environments. The model work with multifold block sizes encrypted with the Chinese Remainder Theorem-based RSA (C-RSA) technique for end-to-end security of multimedia data. The proposed RBS model has a key generation phase (KGP) for constructing asymmetric keys, and a rand generation phase (RGP) for applying optimal asymmetric encryption padding (OAEP) to the original message. The experimental results obtained with text and image files show that the post encryption file size is not much affected, and data is efficiently encrypted while storing at the distributed storage server (DSS). The parameters such as ciphertext size, encryption time, and throughput have been considered for performance evaluation, whereas statistical analysis like similarity measurement, correlation coefficient, histogram, and entropy analysis uses to check image pixels deviation. The number of pixels change rate (NPCR) and unified averaged changed intensity (UACI) were used to check the strength of the proposed encryption technique. The proposed model is robust with high resilience against eavesdropping, insider attack, and chosen-plaintext attack.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.9
• /
• pp.2134-2153
• /
• 2013

A network-coding-based scheme is proposed to improve the energy efficiency of distributed storage systems in WSNs (Wireless Sensor Networks). We mainly focus on two problems: firstly, consideration is given to effective distributed storage technology; secondly, we address how to effectively repair the data in failed storage nodes. For the first problem, we propose a method to obtain a sparse generator matrix to construct network codes, and this sparse generator matrix is proven to be the sparsest. Benefiting from this matrix, the energy consumption required to implement distributed storage is reduced. For the second problem, we designed a network-coding-based iterative repair method, which adequately utilizes the idea of re-encoding at intermediate nodes from network coding theory. Benefiting from the re-encoding, the energy consumption required by data repair is significantly reduced. Moreover, we provide an explicit lower bound of field size required by this scheme, which implies that it can work over a small field and the required computation overhead is very low. The simulation result verifies that the proposed scheme not only reduces the total energy consumption required to implement distributed storage system in WSNs, but also balances energy consumption of the networks.

• Smart Media Journal
• /
• v.4 no.3
• /
• pp.62-67
• /
• 2015

The trend keywords in ICT sector will be Big Data, Internet of Things, and Cloud Computing. The rear end to support those techniques requires a large-capacity storage technology of low-cost. Therefore, we proposed the prototype of low-cost and mass distributed storage system based on PC using open-source Ceph FS for SMB.

• Smart Media Journal
• /
• v.12 no.11
• /
• pp.145-153
• /
• 2023

In a P2P-based distributed storage system where peers frequently join and leave, it is essential to guarantee not only data availability but also playback quality comparable to that provided by local storage devices when playing back video files with real-time constraints. In addition, cloud storage services based on distributed storage systems provide each user with the functionality to share their files with other users, so when multiple users request playback of the same video file at the same time, all playback should be supported seamlessly in real time. Therefore, in this paper, we propose a scheme that process multiple simultaneous playback requests for each video file in real time as well as data availability in a P2P-based distributed storage system that supports file sharing. This scheme can support real-time simultaneous playback and efficiently use storage space by adjusting the amount of redundant data encoded through erasure coding according to the number of concurrent playback requests for each video file.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.9
• /
• pp.4063-4086
• /
• 2016

Cloud computing is a robust technology, which facilitate to resolve many parallel distributed computing issues in the modern Big Data environment. Hadoop is an ecosystem, which process large data-sets in distributed computing environment. The HDFS is a filesystem of Hadoop, which process data blocks to the cluster nodes. The data block placement has become a bottleneck to overall performance in a Hadoop cluster. The current placement policy assumes that, all Datanodes have equal computing capacity to process data blocks. This computing capacity includes availability of same storage media and same processing performances of a node. As a result, Hadoop cluster performance gets effected with unbalanced workloads, inefficient storage-tier, network traffic congestion and HDFS integrity issues. This paper proposes a storage-tier-aware Robust Data Placement (RDP) scheme, which systematically resolves unbalanced workloads, reduces network congestion to an optimal state, utilizes storage-tier in a useful manner and minimizes the HDFS integrity issues. The experimental results show that the proposed approach reduced unbalanced workload issue to 72%. Moreover, the presented approach resolve storage-tier compatibility problem to 81% by predicting storage for block jobs and improved overall data block placement by 78% through pre-calculated computing capacity allocations and execution of map files over respective Namenode and Datanodes.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.2
• /
• pp.85-91
• /
• 2014

Cloud storage system uses a distributed file system for storing and managing data. Traditional distributed file system makes a triplication of data in order to restore data loss in disk failure. However, enforcing data replication method increases storage utilization and causes extra I/O operations during replication process. In this paper, we propose a data replication method using erasure codes in cloud storage system to improve storage space efficiency and I/O performance. In particular, according to data access frequency, the proposed method can reduce the number of data replications but using erasure codes can keep the same data recovery performance. Experimental results show that proposed method improves performance in storage efficiency 40%, read throughput 11%, write throughput 10% better than HDFS does.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.8C
• /
• pp.670-679
• /
• 2012

The recent dissemination of cloud computing makes the amount of data storage to be increased and the cost of storing the data grow rapidly. Accordingly, data and service requests from users also increases the load on the cloud storage. There have been many works that tries to provide low-cost and high-performance schemes on distributed file systems. However, most of them have some weaknesses on performing parallel and random data accesses as well as data accesses of frequent small workloads. Recently, improving the performance of distributed file system based on caching technology is getting much attention. In this paper, we propose a CHPC(Cloud storage High-Performance Caching) framework, providing parallel caching, distributed caching, and proxy caching in distributed file systems. This study compares the proposed framework with existing cloud systems in regard to the reduction of the server's disk I/O, prevention of the server-side bottleneck, deduplication of the page caches in each client, and improvement of overall IOPS. As a results, we show some optimization possibilities on the cloud storage systems based on some evaluations and comparisons with other conventional methods.

• KIPS Transactions on Computer and Communication Systems
• /
• v.2 no.12
• /
• pp.569-576
• /
• 2013

Cloud computing has been receiving increasing attention recently. Despite this attention, security is the main problem that still needs to be addressed for cloud computing. In general, a cloud computing environment protects data by using distributed servers for data storage. When the amount of data is too high, however, different pieces of a secret key (if used) may be divided among hundreds of distributed servers. Thus, the management of a distributed server may be very difficult simply in terms of its authentication, encryption, and decryption processes, which incur vast overheads. In this paper, we proposed a efficiently data storage and recovery scheme using XOR and RAID in Hadoop environment.