Performance Measurement Technique of Cloud Storage System

2013 ◽  
Vol 760-762 ◽  
pp. 1197-1201
Author(s):  
Qin Lu He ◽  
Zhan Huai Li ◽  
Le Xiao Wang ◽  
Hui Feng Wang ◽  
Jian Sun
Keyword(s):  
Cloud Storage ◽  
File System ◽  
Storage System ◽  
File Systems ◽  
Test Methods ◽  
Theory Analysis ◽  
Network File System ◽  
Cloud Storage Environment ◽  
System File ◽  
Reasonable Test

Researches on technologies about testing aggregate bandwidth of file systems in cloud storage systems. Through the memory file system, network file system, parallel file system theory analysis, according to the cloud storage system polymerization bandwidth and concept, developed to cloud storage environment file system polymerization bandwidth test software called FSPoly. In this paper, use FSpoly to luster file system testing, find reasonable test methods, and then evaluations latest development in cloud storage system file system performance by using FSPoly.

Data Consistency Research of the Cloud Storage Environment Based on P2P Technology

2013 ◽  
Vol 380-384 ◽  
pp. 2589-2592
Author(s):  
Jun Wei Ge ◽  
Feng Yang ◽  
Yi Qiu Fang
Keyword(s):  
Cloud Storage ◽  
High Performance ◽  
Storage System ◽  
Model Systems ◽  
Data Consistency ◽  
Service Reliability ◽  
Cloud Storage Environment ◽  
P2p Technology ◽  
Server Architecture

Many of the characteristics of P2P technology such as decentralization, scalability, robustness, high performance and load balancing are in line with the cloud storage design requirements. In this article, it proposesd a cloud storage model based on P2P technology. This model uses multivariate data server architecture, which can effectively solve the bottleneck problem of centralized cloud storage system. Thereby increasing the cloud storage system performance and the quality of cloud storage services, enhance service reliability. In this article, through researching data consistency algorithm named Paxos and the model systems metadata consistency problem, we improve and optimize Basic Paxos making it applied in the model system.

Data Storage Technology and its Development Based on Cloud Computing

2013 ◽  
Vol 756-759 ◽  
pp. 1275-1279
Author(s):  
Lin Na Huang ◽  
Feng Hua Liu
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Cloud Storage ◽  
High Performance ◽  
File System ◽  
Storage System ◽  
Distributed File System ◽  
Cloud Data ◽  
Storage Technology ◽  
Cloud Data Storage

Cloud storage of high performance is the basic condition for cloud computing. This article introduces the concept and advantage of cloud storage, discusses the infrastructure of cloud storage system as well as the architecture of cloud data storage, researches the details about the design of Distributed File System within cloud data storage, at the same time, puts forward different developing strategies for the enterprises according to the different roles that the enterprises are acting as during the developing process of cloud computing.

scholarly journals An Approach for Evaluating and Mitigating Intra-Application I/O Performance Variability Over Parallel File Systems

2019 ◽  
Author(s):  
Eduardo Inacio ◽  
Mario Antonio Dantas
Keyword(s):  
Load Distribution ◽  
Large Scale ◽  
File System ◽  
Storage System ◽  
Research Work ◽  
File Systems ◽  
Distributed Applications ◽  
Evaluation Tool ◽  
Performance Variability ◽  
Parallel File

To meet ever increasing capacity and performance requirements of emerging data-intensive applications, highly distributed and multilayered back-end storage systems have been employed in large-scale high performance computing (HPC) environments. A main component of these storage infrastructures is the parallel file system (PFS), a especially designed file system for absorbing bulk data transfers from applications with thousands of concurrent processes. Load distribution on PFS data servers compose a major source of intra-application input/output (I/O) performance variability. Albeit mitigating variability is desirable, as it is known to harm application-perceived performance, understanding and dealing with I/O performance variability in such complex environments remains a challenging task. In this research, a differentiated approach for evaluating and mitigating intra-application I/O performance variability over PFSs is proposed. More specifically, from the evaluation perspective, a comprehensive approach combining complementary methods is proposed. An analytical model proposal, named DTSMaxLoad, provides estimates for the maximum load in a PFS data server. To complement DTSMaxLoad, modeling conditions and mechanisms hard to represent analytically, the Parallel I/O and Storage System (PIOSS) simulation model was proposed. Finally, for experimental evaluation over real environments, a flexible and distributed I/O performance evaluation tool, coined as IOR-Extended (IORE), was proposed. Furthermore, a high-level file distribution approach for PFSs, called N-N Round-Robin (N2R2), was proposed focusing on mitigating I/O performance variability for distributed applications where each process accesses an individual and independent file. An extensive experimental effort, including measurements on real environments, was conducted in this research work for evaluating each of the proposed approaches. In summary, this evaluation indicated both DTSMaxLoad and PIOSS modeling proposals can represent load distribution behavior on PFSs with significant fidelity. Moreover, results demonstrated N2R2 successfully reduced intra-application I/O performance variability for 270 distinct experimental scenarios, which, ultimately, translated into overall application I/O performance Improvements.

Research of Scalability Model Based on Cloud Storage System

2011 ◽  
Vol 130-134 ◽  
pp. 3054-3057
Author(s):  
Jun Wei Ge ◽  
Yong Long Deng ◽  
Yi Qiu Fang
Keyword(s):  
Cloud Storage ◽  
Evaluation Model ◽  
Storage System ◽  
Evaluation Methods ◽  
Model Based ◽  
Cloud Storage Environment ◽  
And Storage

Scalability is one of the most important indicators to for performance of cloud storage system. In this paper, firstly, we pointed out limitations of three classical scalability evaluation methods with conditions of iso-speed, iso-efficiency and iso-ratio of parallel overhead to computation, when describing scalability. Then, we proposed a new scalability evaluation model which was suitable for cloud storage environment and named as EP scalability model. The EP scalability model directly reflected the performance of cloud storage system when the system scale and storage tasks expand.

scholarly journals Performance Evaluation of NVMe-over-TCP Using Journaling File Systems in International WAN

Electronics ◽  
2021 ◽  
Vol 10 (20) ◽  
pp. 2486
Author(s):  
Se-young Yu
Keyword(s):  
File System ◽  
Data Transfer ◽  
Storage System ◽  
File Systems ◽  
Data Access ◽  
Streaming Data ◽  
Fine Tuning ◽  
Long Distance ◽  
Data Movement ◽  
Remote Data

Distributing Big Data for science is pushing the capabilities of networks and computing systems. However, the fundamental concept of copying data from one machine to another has not been challenged in collaborative science. As recent storage system development uses modern fabrics to provide faster remote data access with lower overhead, traditional data movement using Data Transfer Nodes must cope with the paradigm shift from a store-and-forward model to streaming data with direct storage access over the networks. This study evaluates NVMe-over-TCP (NVMe-TCP) in a long-distance network using different file systems and configurations to characterize remote NVMe file system access performance in MAN and WAN data moving scenarios. We found that NVMe-TCP is more suitable for remote data read than remote data write over the networks, and using RAID0 can significantly improve performance in a long-distance network. Additionally, a fine-tuning file system can improve remote write performance in DTNs with a long-distance network.

The Strategy of Ontology-Based Semantic Replica in Cloud Storage

2013 ◽  
Vol 347-350 ◽  
pp. 2898-2904
Author(s):  
Shun Yan Wang ◽  
Hai Tao Zhou ◽  
Jun Wang ◽  
Fang Fang Cao
Keyword(s):  
Cloud Computing ◽  
Cloud Storage ◽  
File System ◽  
File Systems ◽  
Replica Allocation ◽  
Low Load ◽  
Copy Strategy

With the development of cloud computing, cloud storage distributed the endless file system,but not a better copy strategy compatible with various file systems.This paper proposed ontology-based metadata replica which make different file systems mutual fusion ,and give a policy of replica allocation of low-load access .

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