Replica Placement Algorithm for Highly Available Peer-to-Peer Storage Systems

2009 ◽  
Author(s):  
Gyuwon Song ◽  
Suhyun Kim ◽  
Daeil Seo
Keyword(s):  
Storage Systems ◽  
Peer To Peer ◽  
Replica Placement ◽  
Placement Algorithm

scholarly journals Optimized Data Replication for Small Files in Cloud Storage Systems

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Xiong Fu ◽  
Wenjie Liu ◽  
Yeliang Cang ◽  
Xiaojie Gong ◽  
Song Deng
Keyword(s):  
Cloud Storage ◽  
Storage Systems ◽  
Data Replication ◽  
Cloud Services ◽  
Cloud System ◽  
Replica Placement ◽  
File Storage ◽  
Block Based ◽  
Placement Algorithm ◽  
Small File

Cloud storage has become an important part of a cloud system nowadays. Most current cloud storage systems perform well for large files but they cannot manage small file storage appropriately. With the development of cloud services, more and more small files are emerging. Therefore, we propose an optimized data replication approach for small files in cloud storage systems. A small file merging algorithm and a block replica placement algorithm are involved in this approach. Small files are classified into four types according to their access frequencies. A number of small files will be merged into the same block based on which type they belong to. And the replica placement algorithm helps to improve the access efficiencies of small files in a cloud system. Related experiment results demonstrate that our proposed approach can effectively shorten the time spent reading and writing small files, and it performs better than the other two already known data replication algorithms: HAR and SequenceFile.

Efficient Data Maintenance Scheme for Peer-to-Peer Storage Systems

2009 ◽  
Vol 20 (1) ◽  
pp. 80-95 ◽  
Author(s):  
Zhi YANG ◽  
Jun ZHU ◽  
Ya-Fei DAI
Keyword(s):  
Storage Systems ◽  
Peer To Peer ◽  
Efficient Data ◽  
Data Maintenance

scholarly journals State Management for Cloud-Native Applications

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 423
Author(s):  
Márk Szalay ◽  
Péter Mátray ◽  
László Toka
Keyword(s):  
Large Scale ◽  
Distributed Databases ◽  
Access Time ◽  
Replica Placement ◽  
State Management ◽  
Placement Decisions ◽  
Dynamic Replication ◽  
Cloud Databases ◽  
Placement Algorithm ◽  
The One

The stateless cloud-native design improves the elasticity and reliability of applications running in the cloud. The design decouples the life-cycle of application states from that of application instances; states are written to and read from cloud databases, and deployed close to the application code to ensure low latency bounds on state access. However, the scalability of applications brings the well-known limitations of distributed databases, in which the states are stored. In this paper, we propose a full-fledged state layer that supports the stateless cloud application design. In order to minimize the inter-host communication due to state externalization, we propose, on the one hand, a system design jointly with a data placement algorithm that places functions’ states across the hosts of a data center. On the other hand, we design a dynamic replication module that decides the proper number of copies for each state to ensure a sweet spot in short state-access time and low network traffic. We evaluate the proposed methods across realistic scenarios. We show that our solution yields state-access delays close to the optimal, and ensures fast replica placement decisions in large-scale settings.

AN EXPLORATION OF NON-ASYMPTOTIC LOW-DENSITY, PARITY CHECK ERASURE CODES FOR WIDE-AREA STORAGE APPLICATIONS

2007 ◽  
Vol 17 (01) ◽  
pp. 103-123 ◽  
Author(s):  
JAMES S. PLANK ◽  
MICHAEL G. THOMASON
Keyword(s):  
Storage Systems ◽  
Distributed Storage ◽  
Ldpc Codes ◽  
Peer To Peer ◽  
Erasure Codes ◽  
Low Density ◽  
Parity Check ◽  
Finite Systems ◽  
Low Density Parity Check ◽  
Distributed Storage Systems

As peer-to-peer and widely distributed storage systems proliferate, the need to perform efficient erasure coding, instead of replication, is crucial to performance and efficiency. Low-Density Parity-Check (LDPC) codes have arisen as alternatives to standard erasure codes, such as Reed-Solomon codes, trading off vastly improved decoding performance for inefficiencies in the amount of data that must be acquired to perform decoding. The scores of papers written on LDPC codes typically analyze their collective and asymptotic behavior. Unfortunately, their practical application requires the generation and analysis of individual codes for finite systems. This paper attempts to illuminate the practical considerations of LDPC codes for peer-to-peer and distributed storage systems. The three main types of LDPC codes are detailed, and a huge variety of codes are generated, then analyzed using simulation. This analysis focuses on the performance of individual codes for finite systems, and addresses several important heretofore unanswered questions about employing LDPC codes in real-world systems.

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