Scalable Distributed Two-Layer Data Structures (SD2DS)

Author:

Sapiecha Krzysztof1,Lukawski Grzegorz1

Affiliation:

1. Department of Computer Science, Kielce University of Technology, Kielce, Poland

Abstract

Scalability and fault tolerance are important features of modern applications designed for the distributed, loosely-coupled computer systems. In the paper, two-layer scalable structures for storing data in a distributed RAM of a multicomputer (SD2DS) are introduced. A data unit of SD2DS (a component) is split into a header and a body. The header identifies the body and contains its address in a network. The headers are stored in the first layer of SD2DS, called the component file, while the bodies are stored in the second layer, called the component storage. Both layers are managed independently. Details of the management algorithms are given, along with SD2DS variant suitable for storing plain records of data. The SD2DS is compared to similar distributed structures and frameworks. Comparison considerations together with test results are also given. The results proved superiority of SD2DS over similar structures.

Publisher

IGI Global

Subject

Computer Networks and Communications,Hardware and Architecture

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Highly Scalable Distributed Architecture for NoSQL Datastore Supporting Strong Consistency;IEEE Access;2021

2. Hierarchical Clustering in Scalable Distributed Two-Layer Datastore for Big Data as a Service;2018 Sixth International Conference on Enterprise Systems (ES);2018-10

3. Scalable Distributed Datastore for Real-Time Cloud Computing;Advances in Intelligent Systems and Computing;2016-12-15

4. SD2DS-Based Datastore for Large Files;Advances in Intelligent Systems and Computing;2016-12-15

5. Scalable Distributed Two-Layer Block Based Datastore;Parallel Processing and Applied Mathematics;2016

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3