A Customer Experience-Based Cost Minimization Strategy of Storing Data in Cloud Computing

WANG Ning; YANG Yang; MENG Kun; CHEN Yu; WANG Lei; JI Qing

doi:10.3969/j.issn.0372-2112.2014.01.004

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A Customer Experience-Based Cost Minimization Strategy of Storing Data in Cloud Computing

更新时间：2025-07-16

- A Customer Experience-Based Cost Minimization Strategy of Storing Data in Cloud Computing
- Acta Electronica Sinica Vol. 42, Issue 1, Pages: 20-27(2014)
- 作者机构：
  
  1. 北京科技大学计算机与通信工程学院,北京,100083
  2. 烟台工程职业技术学院机电工程系,山东,烟台,264006
  3. 清华大学计算机科学与技术系,北京,100084
  4. 北京科技大学计算机与通信工程学院,北京,100083
  5. 烟台工程职业技术学院机电工程系,山东,烟台,264006
  6. 清华大学计算机科学与技术系,北京,100084
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61070182, No.61170209, No.61272528, No.61202432)
- DOI：10.3969/j.issn.0372-2112.2014.01.004
  CLC： TP393
- Published：2014
- 稿件说明：
移动端阅览
WANG Ning, YANG Yang, MENG Kun, et al. A Customer Experience-Based Cost Minimization Strategy of Storing Data in Cloud Computing[J]. Acta Electronica Sinica, 2014, 42(1): 20-27.
DOI：

WANG Ning, YANG Yang, MENG Kun, et al. A Customer Experience-Based Cost Minimization Strategy of Storing Data in Cloud Computing[J]. Acta Electronica Sinica, 2014, 42(1): 20-27. DOI： 10.3969/j.issn.0372-2112.2014.01.004.

摘要

为了提高大数据文件的存取效率，满足各类用户的需求，通常采用对该文件进行分块、冗余副本等机制进行存储，关于设置块大小、副本个数和块部署等存储机制的研究一直是该领域研究重点.根据用户对内容块兴趣需求，我们定义了数据块的热度并提出了一种满足用户需求的存储数据块的最小服务成本策略（MCSB）.在成本矩阵的基础上，通过引入与数据块热度相关的成本矩阵调整因子，使得热度较低的数据块被优先部署，实现了在不改变存储数据块的最小服务总成本的情况下，内容存取服务性能的提高.基于该策略，以Hadoop中的缺省数据块存储策略为控制组，通过在HDFS系统中实现MCSB，并对MCSB进行了较为详细的分析.实验结果显示MCSB策略能够在满足最小服务成本的情况下，具有更短的系统平均响应时间.进一步考虑到数据存储节点由服务器集群承担的事实，对基于不同负载下的数据存储策略进行了深入探讨，在分析现有机制对性能影响的基础上，给出了一种自适应的数据节点内的存储数据块的最小服务成本策略AMCSB，实验表明，本文所提出的AMCSB策略能够在降低服务成本的同时，有利于系统的负载均衡，并提高该系统的服务性能.

Abstract

Splitting a whole large file into some small blocks and distributedly deploying these block replications on severs can improve their application efficiency and meet users' demands.How to split a file

how many replications of a block should be created

and how to deploy these replications become the most critical issures in this field.In this paper

considering client's demands for each block

we introduce block-popularity and present a block deployment strategy according to it

called minimum cost of storing blocks (MCSB)

which can satisfy users' requirement and minimum storage cost.In our strategy

through introducing cost adjustment factors of blocks

not only that lower hot blocks are assured to deploy earlier

but also the practical total storage cost are not exceed than the original case.To maintain the performance of service system

we study resource management methods in-depth among severs with different workloads and propose an adaptive MCSB strategy (AMCSB).We implement the MCSB (and AMCSB) in Hadoop and compare their performance with other related strategies.The experiment results show that MCSB fulfills minimum service cost and shortens average response time

and AMCSB realizes load balance among target servers.

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