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Hadoop中云数据负载均衡算法的研究及优化 被引量：19

Research and Optimize of Cloud Data Load Balancing in Hadoop
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摘要 介绍了Hadoop的数据负载均衡算法.为了提升Hadoop数据负载均衡算法的效率,文中提出了超负载机架的优先处理及引用排序策略的解决负载均衡的改进算法.实验证明了改进算法在特定的环境下或能够在较短的时间内使各个机架的数据负载达到平衡以及能够优先处理负载超大节点. This paper describes the data load balancing algorithm of Hadoop. In order to improve the efficiency of algorithm, we propose the optimization algorithms using sorting method or handling the overloading racks preferentially to solve load balancing. Experiments show the racks used optimization algorithm can realize load balancing in shorter time or handle the overloading nodes preferentially in certain circumstance.
作者 刘琨 肖琳 赵海燕
机构地区 北京联合大学应用科技学院
出处 《微电子学与计算机》 CSCD 北大核心 2012年第9期18-22,共5页 Microelectronics & Computer
基金 北京市教育委员会科技计划项目(KM201211417008) 北京联合大学校级科研项目(ZK2009606)
关键词 HADOOP 云计算 云存储 负载均衡 HDFS Hadoop cloud computing cloud storage load balancing HDFS
分类号 TP393 [自动化与计算机技术—计算机应用技术]
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参考文献8

  • 1张建勋,古志民,郑超.云计算研究进展综述[J].计算机应用研究,2010,27(2):429-433. 被引量：591
  • 2陈康,郑纬民.云计算:系统实例与研究现状[J].软件学报,2009,20(5):1337-1348. 被引量：1314
  • 3Dhruba Borthakur. The hadoop distributed file sys- tem.- architecture and design [EB/OL]. (2008-09-02) [2010-08-25]. http://hadoop, apache, org/common/ docs/r0.16.0/hdfs_design, html.
  • 4Jeffrey Dean, Sanjay Ghemawat. MapReduce: sim- plied data processing on large elusters[C]// Proceed- ings of the 6th Symposium on Operating System De- sign and Implementation. New York: ACM Press, 2004:137-150.
  • 5Hadoop HDFS[EB/OL]. (2011 - 10-18) [2011 - 10- 25]. http://hadoop, apache, org/hdfs/.
  • 6Caibinbupt.Hadoop源代码分析(重读GFS的文章)[EB/OL].(2009-01-29)[2010-8-25].http://caibinbupt.javaeye.com/blog/318949.
  • 7Tom White. Hadoop.. the definitive guide[M]. United States of America: O'Reilly Media, Inc. 2009.
  • 8分布式基础学习[EB/OL]2009-02-22.http://www.cnblogs.com/duguguiyu/archive/2009/02/22/1396034.html.

二级参考文献62

  • 1Sims K. IBM introduces ready-to-use cloud computing collaboration services get clients started with cloud computing. 2007. http://www-03.ibm.com/press/us/en/pressrelease/22613.wss
  • 2Boss G, Malladi P, Quan D, Legregni L, Hall H. Cloud computing. IBM White Paper, 2007. http://download.boulder.ibm.com/ ibmdl/pub/software/dw/wes/hipods/Cloud_computing_wp_final_8Oct.pdf
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  • 5Barroso LA, Dean J, Holzle U. Web search for a planet: The Google cluster architecture. IEEE Micro, 2003,23(2):22-28.
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  • 7Ghemawat S, Gobioff H, Leung ST. The Google file system. In: Proc. of the 19th ACM Symp. on Operating Systems Principles. New York: ACM Press, 2003.29-43.
  • 8Dean J, Ghemawat S. MapReduce: Simplified data processing on large clusters. In: Proc. of the 6th Symp. on Operating System Design and Implementation. Berkeley: USENIX Association, 2004. 137-150.
  • 9Burrows M. The chubby lock service for loosely-coupled distributed systems. In: Proc. of the 7th USENIX Symp. on Operating Systems Design and Implementation. Berkeley: USENIX Association, 2006. 335-350.
  • 10Chang F, Dean J, Ghemawat S, Hsieh WC, Wallach DA, Burrows M, Chandra T, Fikes A, Gruber RE. Bigtable: A distributed storage system for structured data. In: Proc. of the 7th USENIX Symp. on Operating Systems Design and Implementation. Berkeley: USENIX Association, 2006. 205-218.

共引文献1799

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引证文献19

二级引证文献95

微电子学与计算机
2012年 第9期

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