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基于局域网的自适应修复的高可用数据流处理 被引量:1

Self-recovery and highly-available stream processing over local area networks
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摘要 为了在局域网络中实现连续、高可用的数据流处理,提出一种基于自适应修复和节点复制的方法:self-recovery andreplication-based backup(SRRB)。通过使用节点复制机制,利用对等节点并行向下游节点发送数据,使下游节点能够使用最先到达该节点的输入数据,提高数据流的传输速率。同时通过使用自适应修复机制,增强系统的容错处理。为了平衡网络开销和低延时保障,提出中心节点算法(CLEA)。通过在网络模拟器ns-3平台上实现,结果表明了SRRB方法具有更好的连续性、稳定性和高可用性。 A self-recovery and replication-based backup (SRRB) approach is proposed to realize both continuous and highly-available data streams processing over local area networks. This approach uses process-pairs mechanism to send output tuples to each downstream replica so that it can use whichever data arrives first for enhancing data stream transmission rate. To further improve the robustness of system, automatical recovery mechanism is devised, Next, for balancing the cost of data stream processing and latency guarantee, central leader election algorithm (CLEA) is developed. It is demonstrated by experiments on network simulator ns-3 that SRRB has more continuity, stability and high-availability.
出处 《计算机工程与设计》 CSCD 北大核心 2011年第7期2302-2305,共4页 Computer Engineering and Design
关键词 数据流 节点复制 自适应修复 中心节点选择算法 后备节点位置决定 data stream node replica self-recovery central node selection algorithm backup node placement decision
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  • 1Shah MA, Hellerstein JM, Brewere. Highly-available, fault-tolerant, parallel dataflows [C].New York, NY, USA: Proceedings of the ACM SIGMOD International Conference on Management of Data,2004:827-838.
  • 2Hwang JH,Balazinska M,Rasin A,et al.High-availability algori- thms for distributed stream processing[C].Washington,DC,USA: Proceedings of the 21 st International Conference on Data Engi- neering,2005:779-790.
  • 3Balazinska M,Balakrishnan H,Madden S,et al.Fanlt-tolerance in the borealis distributed stream processing system[C].New York, NY, USA: Proceedings of the ACM SIGMOD International Con- ference on Management of Data,2005:13-24.
  • 4Hwang JH, Xing Y, Cetintemel U, et al.A cooperative,self-con- figuring high-availability solution for stream processing [C]. Washington, DC, USA: Proceedings of the 23rd International Conference on Data Engineering,2007:176-185.
  • 5Hwang JH, Cetintemel U, Zdonik S. Fast and highly-available stream processing over wide area networks[C].Washington, DC, USA:Proceedings of the 24th International Conference on Data Engineering,2008:804-813.
  • 6Repantis T, Kalogeraki V.Replica placement for high availability in distributed stream processing systems [C]. New York, NY, USA:Proceedings of the 2nd International Conference on Dis- tributed Event-Based Systems,2008:181-192.
  • 7Ahmad Y, Cetintemel U.Networked query processing for distri- buted stream-based applications [C]. Toronto, Canada: Procee- dings of the 30th International Conference on Very Large Data Bases,2004:456-467.
  • 8Peitzuch P, Ledlie J,Shneidman J,et al.Network-aware operator placement for stream-processing systems [C]. Washington, DC, USA: Proceedings of the 22nd International Conference on Data Engineering,2006:49.
  • 9Ledlie J,Gardner P, Seltzer M.Network coordinates in the wild [C].Cambridge,MA,USA:Proceedings of the 4th USENIX Sym- posium on Networked Systems Design and Implementation, 2007:299-311.
  • 10Wong B, Slivkins A, Sirer EG.Meridian: a lightweight network location service without virtual coordinates[C].New York, NY, USA:Proceedings of the Conference on Applications,Technolo- gies, Architectures, and Protocols for Computer Communica- tions.2005:85-96.

二级参考文献65

  • 1徐伟,金蓓弘,李京,曹建农.一种基于移动Agent的复合Web服务容错模型[J].计算机学报,2005,28(4):558-567. 被引量:11
  • 2张立含,尚福华,姜哲俊.基于流数据挖掘的油田数据库监控系统[J].油气田地面工程,2005,24(6):52-52. 被引量:1
  • 3韩东红,王国仁.数据流系统中卸载技术研究综述[J].计算机科学,2005,32(8):102-105. 被引量:3
  • 4常建龙,曹锋,周傲英+.基于滑动窗口的进化数据流聚类[J].软件学报,2007,18(4):905-918. 被引量:61
  • 5Babcock B, Datar M, Motwani R. Sampling from a moving window over streaming data[C]. Eppstein D. Proc of the 13th Annual ACM-SIAM Syrnp on Discrete Algorithms. San Francisco: ACM/SIAM, 2002:633-634.
  • 6Charu C Aggarwal,Han Jiawei, Wang Jianyong,et al.A frame- work for clustering evolving data streams [C]. Proc the 29th VLDB Conference. Berlin: Johann Christoph Freytag, Morgan Kaufmann,2003:81-92.
  • 7Domingos P, Hulten G.Mining high-speed data streams[C]. Proc of the Sixth Intl Conf on Knowledge Discovery and Data Mining,2000:71-80.
  • 8黄磊.流数据挖掘综述.软件学报,2004,15(1).
  • 9Babcock B, Babu S, Datar M,et al,Models and issues in data streams[C].Proc ACM SIGACT-SIGMOD Symp on Principles of Database Systems,2002:1-16.
  • 10WorldWideWebConsortium(W3C). Simple Object Aceess Protocol(SOAP) Version 1.2. 2003

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