期刊文献+

对等网络中一种优化的副本分布方法 被引量:18

An Optimized Replica Distribution Method for Peer-to-Peer Network
下载PDF
导出
摘要 数据复制技术是一种提高P2P系统中数据可靠性和可用性的常用策略.现有复制方法大多只考虑副本数量,副本数量越多就越能提高资源访问效率,但采用这样的数据复制方法将会带来高昂的副本一致性维护代价.为平衡副本一致性维护的开销和多副本带来的访问性能提升之间的关系,该文提出了动态副本分布方法.文中首先给出了副本目录的设计和副本信息的获取方法,能够获得某一逻辑资源的所有副本信息.然后,根据逻辑资源的全局副本信息,对访问频率高且平均响应时间长的数据资源进行复制,并给出副本数量的计算方法.最后,根据用户访问特征和节点实时带宽等信息计算放置副本的最佳地点,使副本分布能够适应数据访问请求和网络带宽的动态变化.模拟实验结果显示,该方法能够实现全局优化的副本分布,以少量数据副本提升资源访问的性能. Replication is a common method used to improve the performance of data access in P2P systems.It improves not only data access efficiency,but also data availability and fault tolerance.The larger number of replicas,the better performance it can obtain.However,a large number of replicas may lead to high overhead for unnecessary data replication and consistency maintenance in case of updates.The optimal replication strategy MACR (Minimum Access Cost based Replication strategy) is presented which takes into account the access frequency,the status of the network connection and average response time to perform optimal replication.Firstly,the design of the replica catalog is described.To each logical data resource,the replica catalogs have all the information of the replicas and the optimal replication strategy can benefit from it.Secondly,we use the access frequency and the average response time to decide which data resource should be replicated.Then,the method of calculating the number of the replicas is proposed.At the last,MACR strategy finds the appropriate site and executes replication.The simulation results show that MACR offers the benefits of shortening the response time with fewer replicas.
出处 《计算机学报》 EI CSCD 北大核心 2014年第6期1424-1434,共11页 Chinese Journal of Computers
基金 国家自然科学基金(61272511)资助
关键词 对等网络 数据复制 副本分布 副本放置 副本数量 物联网 P2P data replication replica distribution replica placement replica number Internet of Things
  • 相关文献

参考文献19

  • 1Lei M,Vrbsky S V,Hong X.An on-line replication strategy to increase availability in data grids.Future Generation Computer Systems,2008,24(2):85-98.
  • 2Perez J M,Garcia Carballeira F,Carretero J.Branch replica tion scheme:A new model for data replication in large scale data grids.Future Generation Computer Systems,2010,26(1):12-20.
  • 3Tu Manghui,Li Peng,Yen I-Ling,et al.Secure data objects replication in data grid.IEEE Transactions on Dependable and Secure Computing,2010,7(1):50-64.
  • 4Furfaro F,Mazzeo G M,Pugliese A.Managing multidimen sional historical aggregate data in unstructured P2P networks.IEEE Transactions on Knowledge and Data Engineering,2010,22(9):1313-1330.
  • 5Wei Q,Veeravalli B,Gong B,et al.CDRM:A cost-effective dynamic replication management scheme for cloud storage cluster//Proceedings of the 2010 IEEE International Confer ence on Cluster Computing (CLUSTER).Heraklion,Crete,2010:188-196.
  • 6Ananthanarayanan G,Agarwal S,Kandula S,et al.Scarlett:Coping with skewed popularity content in mapreduce clusters//Proceedings of the 6th Conference on Computer Systems(EuroSys'11).Salzburg,Austria,2011:287-300.
  • 7Lin Hsiao-Ying,Tzeng Wen-Guey.A secure erasure codebased cloud storage system with secure data forwarding.IEEE Transactions on Parallel and Distributed Systems,2012,23(6):995-1003.
  • 8Lv Q,Cao P,Cohen E,et al.Search and replication in unstructured peer to peer networks//Proceedings of the 16th ACM International Conference on Supercomputing (ICS'02).New York,USA,2002:84-95.
  • 9Cohen E,Shenker S.Replication strategies in unstructured peer-to-peer networks.ACM SIGCOMM Computer CommunicationReview,2002,32(4):177-190.
  • 10Raicu I,Foster I,Zhao Y,et al.The quest for scalable support of data intensive workloads in distributed systems// Proceedings of the 18th ACM International Symposium on H igh Performance Distributed Computing (H PDC).Munich,Germany,2009:207-216.

二级参考文献27

  • 1Kubiatowicz J, Bindel D, Chen Y et al. OceanStore: An architecture for global-scale persistent storage//Proceedings of the 9th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS-IX). Cambridge, MA, USA, 2000:190-201.
  • 2Andrews M, Shepherd B, Srinivasan A et al. Clustering and server selection using passive monitoring//Proceedings of the 21th Annual IEEE Conference on Computer Communications (INFOCOM'02). New York, USA, 2002:1717-1725.
  • 3Park K, Pal V S. Scale and performance in the CoBlitz largefile distribution service//Proceedings of the 3rd Symposium on Networked Systems Design and Implementation (NSDI 2006). San Jose, CA, 2006:3-3.
  • 4Sripanidkulchai K, Ganjam A, Maggs B et al. The feasibility of supporting large-scale live streaming applications with dynamic application end-points//Proceedings of SIGCOMM04. Partland, Oregon, USA, 2004:107-120.
  • 5Tang W, Fu Y, Cherkasova L et al, MediSyn: A synthetic streaming media service workload generator//Proceedings of the 13th International Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV03). Monterey, CA, USA, 2003:12-21.
  • 6Yu H, Zheng D, Zhao B Y et al. Understanding user behavior in large scale video-on-demand systems//Proeeedings of the 1st EuroSys Conference (EuroSys'06). Leuven, Belgium, 2006:333-344.
  • 7Loeser C, Schomaker G, Brinkmann A et al. Content distribution in heterogeneous video-on-demand P2P networks with ARIMA forecasts//Proceedings of 4th International Conference on Networking(ICN 2005). Reunion Island, France,2005: 800-809.
  • 8Breslau L, Cao P, Fan L et al. Web caching and Zipf like distributions: Evidence and implications//Proceedings of the 18th Annual IEEE Conference on Computer Communications (INFOCOM'99). New York, USA, 1999:126-134.
  • 9Chervenak A L, Patterson D A, Katz R H. Choosing the best storage system for video service//Proceedings of the 3rd ACM International Conference on Multimedia (Multimedia' 95). San Francisco, CA, USA, 1995:109-119.
  • 10Xiang Z, Zhang Q, Zhu W et al. Peer-to peer based multimedia distribution service. IEEE Transactions on Multimedia, 2004, 6(2): 343-355.

共引文献13

同被引文献133

引证文献18

二级引证文献21

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部