基于元胞自动机容灾系统模型的研究
|
摘要
随着信息系统的广泛应用,公司、企业和政府逐渐将其业务扩展到信息平台上来,由此导致应用系统的规模不断增大,参与业务功能的计算机节点不断增多,业务应用的覆盖范围也不断扩展。对信息平台依赖性的增加使得信息系统的高可用性和容灾能力成为业界关注的一个焦点。
大规模的业务容灾系统随着应用的多样性而趋向复杂化,主要呈现为时间和空间上的多种复杂性,其状态和响应事件具有时空离散性;网络拓扑、服务节点、复制、检测规则具有动态综合作用的特征。传统的研究方法已难以满足现代容灾系统的研究需要,而元胞自动机作为研究时空离散系统的一种有效方法,可以用来分析和评价复杂应用环境下的大规模容灾系统。
异步复制传输作为数据复制的重要环节之一,是整个容灾系统得以正常运行的基础。在分析现有异步复制传输机制及其不足的基础上,提出一种依据网络状态自适应调整复制策略的改进模式,并利用元胞自动机对上述模式建模并进行仿真分析与研究。经分析得知,网络异步传输机制下在拥塞临界点附近具有时空长程相关性,改进后的复制模式可以根据上述特性,在一定程度上能有效地提高传输性能。
结合上述对异步复制传输机制的分析,提出一种基于确信度和投票机制的失效检测模型,用元胞自动机对其进行仿真分析及研究,结果表明该模型的准确率和检测时间等指标均符合现代容灾系统的性能要求。
现阶段的大规模分布式业务容灾系统尚缺少有效的性能评价手段。针对这一问题,尝试提出了一种新的评价方法来评估特定复杂业务系统的容灾性能和代价。通过对一个基于对等存储架构案例的建模和分析,可以找出该案例容灾架构的最优点,为实际的容灾系统建设提供理论参考和依据。
Along with the extensive application of information systems, companies, enterprises and the government have gradually expanded their businesses to the information platform, which cause the scale of application system being increased unceasingly, the computer nodes involved in operation functions being grown and the coverage area of service application also being expanded. Due to the increasing dependence on the information platform, the high availability and disaster recovery capability of the information system is being a focus concerned in this field.
The large-scale service disaster-tolerant system has been in the trend of complexity with the diversity of application, which mainly shows a variety of spatiotemporal complex. Besides, its status and responsive events are discrete; and there is a characteristic that the operation of the network topology, the service node, the duplication and the detection are in dynamic combination. While it’s difficult for the traditional technique to accommodate the need of modern disaster-tolerant system research, the cellular automata, as an efficacious tool to study system discrete in time and space, can be used for analyzing and estimating the large-scale disaster-tolerant system under the complex application environment.
As one important tache of data reproduction, the asynchronous duplication transmission is the foundation for the whole disaster-tolerant system to operate normally. In the foundation of analyzing the existed mechanism of the asynchronous duplication transmission and its limitation, one improved mode that be auto-adjusted duplication strategy with consistent of network condition is proposed. The simulation analysis and the research to the above pattern model has been carried on by using the cellular automata, in which it can be seen that under the mechanism of network asynchronous transmission there being spatiotemporal long-range dependece nearby the congestion of the critical point. So according to the above properties, this improved duplication pattern may act a certain extent enhance on transmission performance.
With the combination of above analysis of the asynchronous duplication transmission mechanism, one failure-detector model based on the certainty factor and the voting mechanism has been proposed. Once again, with the simulation analysis and the research to the improved model by using the cellular automata, it is clear that the indices such as model accuracy and detection time are all conformed to the required performance of modern disaster-tolerant system.
As to the issue that there is still a lack of effective evaluation method of performance analysis, a new evaluating method has been put forward in order to estimate the disaster-tolerant capability and the cost of the specific complex service system. Through modeling and analyzing one case based on the peer-to-peer storage systems, the optimal point of the disaster-tolerant construction to the certain case can be found, which provides the theory reference and the gist for constructing reality disaster-tolerant system.
大规模的业务容灾系统随着应用的多样性而趋向复杂化,主要呈现为时间和空间上的多种复杂性,其状态和响应事件具有时空离散性;网络拓扑、服务节点、复制、检测规则具有动态综合作用的特征。传统的研究方法已难以满足现代容灾系统的研究需要,而元胞自动机作为研究时空离散系统的一种有效方法,可以用来分析和评价复杂应用环境下的大规模容灾系统。
异步复制传输作为数据复制的重要环节之一,是整个容灾系统得以正常运行的基础。在分析现有异步复制传输机制及其不足的基础上,提出一种依据网络状态自适应调整复制策略的改进模式,并利用元胞自动机对上述模式建模并进行仿真分析与研究。经分析得知,网络异步传输机制下在拥塞临界点附近具有时空长程相关性,改进后的复制模式可以根据上述特性,在一定程度上能有效地提高传输性能。
结合上述对异步复制传输机制的分析,提出一种基于确信度和投票机制的失效检测模型,用元胞自动机对其进行仿真分析及研究,结果表明该模型的准确率和检测时间等指标均符合现代容灾系统的性能要求。
现阶段的大规模分布式业务容灾系统尚缺少有效的性能评价手段。针对这一问题,尝试提出了一种新的评价方法来评估特定复杂业务系统的容灾性能和代价。通过对一个基于对等存储架构案例的建模和分析,可以找出该案例容灾架构的最优点,为实际的容灾系统建设提供理论参考和依据。
Along with the extensive application of information systems, companies, enterprises and the government have gradually expanded their businesses to the information platform, which cause the scale of application system being increased unceasingly, the computer nodes involved in operation functions being grown and the coverage area of service application also being expanded. Due to the increasing dependence on the information platform, the high availability and disaster recovery capability of the information system is being a focus concerned in this field.
The large-scale service disaster-tolerant system has been in the trend of complexity with the diversity of application, which mainly shows a variety of spatiotemporal complex. Besides, its status and responsive events are discrete; and there is a characteristic that the operation of the network topology, the service node, the duplication and the detection are in dynamic combination. While it’s difficult for the traditional technique to accommodate the need of modern disaster-tolerant system research, the cellular automata, as an efficacious tool to study system discrete in time and space, can be used for analyzing and estimating the large-scale disaster-tolerant system under the complex application environment.
As one important tache of data reproduction, the asynchronous duplication transmission is the foundation for the whole disaster-tolerant system to operate normally. In the foundation of analyzing the existed mechanism of the asynchronous duplication transmission and its limitation, one improved mode that be auto-adjusted duplication strategy with consistent of network condition is proposed. The simulation analysis and the research to the above pattern model has been carried on by using the cellular automata, in which it can be seen that under the mechanism of network asynchronous transmission there being spatiotemporal long-range dependece nearby the congestion of the critical point. So according to the above properties, this improved duplication pattern may act a certain extent enhance on transmission performance.
With the combination of above analysis of the asynchronous duplication transmission mechanism, one failure-detector model based on the certainty factor and the voting mechanism has been proposed. Once again, with the simulation analysis and the research to the improved model by using the cellular automata, it is clear that the indices such as model accuracy and detection time are all conformed to the required performance of modern disaster-tolerant system.
As to the issue that there is still a lack of effective evaluation method of performance analysis, a new evaluating method has been put forward in order to estimate the disaster-tolerant capability and the cost of the specific complex service system. Through modeling and analyzing one case based on the peer-to-peer storage systems, the optimal point of the disaster-tolerant construction to the certain case can be found, which provides the theory reference and the gist for constructing reality disaster-tolerant system.
引文
[1] Jon William Toigo. Disaster Recovery Planning: Preparing for the Unthinkable. Third Edition. Beijing: Publishing House of Electronics Industry, 2004: 2~3, 88, 279~292
[2] Kimberly Keeton, Cipriano Santos, Dirk Beyer, et al. Designing for Disaster. In: FAST 3rd Conference on File and Storage Technologies. 2004. San Francisco, CA, USA: USENIX, 2004: 59~72
[3] Sampath Rangarajan, Sanjeev Setia, Satish K. Tripathi. A Fault-tolerant Algorithm for Replicated Data Management. In: Go Ishani Fed Proceed-ings of the 8th International Conference on Data Engineering Tern pe. Arizona: IEEE Computer Society, 1992: 230~237
[4] Stephen Wolfram. A New Kind of Science. USA: Wolfram Media, 2002: 7~12
[5] Bastien Chopard, Pascal Luthi, Alexandre Masselot. Cellular Automata and Lattice Boltzmann Techniques: An Approach to Model and Simulate Complex Systems. Advances in Complex System, 2002, 5(2002): 103~246
[6] King Richard, Halim Nagui, Hector Garcia-Molina, et al. Management of Remote Backup Copy for Disaster Recovery. ACM Transactions on Database Systems, 1991, 16(2): 338~368
[7] Hector Garcia-Molina, Christos Polyzois. Issues in Disaster Recovery. In: Compcon Spring’90. Thrity-Fifth IEEE Computer Society International Conference. San Francisco, CA, USA: IEEE Computer Society, 1990: 573~577
[8] Man Hoi Choy, Hong Va Leong, Man Hon Wong. Disaster Recovery Techniques for Database Systems. Communications of the ACM, 2000, 43(6): 272~280
[9] Jim Gray, Andreas Reuter. Transaction Processing: Concepts and Techniques.孟小峰译.北京:机械工业出版社, 2004: 67~72
[10] Jon William Toigo. Disaster Recovery Planning: Strategies for Protecting Critical Information Assets. Third Edition. New Jersey: Prentice Hall, 2002: 77~80
[11]田敬,代亚非. P2P持久存储研究.软件学报, 2007, 18(6): 1379~1399
[12] Frank Dabek, Frans Kaashoek, David Karger, et al. Wide-Area Cooperative Storagewith CFS. In: Proceedings of the 18th ACM Symposium on Operating Systems Principles (SOSP 2001). Banff: Chateau Lake Louise, 2001: 202~215
[13] Jeremy Stribling, Isaac Councill, Li Jinyang, et al. OverCite: A Cooperative Digital Research Library. In: Proceedings of the 4th International Workshop on Peer-to-Peer Systems. Ithaca, NY: IPTPS, 2005: 68~79
[14] Peter Druschel, Antony Rowstron. PAST: A Large-scale, Persistent Peer-to-peer Storage Utility. In: Proceedings of the HotOS VIII. Schoss Elmau. Houston: IEEE Conference Proceeding, 2001: 65~70
[15] Atul Adya, William Bolosky, Miguel Castro, et al. Farsite: Federated, Available, and Reliable Storage for an Incompletely Trusted Environment. In: Proceedings of the 5th Symposium on Operating Systems Design and Implementation. Boston, MA: USENIX, 2002: 1~12
[16] Zhang Zheng, Lian Qiao, Lin Shiding, et al. BitVault: a Highly Reliable Distributed Data Retention Platform. ACM SIGOPS Operating Systems Review, 2007, 41(1): 27~36
[17] Ranjita Bhagwan, Kiran Tati, Cheng Yuchung, et al. Total Recall: System Support for Automated Availability Management. In: Proceedings of the 1st ACM/USENIX Symposium on Networked Systems Design and Implementation. San Francisco: USENIX, 2004: 337~350
[18] Ramabhadran Sriram, Pasquale Joseph. Analysis of Long-Running Replicated Systems. In: Proceedings of the 25th IEEE Annual Conference on Computer Communications. Barcelona: IEEE Communications Society, 2006: 1~19
[19] Charles Blake, Rodrigo Rodrigues. High Availability, Scalable Storage, Dynamic Peer Networks: Pick Two. In: Proceedings of the 9th Workshop on Hot Topics in Operating Systems. Hawaii: USENIX, 2003: 1~6
[20] Jai Menon, David Pease, Robert Rees, et al. IBM Storage Tank-A Heterogeneous Scalable SAN File System. IBM Systems Journal, 2003, 42(2): 250~267
[21] Hugo Patterson, Stephen Manley, Mike Federwisch, et al. SnapMirror: File System Based Asynchronous Mirroring for Disaster Recovery. In: Proceedings of the Conference on File and Storage Technologies (FAST). California, USA: USENIX, 2002: 117~129
[22] Baldoni Roberto, Marchetti Carlo, Tucci Piergiovanni Sara. Asynchronous ActiveReplication in Three-Tier Distributed Systems. In: Proceedings of the 2002 Pacific Rim International Symposium on. PRDC. Tsukuba. Japan: Dependable Computing, 2002: 19~26
[23] Pascal Felber, Xavier Défago, Patrick Eugster, et al. Replicating Corba Objects: a Marriage Between Active and Passive Replication. In: Proceedings of Second IFIP International Working Conference on Distributed Applications and Interoperable Systems (DAIS’99). Helsinki, Finland: Kluwer, 1999: 375~388
[24] Xavier Défago, Andre Schiper. Semi-Passive Replication and Lazy Consensus. Journal of Parallel and Distributed Systems, 2004, 64(12): 1380~1398
[25] Xavier Défago, Andre Schiper, Nicole Sergent. Semi-passive Replication. In: Proceedings of Seventeenth IEEE Symposium on. On Reliable Distributed Systems. West Lafayette, USA: IEEE Computer Society, 1998: 43~50
[26] Xavier Défago. Semi-Passive Replication and the Eventual Leadership. In: Proceedings of Workshop on Dependable Distributed Data Management. Florianópolis, Brazil: IEEE Computer Society, 2004: 13~18
[27] Ji Minwen, Alistair Veitch, John Wilkes. Seneca: Remote Mirroring Done Write. In: USENIX Technical Conference. San Antonio, USA: USENIX, 2003: 253~268
[28] Tushar Deepak Chandra, Sam Toueg. Unreliable Failure Detectors for Reliable Distributed System. Journal of the ACM, 1996, 43(2): 225~267
[29] Chen Wei, Sam Toueg, Kawazoe Aguilera Marcos. On the Quality of Service of Failure Detectors. IEEE Transactions on Computers, 2002, 51(5): 561~580
[30] Marin Bertier, Olivier Marin, Pierre Sens. Performance Analysis of a Hierarchical Failure Detector. In: Proceedings of the 2003 International Conference. On Dependable Systems and Networks. Washington DC: IEEE Computer Society, 2003: 635~644
[31] Takuya Hayashibara, Xavier Défago, Yared R., et al. The Accrual Failure Detector. In: Proceedings of 23rd IEEE International Symposium. On Reliable Distributed Systems (SRDS2004). Florianópolis, Brazil: IEEE Computer Society, 2004: 376~391
[32] Marin Bertier, Olivier Marin, Pierre Sens. Implementation and Performance Evaluation of an Adaptable Failure Detector. In: Proceedings 15th International Conference. On Dependable Systems and Networks. Washington DC: IEEEComputer Society, 2002: 354~363
[33] Mark Allman, Vern Paxson. On Estimating End-to-End Network Path Properties. ACM SIGCOMM Computer Communication Review, 1999, 29(4): 263~274
[34]陈江宁,魏峻,杨波,等. Web应用服务器的适应性失效检测.软件学报, 2005, 16(11): 1929~1938
[35] Walter Willinger, Murad Taqqu, Robert Sherman, et al. Self-Similarity through High-Variablility: Statistical Analysis of Ethernet LAN Traffic at the Source Level. IEEE/ACM Transactions on Networking, 1997, 5(1): 71~86
[36] Toru Ohira, Ryusuke Sawatari. Phase Transition in Computer Network Traffic Model. Physics Review E, 1998, 58(1): 193~195
[37]袁坚,任勇,山秀明.一种计算机网络的元胞自动机模型及分析.物理学报, 2000, 49(3): 398~402
[38]袁坚,任勇,刘峰,山秀明.复杂计算机网络中的相变和整体关联行为.物理学报, 2001, 50(7): 1221~1225
[39] Yuan Jian, Kevin Mills. Exploring Collective Dynamics in Communication Networks. Journal of Research of the National Institute of the Standards and Technology, 2002, 107(2): 179~191
[40] Henryk Fuks, Anna T. Lawniczak. Performance of Data Networks with Random Links. Mathematics and Computers in Simulation, 1999, 51(2): 101~117
[41] Henryk Fuks, Anna T. Lawniczak, Stanislav Volkov. Packet Delay in Models of Data Network. ACM Transactions on Modeling and Computer Simulation, 2001, 11(3): 233~250
[42] Chen Maoke, He Tao, Li Xing. A Mean-Field Theory of Cellular Automata Model for Distributed Packet Networks. In: Lecture Notes in Computer Science. ICOIN 2004. Berlin: Springer, 2004: 773~783
[43]刘峰,任勇,山秀明.互联网络数据包传输的一种简单元胞自动机模型.物理学报, 2002, 51(6): 1175~1180
[44] Lewis William, Richard Jr., Richard Watson, et al. An Empirical Assessment of IT Disaster Risk. Communications of the ACM, 2003, 46(9): 201~206
[45] Steven Strogatz. Exploring Complex Networks. Nature, 2001, 410(6825): 268~276
[46] Garth A. Gibson, Rodney Van Meter. Network Attached Storage Architecture.Communications of the ACM, 2000, 43(11): 37~45
[47] Jonathan Bright, John Chandy. A Scalable Architecture for Clustered Network Attached Storage. In: Proceedings 20th IEEE/11th NASA Goddard Conference. Mass Storage Systems and Technologies. California: IEEE Computer Society, 2003: 196~206
[48] Michael Mesnier, Gregory R. Ganger, Erik Riedel. Object-Based Storage. Communications Magazine IEEE, 2003, 41(8): 84~90
[49] Yang Mao, Zhang Zheng, Li Xiaoming, et al. An Empirical Study of Free-Riding Behavior in the Maze P2P File-Sharing System. In: Proceedings of the 4th International Workshop on Peer-to-Peer Systems. Ithaca, NY: IPTPS, 2005: 182~192
[50] Albert Reka, Albert-Laszlo Barabasi. Statistical Mechanics of Complex Networks. Reviews of Modern Physics, 2002(74): 47~94
[51] Bernard M. Waxman. Routing of Multipoint Connections. IEEE Journal on Selected Areas in Communications, 1988, 6(9): 1617~1622
[52] Ellen Zegura, Kenneth Calvert, Michael Donahoo. A Quantitative Comparison of Graph-Based Models for Internet Topology. IEEE/ACM Transactions on Networking, 1997, 5(6): 770~783
[53] Michalis Faloutsos, Petros Faloutsos, Christos Faloutsos. On Power-Law Relationships of the Internet Topology. ACM SIGCOMM Computer Communication Review, 1999, 29(4): 251~262
[54] Anukool Lakhina, John W. Byers, Mark Crovella, et al. Sampling Biases in IP Topology Measurements. In: Proceedings of the IEEE INFOCOM. 2003. San Francisco: IEEE Computer and Communications Societies, 2003: 332~341
[55] Sudhir L. Tauro, Christopher Palmer, Georgos Siganos, et al. A Simple Conceptual Model for the Internet Topology. In: Proceedings of the GLOBECOM’01. San Antonio: IEEE GLOBECOM, 2001: 1667~1671
[56] Robert C. Chalmers, Kevin C. Almeroth. On the Topology of Multicast Trees. IEEE/ACM Trans. on Networking, 2003, 11(1): 153~165
[57] Christopher Palmer, Gregory Steffan. Generating Network Topologies that Obey Power Laws. In: Proceedings of the GLOBECOM 2000. San Francisco: IEEE GLOBECOM, 2000: 434~438
[58] William Aiello, Chung Fan, Lu Linyuan. A Random Graph Model for Massive Graphs. In: Proceedings of the 32nd Annual ACM Symposium on Theory of Computing. New York: ACM SIGACT, 2000: 171~180
[59] Alberto Medina, Anukool Lakhina, Ibrahim Matta, et al. BRITE: An Approach to Universal Topology Generation. In: Proceedings of the MASCOTS 2001. Washington: IEEE Computer Society, 2001: 346~353
[60] Ahmed E., Elgazzar A.S. On Some Application of Cellular Automata. Physica A, 2001, 296(3): 529~538
[61]曹兴芹.复杂系统的元胞自动机方法研究: [博士学位论文].武汉:华中科技大学图书馆, 2005
[62] Li Xia, Anthony Gar-On Yeh. A Cellular Automata Model to Simulate Development Density for Urban Planning. Enviroment and Planning B, 2002, 29(3): 431~450
[63] Edward K. Lee, Chandramohan A. Thekkath. Petal: Distributed Virtual Disk. In: Proceedings of the Seventh International Conference on Architectural Support for Programming Languages and Operating Systems. Cambridge, MA: CiteSeer, 1996: 84~92
[64] Bernardo A. Huberman, Rajan M. Lukose. Social Dilemmas and Internet Congestion. Science, 1997, 277(5325): 535~537
[65] Jon Crowcroft, Michael Luby, Vern Paxson. Traffic Jams on the Internet. Science, 1998, 280(5361): 179
[66] Toru Ohura, Ryusuke Sawatari. Phase Transition in a Computer Network Traffic Model. Physical Review, 1998, 58(1): 193~195
[67] Torsten Huisinga, Robert Barlovic, Wolfgang Knosepe, et al. A Microscopic Model for Packet Transport in the Internet. Physica A, 2001, 294(2001): 294~256
[68] John Doyle, Jean Carlson, Steven Low, et al. Robustness and the Internet: Theoretical Foundations. In: Proceedings of the ACM SIGCOMM NREDS Workshop. Pittsburgh, USA: CiteSeer, 2002: 56~58
[69] Henryk Fuks, Anna Lawniczak. Performance of Data Networks with Random Links. Mathematics and Computers in Simulation, 1999, 51(1): 101~117
[70] Takayasu Misako, Fukuda Kensuke, Takayasu Hideki. Dynamic Phase TransitionObserved in the Internet Traffic Flow. Physica A, 2000, 277(2000): 248~260
[71] Fukuda Kensuke, Takayasu Misako, Takayasu Hideki. Origin of Self-similarity in TCP Traffic. In: Proceedings of International Symposium on Performance Evaluation of Computer and Telecommunication Systems. Montreal: SPECTS, 2003: 18~26
[72] Chen Wei, Sam Toueg, Marcos Kawazoe Aguilera. On the Quality of Service of Failure Detectors. IEEE Transactions Computers, 2002, 51(5): 561~580
[73]黎夏,叶嘉安.约束性单元演化CA模型及可持续城市发展形态的模拟.地理学报, 1999, 54(4): 289~298
[74]谢季坚,刘承平.模糊数学方法及其应用. (第二版).武汉:华中科技大学出版社, 2004: 210~219
[75]刘次华.随机过程(第二版).武汉:华中科技大学出版社, 2001: 73~83
[76] Zheng Weimin, Hu Jinfeng, Li Ming. Granary: Architecture of Object Oriented Internet Storage Service. In: Proceedings of the IEEE International Conference on E-Commerce Technology for Dynamic E-Business. Beijing: IEEE Computer Society, 2004: 294~297
[77] Ben Y. Zhao, John Kubiatowicz, Anthony D. Joseph. Tapstry: An Infrastructure for Fault-tolerant Wide-area Location and Routing. Technical Report UCB/CSD-01-1141 Computer Science Division. California: Berkeley, 2001: 1~9
[78] Dinesh C. Verma, Seraphin B. Calo. A Toolkit for Policy Enablement in Autonomic Computing. In: Proceedings of the International Conference on Autonomic Computing (ICAC04). NY, USA: IEEE Computer Society, 2004: 270~271
[79] Jeffrey O. Kephart, David M. Chess. The Vision of Autonomic Computing. Computer Journal, 2003, 36(1): 41~50
[2] Kimberly Keeton, Cipriano Santos, Dirk Beyer, et al. Designing for Disaster. In: FAST 3rd Conference on File and Storage Technologies. 2004. San Francisco, CA, USA: USENIX, 2004: 59~72
[3] Sampath Rangarajan, Sanjeev Setia, Satish K. Tripathi. A Fault-tolerant Algorithm for Replicated Data Management. In: Go Ishani Fed Proceed-ings of the 8th International Conference on Data Engineering Tern pe. Arizona: IEEE Computer Society, 1992: 230~237
[4] Stephen Wolfram. A New Kind of Science. USA: Wolfram Media, 2002: 7~12
[5] Bastien Chopard, Pascal Luthi, Alexandre Masselot. Cellular Automata and Lattice Boltzmann Techniques: An Approach to Model and Simulate Complex Systems. Advances in Complex System, 2002, 5(2002): 103~246
[6] King Richard, Halim Nagui, Hector Garcia-Molina, et al. Management of Remote Backup Copy for Disaster Recovery. ACM Transactions on Database Systems, 1991, 16(2): 338~368
[7] Hector Garcia-Molina, Christos Polyzois. Issues in Disaster Recovery. In: Compcon Spring’90. Thrity-Fifth IEEE Computer Society International Conference. San Francisco, CA, USA: IEEE Computer Society, 1990: 573~577
[8] Man Hoi Choy, Hong Va Leong, Man Hon Wong. Disaster Recovery Techniques for Database Systems. Communications of the ACM, 2000, 43(6): 272~280
[9] Jim Gray, Andreas Reuter. Transaction Processing: Concepts and Techniques.孟小峰译.北京:机械工业出版社, 2004: 67~72
[10] Jon William Toigo. Disaster Recovery Planning: Strategies for Protecting Critical Information Assets. Third Edition. New Jersey: Prentice Hall, 2002: 77~80
[11]田敬,代亚非. P2P持久存储研究.软件学报, 2007, 18(6): 1379~1399
[12] Frank Dabek, Frans Kaashoek, David Karger, et al. Wide-Area Cooperative Storagewith CFS. In: Proceedings of the 18th ACM Symposium on Operating Systems Principles (SOSP 2001). Banff: Chateau Lake Louise, 2001: 202~215
[13] Jeremy Stribling, Isaac Councill, Li Jinyang, et al. OverCite: A Cooperative Digital Research Library. In: Proceedings of the 4th International Workshop on Peer-to-Peer Systems. Ithaca, NY: IPTPS, 2005: 68~79
[14] Peter Druschel, Antony Rowstron. PAST: A Large-scale, Persistent Peer-to-peer Storage Utility. In: Proceedings of the HotOS VIII. Schoss Elmau. Houston: IEEE Conference Proceeding, 2001: 65~70
[15] Atul Adya, William Bolosky, Miguel Castro, et al. Farsite: Federated, Available, and Reliable Storage for an Incompletely Trusted Environment. In: Proceedings of the 5th Symposium on Operating Systems Design and Implementation. Boston, MA: USENIX, 2002: 1~12
[16] Zhang Zheng, Lian Qiao, Lin Shiding, et al. BitVault: a Highly Reliable Distributed Data Retention Platform. ACM SIGOPS Operating Systems Review, 2007, 41(1): 27~36
[17] Ranjita Bhagwan, Kiran Tati, Cheng Yuchung, et al. Total Recall: System Support for Automated Availability Management. In: Proceedings of the 1st ACM/USENIX Symposium on Networked Systems Design and Implementation. San Francisco: USENIX, 2004: 337~350
[18] Ramabhadran Sriram, Pasquale Joseph. Analysis of Long-Running Replicated Systems. In: Proceedings of the 25th IEEE Annual Conference on Computer Communications. Barcelona: IEEE Communications Society, 2006: 1~19
[19] Charles Blake, Rodrigo Rodrigues. High Availability, Scalable Storage, Dynamic Peer Networks: Pick Two. In: Proceedings of the 9th Workshop on Hot Topics in Operating Systems. Hawaii: USENIX, 2003: 1~6
[20] Jai Menon, David Pease, Robert Rees, et al. IBM Storage Tank-A Heterogeneous Scalable SAN File System. IBM Systems Journal, 2003, 42(2): 250~267
[21] Hugo Patterson, Stephen Manley, Mike Federwisch, et al. SnapMirror: File System Based Asynchronous Mirroring for Disaster Recovery. In: Proceedings of the Conference on File and Storage Technologies (FAST). California, USA: USENIX, 2002: 117~129
[22] Baldoni Roberto, Marchetti Carlo, Tucci Piergiovanni Sara. Asynchronous ActiveReplication in Three-Tier Distributed Systems. In: Proceedings of the 2002 Pacific Rim International Symposium on. PRDC. Tsukuba. Japan: Dependable Computing, 2002: 19~26
[23] Pascal Felber, Xavier Défago, Patrick Eugster, et al. Replicating Corba Objects: a Marriage Between Active and Passive Replication. In: Proceedings of Second IFIP International Working Conference on Distributed Applications and Interoperable Systems (DAIS’99). Helsinki, Finland: Kluwer, 1999: 375~388
[24] Xavier Défago, Andre Schiper. Semi-Passive Replication and Lazy Consensus. Journal of Parallel and Distributed Systems, 2004, 64(12): 1380~1398
[25] Xavier Défago, Andre Schiper, Nicole Sergent. Semi-passive Replication. In: Proceedings of Seventeenth IEEE Symposium on. On Reliable Distributed Systems. West Lafayette, USA: IEEE Computer Society, 1998: 43~50
[26] Xavier Défago. Semi-Passive Replication and the Eventual Leadership. In: Proceedings of Workshop on Dependable Distributed Data Management. Florianópolis, Brazil: IEEE Computer Society, 2004: 13~18
[27] Ji Minwen, Alistair Veitch, John Wilkes. Seneca: Remote Mirroring Done Write. In: USENIX Technical Conference. San Antonio, USA: USENIX, 2003: 253~268
[28] Tushar Deepak Chandra, Sam Toueg. Unreliable Failure Detectors for Reliable Distributed System. Journal of the ACM, 1996, 43(2): 225~267
[29] Chen Wei, Sam Toueg, Kawazoe Aguilera Marcos. On the Quality of Service of Failure Detectors. IEEE Transactions on Computers, 2002, 51(5): 561~580
[30] Marin Bertier, Olivier Marin, Pierre Sens. Performance Analysis of a Hierarchical Failure Detector. In: Proceedings of the 2003 International Conference. On Dependable Systems and Networks. Washington DC: IEEE Computer Society, 2003: 635~644
[31] Takuya Hayashibara, Xavier Défago, Yared R., et al. The Accrual Failure Detector. In: Proceedings of 23rd IEEE International Symposium. On Reliable Distributed Systems (SRDS2004). Florianópolis, Brazil: IEEE Computer Society, 2004: 376~391
[32] Marin Bertier, Olivier Marin, Pierre Sens. Implementation and Performance Evaluation of an Adaptable Failure Detector. In: Proceedings 15th International Conference. On Dependable Systems and Networks. Washington DC: IEEEComputer Society, 2002: 354~363
[33] Mark Allman, Vern Paxson. On Estimating End-to-End Network Path Properties. ACM SIGCOMM Computer Communication Review, 1999, 29(4): 263~274
[34]陈江宁,魏峻,杨波,等. Web应用服务器的适应性失效检测.软件学报, 2005, 16(11): 1929~1938
[35] Walter Willinger, Murad Taqqu, Robert Sherman, et al. Self-Similarity through High-Variablility: Statistical Analysis of Ethernet LAN Traffic at the Source Level. IEEE/ACM Transactions on Networking, 1997, 5(1): 71~86
[36] Toru Ohira, Ryusuke Sawatari. Phase Transition in Computer Network Traffic Model. Physics Review E, 1998, 58(1): 193~195
[37]袁坚,任勇,山秀明.一种计算机网络的元胞自动机模型及分析.物理学报, 2000, 49(3): 398~402
[38]袁坚,任勇,刘峰,山秀明.复杂计算机网络中的相变和整体关联行为.物理学报, 2001, 50(7): 1221~1225
[39] Yuan Jian, Kevin Mills. Exploring Collective Dynamics in Communication Networks. Journal of Research of the National Institute of the Standards and Technology, 2002, 107(2): 179~191
[40] Henryk Fuks, Anna T. Lawniczak. Performance of Data Networks with Random Links. Mathematics and Computers in Simulation, 1999, 51(2): 101~117
[41] Henryk Fuks, Anna T. Lawniczak, Stanislav Volkov. Packet Delay in Models of Data Network. ACM Transactions on Modeling and Computer Simulation, 2001, 11(3): 233~250
[42] Chen Maoke, He Tao, Li Xing. A Mean-Field Theory of Cellular Automata Model for Distributed Packet Networks. In: Lecture Notes in Computer Science. ICOIN 2004. Berlin: Springer, 2004: 773~783
[43]刘峰,任勇,山秀明.互联网络数据包传输的一种简单元胞自动机模型.物理学报, 2002, 51(6): 1175~1180
[44] Lewis William, Richard Jr., Richard Watson, et al. An Empirical Assessment of IT Disaster Risk. Communications of the ACM, 2003, 46(9): 201~206
[45] Steven Strogatz. Exploring Complex Networks. Nature, 2001, 410(6825): 268~276
[46] Garth A. Gibson, Rodney Van Meter. Network Attached Storage Architecture.Communications of the ACM, 2000, 43(11): 37~45
[47] Jonathan Bright, John Chandy. A Scalable Architecture for Clustered Network Attached Storage. In: Proceedings 20th IEEE/11th NASA Goddard Conference. Mass Storage Systems and Technologies. California: IEEE Computer Society, 2003: 196~206
[48] Michael Mesnier, Gregory R. Ganger, Erik Riedel. Object-Based Storage. Communications Magazine IEEE, 2003, 41(8): 84~90
[49] Yang Mao, Zhang Zheng, Li Xiaoming, et al. An Empirical Study of Free-Riding Behavior in the Maze P2P File-Sharing System. In: Proceedings of the 4th International Workshop on Peer-to-Peer Systems. Ithaca, NY: IPTPS, 2005: 182~192
[50] Albert Reka, Albert-Laszlo Barabasi. Statistical Mechanics of Complex Networks. Reviews of Modern Physics, 2002(74): 47~94
[51] Bernard M. Waxman. Routing of Multipoint Connections. IEEE Journal on Selected Areas in Communications, 1988, 6(9): 1617~1622
[52] Ellen Zegura, Kenneth Calvert, Michael Donahoo. A Quantitative Comparison of Graph-Based Models for Internet Topology. IEEE/ACM Transactions on Networking, 1997, 5(6): 770~783
[53] Michalis Faloutsos, Petros Faloutsos, Christos Faloutsos. On Power-Law Relationships of the Internet Topology. ACM SIGCOMM Computer Communication Review, 1999, 29(4): 251~262
[54] Anukool Lakhina, John W. Byers, Mark Crovella, et al. Sampling Biases in IP Topology Measurements. In: Proceedings of the IEEE INFOCOM. 2003. San Francisco: IEEE Computer and Communications Societies, 2003: 332~341
[55] Sudhir L. Tauro, Christopher Palmer, Georgos Siganos, et al. A Simple Conceptual Model for the Internet Topology. In: Proceedings of the GLOBECOM’01. San Antonio: IEEE GLOBECOM, 2001: 1667~1671
[56] Robert C. Chalmers, Kevin C. Almeroth. On the Topology of Multicast Trees. IEEE/ACM Trans. on Networking, 2003, 11(1): 153~165
[57] Christopher Palmer, Gregory Steffan. Generating Network Topologies that Obey Power Laws. In: Proceedings of the GLOBECOM 2000. San Francisco: IEEE GLOBECOM, 2000: 434~438
[58] William Aiello, Chung Fan, Lu Linyuan. A Random Graph Model for Massive Graphs. In: Proceedings of the 32nd Annual ACM Symposium on Theory of Computing. New York: ACM SIGACT, 2000: 171~180
[59] Alberto Medina, Anukool Lakhina, Ibrahim Matta, et al. BRITE: An Approach to Universal Topology Generation. In: Proceedings of the MASCOTS 2001. Washington: IEEE Computer Society, 2001: 346~353
[60] Ahmed E., Elgazzar A.S. On Some Application of Cellular Automata. Physica A, 2001, 296(3): 529~538
[61]曹兴芹.复杂系统的元胞自动机方法研究: [博士学位论文].武汉:华中科技大学图书馆, 2005
[62] Li Xia, Anthony Gar-On Yeh. A Cellular Automata Model to Simulate Development Density for Urban Planning. Enviroment and Planning B, 2002, 29(3): 431~450
[63] Edward K. Lee, Chandramohan A. Thekkath. Petal: Distributed Virtual Disk. In: Proceedings of the Seventh International Conference on Architectural Support for Programming Languages and Operating Systems. Cambridge, MA: CiteSeer, 1996: 84~92
[64] Bernardo A. Huberman, Rajan M. Lukose. Social Dilemmas and Internet Congestion. Science, 1997, 277(5325): 535~537
[65] Jon Crowcroft, Michael Luby, Vern Paxson. Traffic Jams on the Internet. Science, 1998, 280(5361): 179
[66] Toru Ohura, Ryusuke Sawatari. Phase Transition in a Computer Network Traffic Model. Physical Review, 1998, 58(1): 193~195
[67] Torsten Huisinga, Robert Barlovic, Wolfgang Knosepe, et al. A Microscopic Model for Packet Transport in the Internet. Physica A, 2001, 294(2001): 294~256
[68] John Doyle, Jean Carlson, Steven Low, et al. Robustness and the Internet: Theoretical Foundations. In: Proceedings of the ACM SIGCOMM NREDS Workshop. Pittsburgh, USA: CiteSeer, 2002: 56~58
[69] Henryk Fuks, Anna Lawniczak. Performance of Data Networks with Random Links. Mathematics and Computers in Simulation, 1999, 51(1): 101~117
[70] Takayasu Misako, Fukuda Kensuke, Takayasu Hideki. Dynamic Phase TransitionObserved in the Internet Traffic Flow. Physica A, 2000, 277(2000): 248~260
[71] Fukuda Kensuke, Takayasu Misako, Takayasu Hideki. Origin of Self-similarity in TCP Traffic. In: Proceedings of International Symposium on Performance Evaluation of Computer and Telecommunication Systems. Montreal: SPECTS, 2003: 18~26
[72] Chen Wei, Sam Toueg, Marcos Kawazoe Aguilera. On the Quality of Service of Failure Detectors. IEEE Transactions Computers, 2002, 51(5): 561~580
[73]黎夏,叶嘉安.约束性单元演化CA模型及可持续城市发展形态的模拟.地理学报, 1999, 54(4): 289~298
[74]谢季坚,刘承平.模糊数学方法及其应用. (第二版).武汉:华中科技大学出版社, 2004: 210~219
[75]刘次华.随机过程(第二版).武汉:华中科技大学出版社, 2001: 73~83
[76] Zheng Weimin, Hu Jinfeng, Li Ming. Granary: Architecture of Object Oriented Internet Storage Service. In: Proceedings of the IEEE International Conference on E-Commerce Technology for Dynamic E-Business. Beijing: IEEE Computer Society, 2004: 294~297
[77] Ben Y. Zhao, John Kubiatowicz, Anthony D. Joseph. Tapstry: An Infrastructure for Fault-tolerant Wide-area Location and Routing. Technical Report UCB/CSD-01-1141 Computer Science Division. California: Berkeley, 2001: 1~9
[78] Dinesh C. Verma, Seraphin B. Calo. A Toolkit for Policy Enablement in Autonomic Computing. In: Proceedings of the International Conference on Autonomic Computing (ICAC04). NY, USA: IEEE Computer Society, 2004: 270~271
[79] Jeffrey O. Kephart, David M. Chess. The Vision of Autonomic Computing. Computer Journal, 2003, 36(1): 41~50