用户名: 密码: 验证码:
基于QoS的分布式Web服务结构模型及其关键技术研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
Web服务占据了当前网络70%以上的通信流量,并呈明显上升的趋势,在下一代互联网中Web服务普遍被认为代表了网格的发展方向。如何建立合理的Web服务结构模型,并实现有效QoS(Quality of Service)控制的机制与策略,从而满足不断增长的客户需求,为用户提供有效的Web服务,并为不同用户提供区分服务和性能保证,这是当今Web服务发展所面临的巨大挑战,也是实现下一代网络不可缺少的关键技术。
     本文针对基于局域网的Web服务集群和网格Web服务二个研究对象,深入研究了Web服务的结构模型、Web QoS控制的策略和算法。针对Web服务集群,首先提出了一种基于QoS-aware的Web集群区分服务模型,然后在此基础上针对系统负载均衡、区分服务、克服自相似访问业务对QoS的影响、高可用性等几个方面的QoS控制指标提出了一系列解决策略与算法。采取的策略是:先进行某一方面的QoS优化,然后逐步在随后提出的解决方案中综合前面提出的QoS指标一起优化,最后,达到使系统总体回报率最大化的同时,使各项QoS指标得到优化。针对网格Web服务还没有较完善的结构模型,提出了一种多级多层的Web服务结构模型,并对其进行了改进使其具有从协议低层支持负载均衡。总结来说,本文的主要研究工作如下:
     (1)提出了一种Web集群区分服务结构模型,它较好地解决了以往在Web集群系统中前后台区分服务分离的不足。在此基础上,将基于事务的区分服务接纳控制策略运用到此模型。理论分析与实验结果表明:在系统过载时能有效保证系统的稳定性,高优先级任务得到较好的服务,比基于会话的接纳控制效果要好。
     (2)提出了一种结合网络自相似访问特征的接纳控制算法,它综合考虑了请求访问特征以及负载情况等多方面的因素自适应调整,综合优化Web集群系统中多维调度目标,实验结果证明了算法的有效性,它既能适应网络自相似访问特征,又可支持多维QoS的调度优化。
     (3)提出了一种资源优化的QoS控制算法,针对不同的服务有不同的资源需求,提出了一种既能使系统负载均衡又能充分利用系统资源的启发式算法。实验证明,该启发式算法能显著地降低资源优化分配中的计算复杂度,使其能满足实时调度的需要。在此基础上,进一步提出了一种资源优化的双最小均衡区分服务调度算法,该算法综合了多维QoS目标优化以及区分服务。在与其它调度策略如分离式调度算法的对比结果显示:双最小均衡调
Web service, widely considered as the future trend of grid in the next generation of Internet, takes up more than 70% of communication traffic and goes into its boom period. One of the major challenges Web service evolution faces, which is also a fundamental technology for the next generation networks, is how to build a well-defined architecture model and implement effective QoS control mechanisms and policies, so to fulfill increasing users' demand and moreover, to provide varied services and guarantee high performance for different users.The paper, focused on 2 research objects consisting of the LAN Web server clusters and the Grid Web service, carries on an intensive study about Web service architecture model, Web QoS control policies and, algorithms. At first, a Web cluster differentiate service model based on QoS-aware is put forward aiming at the Web server clusters. And then on such a basis a series of solution policies and algorithms is brought up with the guideline of system load balancing, differentiate service, integral self-similar access transaction characteristics and high availability. The policy suggests that QoS optimization at the beginning is taken on some aspect, and then gradually incorporated with the QoS guidelines mentioned above in the following solution, at last brought down on the maximal of system total payoff ratio as well as each QoS guidelines. Given the incomplete structure model of Grid Web service,a multi-level multi-tier architecture model for Web service is held out with the enhancement of QoS features in the capability of load balancing support in the lower part of the protocol. To sum up, Major research contributions are as follows:(1) A differentiate service architecture model over Web cluster is put forward to take a better effect on the solution to the shortcoming of differentiate service detachment in the front-back end over previous Web cluster system. On such a basis, the admission control policy for differentiate service based on the transaction is applied in the model. The experiment result and theory analysis reveal that the system stability is effectively guaranteed in the case of system over-loading and a better service quality is allocated to the high-priority task. it is better than the ones based on the session.(2) A admission control algorithm combined with the self-similar access characteristics over networks is brought forward. It is likely capable of overcoming the defect of self-similar request with the adjustment to the multiple factor regarding the consideration into the request access characteristics and load condition as well as optimizing the multi-dimension objective in the Web cluster system. The experiments result proves
    the availability of the algorithm that can fit the self-similar access characteristics over networks as well as the schedule optimization in multi-dimension QoS.(3) A QoS control algorithm of resource optimization is set forth with the essence of multi-dimension QoS objective control. According to different service demands different resources, a heuristic algorithm (LBBA for shore) that makes full use of system resources also balances system load is raised. The experiment proves that the algorithm can take a apparent decline in the computation complexity in the resource optimization allocation to fulfill the requirement of real-time scheduling. Given the foundation, a dual minimal balance differentiate service scheduling algorithm (DMBA for shore) of resource optimization is further brought up in the combination of multi-dimension resource QoS optimization and differentiate service as well.(4) A QoS scheduling policy based on the inaccurate state aiming at the inaccuracy of the Web cluster system status is held forth. It makes a modeling of system inaccurate status via probability analysis in the purpose of maximizing the value ratio implemented by system with the total consideration into the differentiate service as well as other QoS guidelines. The simulation shows that the algorithm is likely to overcome the inaccuracy of system status and is better than EDF counterpart in the performance. Also taking account the self-similar access transaction flow and differentiate service directing towards the high availability, a error-tolerated scheduling algorithm is held out with the guarantee of high availability for high priority task.(5) A Grid Web service structure model over WAN is proposed. On a basis of the OGSA framework, it separates the logic frame of Web service resource from physical resource structure. And it carries on the searching and locating for Web service resource via the Web service naming system(WSNS for short)in the form of hierarchy organization and maintaining for Web service resource by the area autonomy system (AAS for short). Then it makes an improvement on the structure model. On a basis of the maintaining the advantage of original structure, a resource organization tree (WSROT for short) is appended with the support of good characteristic for QoS guarantee. In conclusion, it is a much better organization structure model over the current Computational Grid.
引文
[1] V. Cardellini, E. Casalicchio, M. Colajanni, P. S. Yu. The state of the art in locally distributed Web-server systems. ACM Computing Surveys[J]. 2002, 34(2): 1-49.
    [2] 单志广,林闯等.Web QoS控制研究综述[J].计算机学报,2004(2):145-156.
    [3] Ben. Ng, C. L. Wang. Document Distribution Algorithm for Load Balancing on an Extensible Web Server Architecture, First IEEE/ACM International Symposium on Cluster Computing and the Crid (CCGrid2001), May, 2001, 15-18 Brisbane, Australia.
    [4] Bestavros. World Wide Web Traffic Reduction and Load Balancing Through Server-Based Caching. IEEE Concurreny: Special Issue on Parallel and Distributed Technology, 5(1): 56-67, Jan-Mar 1997.
    [5] Ian, Foster. Carl, Kesselman. Jeffrey. The Physiology of the Grid An Open Grid Services Architecture for Distributed Systems Integration. Open Grid Services Infrastructure WG, Global Grid Forum. Toronto, Canada, 2002 http://www.Globus.org/ogsa/.
    [6] Florescu D, Grunhagen A, Kossmann D. An XML programming language for Web service specification and composition. In: Prec. of the 11th Int'l World Wide Web Conf. Honolulu: ACM, 2002. 65-76.
    [7] M Klein. XML, RDF, and relatives[J]. IEEE Internet Computing, 2001, 6(2): 26-28.
    [8] E Christensen, F Curbera, G Meredith et. Web Services Description Language (WSDL) 1.1 http://www.w3.org/TR/wsdl.
    [9] Dias D. M, Kish W. etc al. A scalable and highly available Web server. In: Proceedings of the 41st IEEE Computer Society International Conference(COMPCON'96), 1996, 85~92.
    [10] Egevang K., Francis P. The IP network address translation(NAT). RFC1631, May 1994. http://www.ietf.org/rfc/rfc1631.txt
    [11] Anderson E., Patterson D. etc al. The magicrouter, An application of fast packet interposing. University of California, Berkeley, May 1996. http://www.es.berkeley.edu/~eanders/projects/magicrouter/osdi962mr2submission.Ps.
    [12] Ciseo LoealDirector 400 Series, http://www.cisco.com/warp/public/cc/pd/cxsr/400/index. Shtml.
    [13] Hunt G. D. H., Goldszmidt G. S., etc al. Network dispatcher: A connection router for scalable Internet services. Computer Networks and ISDN Systems, 1998, 30: 347~357.
    [14] Damani O. P., Chung P. Y., Huang Y., etc. ONE-IP: Techniques for hosting a service on a cluster of machines. ComputerNetworks and ISDN Systems, 1997, 29: 1019~1027.
    [15] Garland M., Grassia S, etc al. Implementing distributed server groups for the World Wide Web. Carnegie Mellon University: Technical Report CMU2CS2952114, 1995.
    [16] Apostolopoulos G., Aubespin D., etc. Design, implementation and performance of a content based switch. In: Proceedings of INFOCOM 2000, IEEE Press, NewJersey, 2000, 3: 1117~1126.
    [17] Aron M., Sanders D., etc. Scalable content-aware request distribution in cluster based network servers. In: Proceedings of the USENIX Annual Technical Conference, San Diego LA, 2000, 323~336.
    [18] Cohen A, Rangarajan S., Slye H. On the performance of TCP splicing for URL aware redirection. In: Proceedings of the 2nd USENIX Symposium on Internet Technologies and Systems, Boulder, CO, 1999, 117~125.
    [19] Colajanni. M, Yu, P. S. Dynamic load balancing in geographically distributed heterogeneous Web servers. Amsterdam IEEE Computer Society, 1998: 295-302, http://dlib.computer.org/conferen/icdcs/8292/pdf/82920295.pdf.
    [20] Katz. E, Butler. M, McGrath. R. A scalable Web server: the NCSA Prototype[J]. Computer Networks and ISDN Systems, 1994, 27: 155-164.
    [21] Cisco Systems Inc. Load balancing: a multifaceted solution for improving server avalability. White paper, 2000. http://www.cisco.com/warp/public/cc/pd/cxsr/400/tech/lobal-wp.htm.
    [22] Crovella, M. E., Carter, R. L. Dynamic server selection in the Internet. Technical Report, TR-95-014, Department of Computer Science, Bostor University, 1995.
    [23] 林闯.Web服务器集群请求分配和选择的性能分析[J].计算机学报,2000,23(5),500-508.
    [24] 单志广,戴琼海等.Web请求分配和选择的综合方案与性能分析[J].软件学报,2001,12(3),355-366.
    [25] 邸烁,郑纬民.并行WWW服务器集群请求分配算法的研究[J].软件学报 1999,10(7),713-718.
    [26] 雷迎春,张松,李国杰.Web集群服务器的分离式调度策略[J].计算机研究与发展,2002,39(9):1093-1098.
    [27] Huamin Chen, Prasant Mohapatra Session-Based Overload Control in QoS-Aware Web Servers. IEEE INFOCOM, Jun 2002.
    [28] Thiemo Voigt, Renu Tewari, Douglas Freimuth and Ashish Mehra. Kernel Mechanisms for Service Differentiation in Overloaded Web Servers. 2001 Usenix Annual Technical Conference, Boston, MA, USA, June 2001.
    [29] Vikram Kanodia, and Edward W. Knightly. Ensuring Latency Targets In Multi-Class Web Servers[J]. IEEE Transactions on Parallel and Distributed Systems, 2002, 13(10): 145-156.
    [30] Jakob Carlstrom, Raphael Rom. Application-aware Admission Control and Scheduling in Web Servers IEEE Infocom 2002.
    [31] V. Cardellini, E. Casalicchio, M. Colajanni, M. MambeHi, Enhancing a Web-server cluster with Quality of Service mechanisms, Prec. of 21st IEEE Int'l Performance, Computing, and Communications Conf. (IPCCC 2002), Phoenix, Arizona, April 2002.
    [32] V. Cardellini, E. Casalicchio, M. Colajanni. A performance study of distributed architectures for the quality of Web services, Proc. of Hawaii Int'l Conf. on System Sciences (HICSS-34), Software Technology Track, Maui, Jan. 2001. IEEE Computer Society.
    [33] L. Cherkasova, M. DeSouza, S. Ponnekanti. Performance Analysis of Content-Aware Load Balancing Strategy FLEX: Two Case Studies. In Proceedings of Thirty-Fourth Hawaii International Conference on System Sciences (HICSS-34), Software Technology Track, January 3-6, 2001.
    [34] Tarek Abdelzaher, Kang G. Shin, Nina Bhatti, Performance Guarantees for Web Server End-Systems: A Control-Theoretical Approach IEEE Transactions on Parallel and Distributed Systems[J]. 2002, 13(1): 23-31.
    [35] Jonghyuck Hong and Dongseung Kim Hierarchical Cluster for Scalable Web Servers. Proceedings of the 2001 IEEE International Conference on Cluster Computing.
    [36] L. Cherkasova, M. Karlsson: Scalable Web Server Cluster Design with WARD. In Proceedings of the Third International Workshop on Advanced issues of E-Commerce and Web-Based Information Systems (WECWIS'01), San Jose, June 20-21, 2001, 212-221.
    [37] M. Colajanni, P. S. Yu, V. Cardellini. Scalable Web-server systems: Architectures, models and load balancing algorithms. Tutorial presented at ACM Sigmetrics 2000, Santa Clara, CA, June 2000.
    [38] Schroeder T, Goddard S, and Ramamurthy B. Scalable Web server clustering technologies. IEEE Network, May/June 2000, 35~45.
    [39] W. Leland, M. Taqqu, W. Willinger, etc al. On the self-similar nature of ethernet traffic (extended version). IEEE/ACM Transactions on Networking [J]. 1994, 2 (1): 1-15.
    [40] A. Riska, E. Smirni, G. Ciardo. Analytic Modeling of Load Balancing Policies for Tasks with Heavy-tailed Distributions, in Proceedings of the 2000 ACM Workshop on Software and Performance, WOSP 2000, 147-157.
    [41] Paxson V, Floyd S. Wide area trfiic: the failure of passion modeling[J]. IEEE/ACM trans on Networking, 1995, 3 (3): 226-244.
    [42] Scott, Steven L. and Smyth. The Markov Modulated Poisson Process and Markov Poisson Cascade with Applications to Web Traffic Data. in Bayesian Statistics 7. Oxford University Press, 2003.
    [43] Crovella and Azer Bestavros. Self-Similarity in World Wide Web Traffic: Evidence and Possible Causes[J]. IEEE/ACM Transactions on Networking, 1997, 5(6): 835-846.
    [44] R. Bayya, D. Abramson, and J. Giddy, Nimrod/G: An Architecture for a Resource Management and Scheduling System in a Global Computational Grid, HPC ASIA'2000, China, IEEE CS Press, USA, 2000.
    [45] 董方鹏,龚奕利,李伟,查礼.网格环境中资源发现机制的研究[J].计算机研究与发展,2003,40(12):1749-1755.
    [46] 李伟,徐志伟,卜冠英等.网格环境下一种有效的资源查找方法[J].计算机学报,2002,26(11):1546-1549.
    [47] Foster I, Kesselman C, Lee C, Lindell R. A distributed resource management architecture that supports advance reservations and coallocation. In: Proceedings of the International Workshop on Quality of Service, London, 1999: 27-36.
    [48] 李伟,徐志伟.一种网格资源空间模型及其应用[J].计算机研究与发展,2003,40(12):1756-1762
    [49] Klein M, Bemstein A. Searching services on the semantic Web using process on tologies. In: Isabel C, ed. Proc. of the Int'l Semantic Web Working Symp. (SWWS2001), Amsterdam: IOS Press, 159-172.
    [50] J Hendler. Agents and semantic Web[J]. IEEE Intelligent Systems, 2001, 16(2): 20-37.
    [51] Ian Foster, Carl Kesselman. The Anatomy of the Grid-Enabling Scalable Virtual Organizations [J]. International Journal of Supercomputer Applications, 2001, 15(3): 200-222.
    [52] Czajkowski K, Fitzgerald S, Foster I, Kesselman C. Grid information services for distributed resource sharing. In: Proceedings of the 10thIEEE International Symposium on High Performance Distributed Computing (HPDC210), San Francisco, CA, 2001.
    [53] 廖华明,程伯羽,刘新周,虎嵩林,刘欣.信息网格中元数据层次化结构模型的研究和应用[J].计算机研究与发展,2003-40(12):1694-1699.
    [54] 杨广文,武永卫,朱晶.一种全局统一的层次化网格资源模型[J].计算机研究与发展,2003,40(12):1763-1769.
    [55] 冯百明,刘兴武,李伟.一种面向消费者的服务发现机制[J].计算机研究与发展.2003.40(12):1787-1790.
    [56] Klaus Krauter, Rajkumar Buyya, and Muthucumaru Maheswaran, A Taxonomy and Survey of Grid Resource Management Systems, Technical Report 2000/80: Mannitoba University (Canada) and Monash University (Australia), Nov. 2000.
    [57] Klein M, Bernstein A. Searching services on the semantic Web using process ontologies. In: Isabel C, ed. Proc. of the Int'l Semantic Web Working Symp. (SWWS2001). Amsterdam: IOS Press, 159-172.
    [58] 丁箐,陈国良,顾钧.计算网格环境下一个统一的资源映射策略[J].软件学报,2002,13(07):1303-1308.
    [59] 翁楚良,陆鑫达.一种基于市场机制的网格资源调价算法[J].计算机研究与发展,2004,41(7):1151-1156.
    [60] Nemo Semret. Market mechanisms for network resource sharing [PhD dissertation]. Columbia University, New York, 1999.
    [61] Rajkumar Buyya, David Abramson, and Jonathan Giddy, A Computational Economy for Grid Computing and its Implementation in the Nimrod-G Resource Broker, Future Generation Computer Systems (FGCS Journal, Elsevier Science, The Netherlands, 2002.
    [62] 曹鸿强,肖侬,卢锡城.一种基于市场机制的计算网格资源分配方法[J].计算机研究与发 展,2002,39(08):913-916.
    [63] Pai V S, Aron M, Banga G, Svendsen M. Locality-aware request distribution in cluster-based network servers. In Proceedings of the 8th ACM Conference on Architectural Support for Programming Languages and Operating Systems, 1998, ASPLOS Ⅷ: 205-216
    [64] W. Simpson. IP in IP Tunneling. RFC1853, 1995.
    [65] D Maltz. TCP splicing for application layer proxy performance. IBM, Tech Rep, RC21139, 1998.
    [66] J. Almeida, V Almeida, and D. Yates. Measuring the Behavior of a World-Wide Web Server. Technical Report TR-96-025, Boston University, CS Dept., Boston MA, 1996,
    [67] Martin F. Arlit and Carey L. Williamson. Web Server Workload Characterization: TheSearch for Invariants. In Proceedings of the ACM SIGME TRICS'96 Conference, Philadelphia, PA, May 1996. ACM. ftp://fto.cs.usask.ca/pub/discus/oater.96-3.ps.Z.
    [68] Cunha, C. A., A. Bestavros, and M. E. Crovella. Characteristics of WWW Client-basedTraces, Technical Report TR-95-010, Boston University Department of Computer Science, 1995. http://citeseer.nec.com/cunha95characterisfcs.html.
    [69] T Bu, D Towsley. On distinguishing between Internet power law topology generators. In Proc. of the IEEE INFOCOM 2002, Washington, IEEE Computer Society Press, 2002: 638-647. hap://www.cs.bu.edu/brite/.
    [70] Watts DJ, Strogatz SH. Collective dynamics of small-world networks[J]. Nature, 1998, 393: 440-442.
    [71] 雷迎春等.高性能L5-Dispatcher的性能评测[J].计算机研究与发展 2003,40(3).183-191.
    [72] Xiangping Chen and Prasant Mohapatra Performance Evaluation of Service Differentiating Internet Servers[J]. IEEE TRANSACTIONS ON COMPUTERS, 2002, 51 (11): 234-238
    [73] 金亮、陈志刚、张松.一种基于内容的可扩展性透明Web Cluster体系结构的设计[J].计算机工程 2004,30(7):101-103.
    [74] Gaurav Banga and Jeffrey C. Mogul Resource containers: A new facility for resource management in server systems Proceedings of the Third Symposium on Operating Systems Design and Implementation (OSDI'99), New Orleans, LA, February 1999.
    [75] L. Cherkasova, P. Phaal Session Based Admission Control: a Mechanism for Peak Load Management of Commercial Web Sites[J]. IEEE Journal Transactions on Computers. 2002, 51(6): 721-728.
    [76] Huican Zhu, Hong Tang and Tao Yang, Demand-driven Service Differentiation for Cluster-based Network Servers. IEEE INFOCOM 2001, 123-132.
    [77] Sclient http://www.cs.rice.edu/cs/systems/web-measurement/.
    [78] The LoadRunner http://www.mercury.com/us/products/performance-center/loadrunner/
    [79] W. Leland, M. Taqqu, W. Willinger, and D. Wilson. On the self-similar nature of ethernet traffic (extended version), IEEE/ACM Transactions on Networking[J]. 1994, 2(1): 1-15.
    [80] Luo Cang Chen Chnnjun Contradictory Relations between the Object in multi objective Optimization Problem[J]. Journal of South West Jiaotong university. 1999, 34(4). 471-475.
    [81] Shan Z, Lin C, Yang Y, Wang Y. Performance modeling and approximate analysis of multiserver multiqueue systems with Poisson and self-similar arrivals. Journal of University of Science and Technology Beijing, 2001, 8(2), 145~151.
    [82] 王兵,叶栋,丁炜 适应自相似业务流量模型的CAC算法研究.通信学报,2003,24(5):121-128.
    [83] Hans-Peter Schwefel and Lester Lipsky. Impact of Aggregated Self-Similar ON/OFF traffic on Delay in Stationary Queueing Models (Ext.Version)[A]. ERFORMANCE EVALUATION [OL]. 2000-05.
    [84] 陈卫东,杨建军.互联网通信中的两个数学模型及求解[J].计算机学报[J].1999,22(1).51-55.
    [85] Huican Zhu, Ben Smith and Tao Yang, Scheduling Optimization for Resource-Intensive Web Requests on Server Clusters, the Proceedings of the Eleventh Annual ACM Symposium on Parallel Algorithms and Architectures (SPAA'99), 13-22, Jun. 1999.
    [86] Martin Moser. Declarative Scheduling for optimally graceful QoS degradation. Tohoku University, TechRep: CSE-TR260-95, 1995.
    [87] M. M. Akbar, E. G. Manning, G. C. Shoja, S. Khan. Heuristic Solutions for the Multiple-Choice Multi-Dimension Knapsack Problem, International Conference on Computational Science, May 2001, San Francisco, USA.
    [88] P. Koleser, A Branch and Bound Algorithm for Knapsack Problem[J]. management Science, 1967, 13: 723-735.
    [89] R. Nauss. The 0-1 Knapsack Problem with Multiple Choice Constraints[J]. European Journal of Operation Research, 1978, 2: 125-131.
    [90] W. Shih. A branch and Bound Method for Multiconstraint Knapsack Problem[J]. Journal of the Operational Research Society, 1979, 30: 369-378.
    [91] Y. Toyoda. A Simplified Algorithm for Obtaining Approximate Solution to Zero-one Programming Problems[J]. management Science, 1971, 21: 1417-1427.
    [92] D. Andresen, T. Yang. Multiprocessor Scheduling with Client Resources to Improve the Response Time of WWW Applications. in Proc. of the 11th ACM SIGARCH International Conference on Supercomputing (ICS'97), 1997.
    [93] Mor Harchol-Balter, Bianca Schroeder, Nikhil Bansal, Mukesh Agrawal. Size-based Scheduling to Improve Web Performance[J]. ACM Transactions on Computer Systems, 2003, 21 (2): 207-233.
    [94] Michael Barabanov. A Linux2based Real2Time Operating System[D]. New Mexico: New Mexico Institute of Mining and Technology, Socorro, June 1997.
    [95] Jensen ED, Locke CD, Toduda H. A time-driven scheduling model for real-time operating systems. Proc. of the 6th IEEE Real-Time Systems Symp. San Diego: IEEE Computer Society Press, 1985. 112-122.
    [96] Buttazzo G; Spuri M, Sensini F. Value vs. deadline scheduling in overload conditions. Proc. of the 19th IEEE Real-Time Systems Symp. Pisa: IEEE Computer Society Press, 1995. 90-99.
    [97] wang yong-yan, wang qiang, etc. a real-time scheduling algorithm based on priority table and its implementation[J], journal of software(china) 2004, 15(3): 360-370.
    [98] Arun Iyengar, Mark S. Squillante, and Pi Zhang. Analysis and characterization of large-scale Web server access patterns and performance[J]. World Wide Web, 2(1-2): 85-100, 1999.
    [99] V. Holmedahl, B. Smith, and T. Yang. Cooperative Caching of Dynamic Content on a Distributed Web Server in Proc. of 7th IEEE International Symposium on High Performance Distributed Computing (HPDC-7) Chicago, USA July 28-31, 1998.: 243-250.
    [100] Cisco Systems Inc. Load balancing: a multifaceted solution for improving server avalability. White paper, 2000. http://www.cisco.corn/warp/public/cc/pd/cxsr/400/tech/lobal-wp.htm.
    [101] 曾碧卿,叶晓舟,陈志刚,刘安丰.Web集群系统可用度分析与设计研究[J].计算机工程,2005,31(9):112-114.
    [102] QIAN Fang JIA Yan A Dynamic Fault Tolerant Algorithm for Improving Performance of Redundant Services[J]. Journal of SoftWare 2001, 12(6): 928-935.
    [103] Rachid, G. Andre, S. Software-Based replication for fault tolerance[J]. IEEE Computer, 1997 30(4): 68-74.
    [104] Ying feng, Son Sang H. Scheduling hard real-time tasks with tolerance of multiple processor failures[J]. Microprocessing and Mcroprogramming, 1994, 40: 193-206.
    [105] Sylvain Lauzac, Rami Melhem. Adding fault-tolerance to P-Fair real-time scheduling. In: Workshop on Embedded Fault-Tolerant Systems 1998. 34-37.
    [106] 金海,邹德清,韩宗芬.基于Web的网格系统的实现[J].小型微型计算机系统 2003,24(12):2053-2056.
    [107] 黄道颖,黄建华等.基于主动网络的分布式P2P网络模型fJ].软件学报,2004,15(7):1081-1089.
    [108] I Foster, C Kesselman. The Globus project: A status report. In: Proc. of the IPPS/SPDP'98 Heterogeneous Computing Workshop. Orlando, IEEE Computer Society Press, 1998: 4-18. http://ipdps.eece.unm.edu/1998/hcw/foster.pdf.
    [109] SJ Chapin, D Katramatos, J Karpovich et al. Resource management in legion[J]. Future Generation Computer Systems, 1999, 15 (5-6): 583-594.
    [110] MJ Litzkow, M Livny, MW Mutka. Condor—A hunter of idle workstations. In: Proc. of 8th Int'l Conf on Distributed Computing Systems. Washington: IEEE Computer Society Press, 1988. 104-110. http://www.cse.Ohio-state.edu/~lauria/cis788/papers/condor.pdf.
    [111] Rowstron A, Druschel P. Pastry: Scalable, distributed object location and routing for large-scale peer-to-peer systems. In: Guerraoui R, ed. Proc. of the Middleware 2001. Heidelberg: Springer-Verlag, 2001. 329~350.
    [112] Ratnasamy S, Francis P, Handley M, Karp R, Shenker S. A scalable content-addressable network. In: Govindan R, ed. Proc. of the ACM SIGCOMM 2001. ACM Press, 2001. 161~172.
    [113] J Mischke. Rich and scalable peer-to-peer search with SHARK. In: The 5th Int'l Workshop on Active Middleware Services. Washington: IEEE Computer Press, 20031. 112~122. Napster. 2003. http://www.napster.com.
    [114] Zhou J, Lu HM, Li YD. Using small-world to devise routing algorithm for unstructured peer-to-peer system[J]. Journal of Software, 2004, 15(6): 915~923.
    [115] 窦文,王怀民.模拟谣言传播机制的无结构P2P网络中广播机制的研究[J].计算机研究与发展 2004,41(9):1460-1465.
    [116] 凌波,陆志国等.PeerlS:基于Peer-to-Peer的信息检索系统软件学报[J].2004,15(9):1375-1384.
    [117] T Bu, D Towsley. On distinguishing between Internet power law topology generators. In Proc. of the IEEE INFOCOM 2002, Washington, IEEE Computer Society Press, 2002: 638-647. http://www.cs.bu.edu/brite/.
    [118] Seungh H, Yuck. ImpIemenhtion of a bandwidth allocation scheme in a token—passing fieldbus network[J]. IEE Transactions on Instrumentation and Measurement, 2002, 51 (2): 246-251.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700