Modeling Service Availability in Web Clusters Architectures

• Magnos Martinello FUCAPE
• Mohamed Kaâniche LAAS-CNRS
• Karama Kanoun LAAS-CNRS

DOI: https://doi.org/10.5753/wtf.2006.23353

Resumo

Internet is often used for transaction based applications such as online banking, stock trading, among many others where the service outages are unacceptable. It is important for designers of such applications to analyze how hardware, software and performance related failures affect the quality of service delivered to the users. This paper presents analytical models for evaluating the service availability of web cluster architectures. A composite performance and availability modeling approach is defined considering various causes of service unavailability. In particular, web cluster systems are modeled taking into account: two recovery strategies (client transparent and non client-transparent). Sensitivity analysis results are presented to show their impact on the web service availability. The obtained results are aimed at providing useful guidelines to web designers.

Palavras-chave: Modeling, availability, fault tolerance, web clusters

Referências

N. Aghdaie and Y. Tamir. Client-Transparent Fault-Tolerant Web Service. IEEE International Performance, Computing, and Communications Conference, pages 209–216, 2001.

L. Aversa and A. Bertavros. Load balancing a cluster of web servers using distributed packet rewriting. IEEE International Performance, Computing and Communication Conference, pages 24–29, 2000.

G. Bolch, S. Greiner, H. de Meer, and K. S. Trivedi. Queueing Networks and Markov Chains. John Willey and Sons, Inc., 1998.

E.A. Brewer. Lessons from Giant-Scale Service. IEEE Internet Computing, pages 46–55, 2001.

T. Brisco. DNS support for load balancing . IETF RFC 1794, 1995.

D. Patterson E. Anderson and E. Brewer. The MagicRouter, an application of fast packet interposing. http://www.cs.berkeley.edu, 1996.

S. Garg, Y. Huang, C.M.R. Kintala, K.S. Trivedi, and S. Yajnik. Performance and Reliability Evaluation of Passive Replication Schemes in Application Level Fault Tolerance. IEEE Dependable Systems and Networks, 1999.

Cisco Systems Inc. Failover Configuration for LocalDirector. http://www.cisco.com, 2000.

M. Kalyanakrishnan, R. K. Iyer, and J. U. Patel. Reliability of Internet Hosts: a Case Study from the End User’s Perspective. Computer Networks, (31):47–57, 1999.

M. Y. Luo and C. S. Yang. Enabling fault resilience for web services. Computer Communications, (25):198–209, 2002.

M. Martinello. Availability Modeling and Evaluation of Web-based Services : A Pragmatic Approach. PhD thesis LAAS-CNRS, 2005.

M. Martinello, M. Kaâniche, and K.Kanoun. Web Service Availability : Impact of Error Recovery and Traffic Model. Journal of Reliability Engineering and System Safety (RESS), 89(1):6–16, 2005.

J. F. Meyer. On evaluating the performability of degradable computing systems. IEEE Journal on Selected Areas in Communications, 29(8):720–731, 1980.

J. F. Meyer. Closed-form solutions of performability. IEEE Transactions on Computing, 7(31):648–657, 1982.

R. Morris and D. Lin. Variance of aggregated web traffic. IEEE Infocom, 2000.

K. Nagaraja, G. M. C. Gama, R. Bianchini, R. P. Martin, W. Meira, and T. D. Nguyen. Quantifying the Performability of Cluster-Based Services. IEEE Transactions on Parallel and Distributed System, 5(16):456–467, 2005.

D. Oppenheimer and D. A. Patterson. Architecture and Dependability of Large-Scale Internet Services. IEEE Internet Computing, pages 41–49, 2002.

M. Colajanni V. Cardellini, E. Casalicchio and P. S. Yu. The state of the art in Locally Distributed Web-Server System. ACM Computing Surveys, 34(2):363–371, 2002.

W. Willinger and V. Paxson. Where Mathematics meets the Internet. Notices of the American Mathematical Society, 45(8):961–970, 1998.

R. Wolff. Poisson arrivals see time averages. Operations Research, (30):223–231, 1982.