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Issue No.03 - July-September (2008 vol.1)
pp: 169-185
John Harney , University of Georgia, Athens
Prashant Doshi , University of Georgia, Athens
Web service composition (WSC) techniques assume that the parameters used to model the environment remain static and accurate throughout the composition's execution. However, WSCs often operate in environments where the parameters of its component services are volatile. To remain optimal, WSCs must adapt to these changes. Adaptation requires up-to-date knowledge about the revised parameters of each of the services. One way of obtaining this knowledge is to query services for their revised parameters. Querying services for their parameters is time-consuming and expensive. We must therefore carefully manage how queries are conducted. Specifically, an adaptive WSC must know when to query for revised information, and from which service(s) to obtain information. We present a method to selectively query services using the value of changed information (VOC). VOC measures the value of the change that revised information may potentially introduce to the composition. We reduce the complexity of computing the VOC, first by anticipating values of the service parameters that do not change the WSC, and second by using parameter expiration times obtained from predefined service-level agreements. Using two scenarios, we illustrate our approach and demonstrate the computational savings theoretically and experimentally.
Value of information, Optimization of Services Composition
John Harney, Prashant Doshi, "Selective Querying for Adapting Web Service Compositions Using the Value of Changed Information", IEEE Transactions on Services Computing, vol.1, no. 3, pp. 169-185, July-September 2008, doi:10.1109/TSC.2008.11
[1] J. Harney and P. Doshi, “Adaptive Web Processes Using Value of Changed Information,” Proc. Fourth Int'l Conf. Service-Oriented Computing (ICSOC '06), pp. 179-190, 2006.
[2] J. Harney and P. Doshi, “Speeding Up Adaptation of Web Service Compositions Using Expiration Times,” Proc. 16th Int'l Conf. World Wide Web (WWW '07), pp. 1023-1032, 2007.
[3] W.M.P. van der Aalst and S. Jablonski, “Dealing with Workflow Change: Identification of Issues and Solutions,” Int'l J. Computer Systems Science and Eng., vol. 15, no. 5, pp. 267-276, Sept. 2000.
[4] A.S.Y. Han and C. Bussler, “A Taxonomy of Adaptive Workflow Management,” Proc. ACM Conf. Computer-Supported Cooperative Work (CSCW), 1998.
[5] A. Borgida and T. Murata, “Tolerating Exceptions in Workflows: A Unified Framework for Data and Processes,” Proc. Int'l Joint Conf. Work Activities Coordination and Collaboration (WACC '99), pp. 59-68, 1999.
[6] N. Desai, A.K. Chopra, and M.P. Singh, “Business Process Adaptations via Protocols,” Proc. Third IEEE Int'l Conf. Services Computing (SCC '06), pp. 601-608, 2006.
[7] D.M. Strong and S.M. Miller, “Exceptions and Exception Handling in Computerized Information Processes,” ACM Trans. Information Systems, vol. 13, no. 2, pp. 206-233, 1995.
[8] M. Brambilla, S. Ceri, S. Comai, and C. Tziviskou, “Exception Handling in Workflow-Driven Web Applications,” Proc. 14th Int'l Conf. World Wide Web (WWW '05), pp. 170-179, 2005.
[9] Z. Luo, A.P. Sheth, K. Kochut, and J.A. Miller, “Exception Handling in Workflow Systems,” Applied Intelligence, vol. 13, no. 2, pp. 125-147, 2000.
[10] R. Muller, U. Greiner, and E. Rahm, “Agentwork: A Workflow System Supporting Rule-Based Workflow Adaptation,” J. Data and Knowledge Eng., vol. 51, no. 2, pp. 223-256, 2004.
[11] N.C. Narendra and S. Gundugola, “Automated Context-Aware Adaptation of Web Service Executions,” Proc. Fourth ACS/IEEE Int'l Conf. Computer Systems and Applications (AICCSA '06), pp.179-187, 2006.
[12] Z. Maamar, N.C. Narendra, D. Benslimane, and S. Sattanathan, “Policies for Context-Driven Transactional Web Services,” Proc. 19th Int'l Conf. Advanced Information Systems Eng. (CAiSE'07), pp. 249-263, 2007.
[13] M. Reichert and P. Dadam, “Adeptflex-Supporting Dynamic Changes of Workflows without Losing Control,” J. Intelligent Information Systems, vol. 10, no. 2, pp. 93-17, 1998.
[14] E.A. Stohr and J.L. Zhao, “A Technology Adaptation Model for Business Process Automation,” Proc. 30th Hawaii Int'l Conf. System Sciences (HICSS '97), vol. 4, pp. 405-414, 1997.
[15] W.M.P. van der Aalst, “Exterminating the Dynamic Change Bug: A Concrete Approach to Support Workflow Change,” Information Systems Frontiers, vol. 3, no. 3, pp. 297-317, 2001.
[16] A. Sheth, J. Cardoso, J. Miller, and K. Kochut, “QoS for Service-Oriented Middleware,” Proc. Sixth World Multiconf. Systemics, Cybernetics and Informatics (SCI '02), pp. 528-534, 2002.
[17] G. Chafle, K. Dasgupta, A. Kumar, S. Mittal, and B. Srivastava, “Adaptation in Web Service Composition and Execution,” Proc. IEEE Int'l Conf. Web Services (ICWS '06), pp. 549-557, 2006.
[18] G. Chafle, P. Doshi, J. Harney, S. Mital, and B. Srivastava, “Improved Adaptation of Web Service Compositions Using Value of Changed Information,” Proc. IEEE Int'l Conf. Web Services (ICWS'07), Industry Track, pp. 784-791, 2007.
[19] H. Paques, L. Liu, and C. Pu, “Adaptation Space: A Design Framework for Adaptive Web Services,” Int'l J. Web Service Research, vol. 1, no. 3, pp. 1-24, 2004.
[20] P. Doshi, R. Goodwin, R. Akkiraju, and K. Verma, “Dynamic Workflow Composition Using Markov Decision Processes,” Int'l J. Web Service Research, vol. 2, no. 1, pp. 1-17, 2005.
[21] T.-C. Au, D.S. Nau, and V.S. Subrahmanian, “Utilizing Volatile External Information During Planning,” Proc. 16th European Conf. Artificial Intelligence (ECAI '04), pp. 647-651, 2004.
[22] T.-C. Au, U. Kuter, and D.S. Nau, “Web Service Composition with Volatile Information,” Proc. Ninth IEEE Int'l Symp. Wearable Computers (ISWC '05), pp. 52-66, 2005.
[23] T.-C. Au and D. Nau, “Reactive Query Policies: A Formalism for Planning with Volatile External Information,” Proc IEEE Symp. Computational Intelligence and Data Mining (CIDM '07), pp. 243-250, 2007.
[24] D. Gotz and K. Mayer-Patel, “A General Framework for Multidimensional Adaptation,” Proc. IEEE Int'l Conf. Multimedia and Expo (ICME '04), 612-619-126, 2004.
[25] N.C. Narendra, K. Ponnalagu, J. Krishnamurthy, and R. Ramkumar, “Run-Time Adaptation of Non-Functional Propertiesof Composite Web Services Using Aspect-Oriented Programming,” Proc. Fifth Int'l Conf. Service-Oriented Computing (ICSOC '07), pp.546-557, 2007.
[26] A. Charfi and M. Mezini, “Aspect-Oriented Web Service Composition with ao4bpel,” Proc. European Conf. Web Services (ECOWS '04), pp. 168-182, 2004.
[27] K. Gomadam, A. Ranabahu, L. Ramaswamy, A.P. Sheth, and K. Verma, “A Semantic Framework for Identifying Events in a Service Oriented Architecture,” Proc. IEEE Int'l Conf. Web Services (ICWS '07), pp. 545-552, 2007.
[28] K. Verma, P. Doshi, K. Gomadam, J. Miller, and A. Sheth, “Optimal Adaptation in Web Processes with Coordination Constraints,” Proc. IEEE Int'l Conf. Web Services (ICWS '06), pp.257-264, 2006.
[29] Y. Wu and P. Doshi, “Regret-Based Decentralized Adaptation of Web Processes with Coordination Constraints,” Proc. Fourth IEEE Int'l Conf. Services Computing (SCC '07), pp. 262-269, 2007.
[30] Microsoft, “Enabling an Adaptable, Aligned, and Agile Supply Chain with Biztalk Server and Rosettanet Accelerator,” technical report, contentscmbiztalktcs.mspx, 2005.
[31] V. Agarwal, G. Chafle, K. Dasgupta, N.M. Karnik, A. Kumar, S. Mittal, and B. Srivastava, “Synthy: A System for End to End Composition of Web Services,” J. Web Semantics, vol. 3, no. 4, pp. 311-339, 2005.
[32] M.L. Puterman, Markov Decision Processes. John Wiley & Sons, 1994.
[33] S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, second ed. Prentice Hall, 2003.
[34] T.M. Mitchell, Machine Learning. McGraw-Hill, 1997.
[35] B. Bojanov, H. Halcopian, and A. Sabakian, Spline Functions and Multivariate Interpolations. Kluwer Academic Publishers, 1993.
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