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Data Driven Adaptation of Service Oriented Processes

Data-Driven process adaptation accommodates the provision of adaptable service processes by exploiting the use of information available to the process environment in addition to existing services. Adaptation in the context of our approach includes the identification and use of possible alternatives for the achievement of the goals and sub-goals defined in a process; alternatives include the utilization of available related information and/or services (or service chains). Data-Driven adaptation incorporates AI planning and Context-Aware Computing techniques to support the identification of possible alternatives at deployment time. When calculating the possible alternatives the goal of our approach is to reduce the number of steps, i.e. number of process tasks, defined in the original process.

More specifically our approach models the problem of discovering alternate process paths as a non-deterministic, partially observable planning problem and uses model based planning (MBP) techniques to resolve it. The problem of information collection and exchange is resolved using a semantically enhanced Tuplespace model. In addition to the combined use of these two techniques, focal with respect to the provided set of features are: a) the specification of appropriate process variables for the management of related information and the discovery of alternate process paths that can exploit this information as well as, b) the expansion of the process variable (i.e. observations) and available service (i.e. actions) sets using semantically-based distance measurements along with appropriate heuristics.


Related Papers:
Pantazoglou M., Athanasopoulos G., Tsalgatidou A., and Kouki P., 2014. Distributed and adaptive business process execution: a scalable and performant solution architecture, Handbook of research on architectural trends in service-driven computing, Chapter 3, pp. 42-72, R. Ramanathan, K. Raja IGI Global ISBN: DOI: 10.4018/978-1-4666-6178-3.ch003.


Athanasopoulos G., and Tsalgatidou A., 2010. An Approach to Data-Driven Adaptable Service Processes, An Approach to Data-Driven Adaptable Service Processes, July 2010, proceedings of International Conference on Software and Data Technologies (ICSOFT2010).