Optimal adaptation in web processes with coordination constraints

We present methods for optimally adapting Web processes to exogenous events while preserving inter-service constraints that necessitate coordination. For example, in a supply chain process, orders placed by a manufacturer may get delayed in arriving. In response to this event, the manufacturer has the choice of either waiting out the delay or changing the sup-plier. Additionally, there may be compatibility constraints between the different orders, thereby introducing the problem of coordination between them if the manufacturer chooses to Web process flow is pre-specified, and service managers are tasked with interacting with the actual Web services. We fo-cus on the decision making models of the managers who must adapt to external events while satisfying the coordination con-straints. We use Markov decision processes as the underlying models for the managers, and show how they can be formu-lated offline resulting in policies that guide the managers ’ ac-tions. Our methods range from being centralized and globally optimal in their adaptation but not scalable, to decentralized that is suboptimal but scalable to multiple managers. We also develop a hybrid approach that improves on the performance of the decentralized approach with a minimal loss of scalabil-ity