A genetic algorithm for the adaptation of service compositions

The view on applications in large-scale open systems shifted to a service-oriented perspective, where each functional feature forming an application is regarded as service. The services which constitute an application can be physically spread over different network nodes and can be even provided by different administrative entities. According to the vision of the BIONETS project we are additionally facing a dynamically changing computing environment, which entails a dynamically changing set of available services. We investigate how service compositions, on which novel applications are based on, can flexibly be adapted to the changing conditions in the computing environment, while going beyond late-binding mechanisms. We apply methods of genetic programming to modify the structures describing service compositions to find compensation for types of services no longer available to applications. In this paper, we describe the current state of our efforts on complex algorithms for service composition transformation, based on the application of genetic operators to graph based service composition representations.