Evolving service-orientated architectures

A novel optimisation technique inspired by natural ecosystems is presented, where the optimisation works at two levels: a first optimisation, migration of services which are distributed in a decentralised peer-to-peer network, operating continuously in time; this process feeds a second optimisation based on evolutionary computing that operates locally on single peers and is aimed at finding solutions to satisfy locally relevant constraints. Through this twofold process, the local search is accelerated and will yield better local optima, because the distributed optimisation already provides a good sampling of the search space by making use of computations already performed in other peers with similar constraints. We call this new distributed optimisation architecture a Digital Ecosystem, an Ecosystem-Orientated Architecture (EOA) created by extending a Service-Oriented Architecture (SOA) with Distributed Evolutionary Computing (DEC). The Digital Ecosystem will allow services to recombine and evolve over time, constantly seeking to improve their effectiveness for the user base. Individuals within our Digital Ecosystem will be applications (groups of services), created in response to user requests by using evolutionary optimisation to aggregate the services. These individuals will migrate through the Digital Ecosystem and adapt to find niches where they are useful in fulfilling other user requests.