Mercury: multi-agent adaptive service selection based on non-functional attributes

Service selection in an SOA is primarily based on matching functional requirements to those advertised by the services. The focus of this paper is on selecting, from those functionally capable services, the best service in terms of its non-functional attributes. We propose an adaptive multi-agent framework, Mercury, which involves collaborative modelling of the service landscape based on consumer experience of service quality. The framework introduces several mechanisms to enable the system to be adaptive, and thus effective in highly dynamic scenarios. In particular, different strategies of information exchange between selector agents are investigated with the aim of maximising the speed of adaptation while minimising unfavourable competition between consumers. Combined with adaptive exploitation-exploration control, this allows the selection mechanism to improve the QoS delivered in the presence of strong demand/supply fluctuations and possible service overloading, thus improving the overall operation of an SOA