A Model for Intelligent Adaptation and Evolution of Polymorphic Services

The highly dynamic nature and ubiquity of contemporary computer environments requires services to adapt and evolve to match varying contexts. Such services can be referred to as polymorphic since they can deliver their functionality in different forms. This paper proposes a fuzzy-based model for intelligent adaptation and evolution of polymorphic services based on context. Context is represented by parameters whose values fluctuate dynamically and their characteristics, such as range and mean, can evolve in time. Service adaptation is realized by selecting suitable service provision policies depending on context parameter configurations. The suitability of each service provision policy is determined by qualitative criteria which are estimated by fuzzy rules applied on context parameter values. Evolution is realized by having the fuzzy rule structure and parameters altered dynamically to align with evolved context. The applicability of the proposed approach is demonstrated in a traffic management case study.