Towards a case-based reasoning approach to dynamic adaptation for large-scale distributed systems

Abstract

The ever growing demands from the software area have led to the development of large-scale distributed systems which bring together a wide pool of services and resources. Their composition and deployment come in different solutions tailored to users requests based on business models, functionality, quality of service, cost, and value. Bridging different parts into one software solution is brittle due to issues like heterogeneity, complexity, lack of transparency, network and communication failures, and misbehavior. The current paper proposes a decision-based solution for the dynamic adaptation part of a middleware which addresses the aforementioned problems for large-scale distributed systems. The envisioned architecture is built on case-based reasoning principles and stands at the base of the adaptation processes that are imperative for ensuring the delivery of high-quality software. The solution is further extended through ground models with a focus on reliability, availability of components, and failure tolerance in terms of abstract state machines. The novelty of the approach resides in making use of formal modeling for one of the emerging problems and introducing an adequate prototype, on top of which one can apply reasoning and verification methods.