A Model and Algorithm for Self-Adaptation in Service-oriented Systems

Abstract

Abstract-In this paper, we address the problem of selfadaptation in internet-scale service-oriented systems. Services need to adapt by select the best neighboring services solely based on local, limited information. In such complex systems, the global significance of the various selection parameters dynamically changes. We introduce a novel metric measuring the distribution and potential impact of service properties affecting such selection parameters. We further present an formalism identifying the most significant properties based on aggregated service interaction data. We ultimately provide a ranking algorithm exploiting these dynamic interaction characteristics. Experimental evaluation demonstrates scalability and adaptiveness of our approach.

Interaction-Driven Self-adaptation of Service Ensembles

“…One important structural property of service ensembles is the number and the size of subgroups that emerge from the interaction distance graph and what factors cause this structure. Graph analysis based on interaction affinities (e.g., [19]) or community detection algorithms (e.g., [20] or [21]) describes the underlying structure from which we subsequently derive appropriate system requirements. Fig.…”

WSARCH: Uma arquitetura para a provisão de web services com qualidade de serviço

“…O problema de adaptação baseada em QoS é tratado em (Dorn et al, 2009). Os autores abordam o problema de auto-adaptação em sistemas orientados a serviços de larga-escala.…”