An experimental evaluation of self-managing availability in shared data spaces

Abstract

With its decoupling of processes in space and time, the shared data space model has proven to be a well-suited solution for developing distributed component-based systems. However, as in many distributed applications, functional and extra-functional aspects are still interwoven in components. In this paper, we address how shared data spaces can support the separation of concerns. In particular, we present a solution that allows developers to merely specify availability requirements for data tuples, while the underlying middleware evaluates various distribution and replication policies in order to select the one that meets these requirements best. Moreover, in our approach, the middleware continuously monitors the behavior of application and system components, and switches to different policies if this would lead to better results. We describe our approach, along with the design of a prototype implementation and its quantitative evaluation.

Decision Support-Related Resource Presence and Availability Awareness for DSS in Pervasive Computing Environments

“…Roughan et al (2004) propose how combining routing and traffic data can be used to detect network anomalies. Russello et al (2007) provide a comprehensive hardware solution for managing network-distributed data that is policy based. Their approach allows application developers to specify availability requirements for data tuples, while an underlying middleware evaluates various distribution and replication policies to select the one that best meets the developer's requirements.…”