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Autonomous State-Management Support in Distributed Self-adaptive Systems

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Abstract

Modern systems are increasingly required to be adaptable in order to handle constantly changing environments. Adaptability is often based on the ability to adapt the behaviour of a running system where multiple implementations are available. Example of this are technologies such as reflective middleware and meta-models which offer control over how logic is wired together. While these technologies support high degrees of autonomous flexibility around the compute element of distributed systems, they completely neglect handling state} in an externally-managed, automated way. This paper advocates a reflective model over system state, to complement existing models that enable meta-management of behaviour. This concept has the potential to support an entirely new dimension of self-adaptive systems, offering a richer set of options to compose a system. We demonstrate a possible implementation of this concept by extending a lightweight component-based model; our implementation can transparently and generically relocate, replicate, and shard stateful components. Using a set of annotations, our framework constructs a pool of possible compositions which distribute any system using a variety of different state management options. We posit that this offers an unexplored dimension of self-adaptive systems, supporting novel concepts such as self-distributing systems which can emerge to best match their environment.

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©2020 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.