Adaptation and Abstract Runtime Models

TL;DR

This paper introduces a model-driven approach that maintains multiple abstract runtime models at different levels and concerns, enhancing adaptability, reusability, and extensibility in complex software systems.

Contribution

It proposes a novel multi-model, multi-level abstraction framework for runtime adaptation, improving reusability and concern coverage compared to existing low-level models.

Findings

Implemented for Enterprise Java Beans standard

Supports self-healing with structural adaptation

Reduces development efforts through model-driven engineering

Abstract

Runtime adaptability is often a crucial requirement for today's complex software systems. Several approaches use an architectural model as a runtime representation of a managed system for monitoring, reasoning and performing adaptation. To ease the causal connection between a system and a model, these models are often closely related to the implementation and at a rather low level of abstraction. This makes them as complex as the implementation and it impedes reusability and extensibility of autonomic managers. Moreover, the models often do not cover different concerns, like security or performance, and therefore they do not support several self-management capabilities at once. In this paper we propose a model-driven approach that provides multiple architectural runtime models at different levels of abstraction as a basis for adaptation. Each runtime model abstracts from the underlying system and platform leveraging reusability and extensibility of managers that work on these models. Moreover, each model focuses on a specific concern which simplifies the work of autonomic managers. The different models are maintained automatically at runtime using model-driven engineering techniques that also reduce development efforts. Our approach has been implemented for the broadly adopted Enterprise Java Beans component standard and its application is presented in a self-healing scenario requiring structural adaptation.