Decentralised Autonomic Computing: Analysing Self-Organising Emergent Behaviour using Advanced Numerical Methods

When designing decentralised autonomic computing systems, a fundamental engineering issue is to assess system-wide behaviour. Such decentralised systems are characterised by the lack of global control, typically consist of autonomous cooperating entities, and often rely on self-organised emergent behaviour to achieve the requirements. A well-founded and practically feasible approach to study overall system behaviour is a prerequisite for successful deployment. On one hand, formal proofs of correct behaviour and even predictions of the exact system-wide behaviour are practically infeasible due to the complex, dynamic, and often nondeterministic nature of self-organising emergent systems. On the other hand, simple simulations give no convincing arguments for guaranteeing system-wide properties. We describe an alternative approach that allows to analyse and assess trends in system-wide behaviour, based on so-called "equation-free" macroscopic analysis. This technique yields more reliable results about the system-wide behaviour, compared to mere observation of simulation results, at an affordable computational cost. Numerical algorithms act at the system-wide level and steer the simulations. This allows to limit the amount of simulations considerably. We illustrate the approach by studying a particular system-wide property of a decentralised control system for automated guided vehicles and we outline a road map towards a general methodology for studying decentralised autonomic computing systems