Natural inspiration for self-adaptive systems

The emergent behaviour of autonomic systems, together with the scale of their deployment, impedes prediction of the full range of configuration and failure scenarios; thus it is not possible to devise management and recovery strategies to cover all possible outcomes. One solution to this problem is to embed self-managing and self-healing abilities into such applications. Traditional design approaches favour determinism, even when unnecessary. This can lead to conflicts between the non-functional requirements. Natural systems such as ant colonies have evolved cooperative, finely tuned emergent behaviours which allow the colonies to function at very large scale and to be very robust, although non-deterministic. Simple pheromone-exchange communication systems are highly efficient and are a major contribution to their success. This paper proposes that we look to natural systems for inspiration when designing architecture and communications strategies, and presents an election algorithm which encapsulates non-deterministic behaviour to achieve high scalability, robustness and stability.

Identification and doing without it, V: A formal mathematical analysis for a case of mix-up of individuals, and of recovery from failure to attain identification

Identification, when sought, is not necessarily obtained. Operational guidance that is normatively acceptable may be necessary for such cases. We proceed to formalize and illustrate modes of exchanges of individual identity, and provide procedures of recovery strategies in specific prescriptions from an ancient body of law for such situations when, for given types of purposes, individuals of some relevant kind had become intermixed and were undistinguishable. Rules were devised, in a variety of domains, for coping with situations that occur if and when the goal of identification was frustrated. We propose or discuss mathematical representations of such recovery procedures.

On the persistence of computer dreams: an application framework for robust adaptive deployment

The anticipated rewards of adaptive approaches will only be fully realised when autonomic algorithms can take configuration and deployment decisions that match and exceed those of human engineers. Such decisions are typically characterised as being based on a foundation of experience and knowledge. In humans, these underpinnings are themselves founded on the ashes of failure, the exuberance of courage and (sometimes) the outrageousness of fortune. In this paper we describe an application framework that will allow the incorporation of similarly risky, error prone and downright dangerous software artefacts into live systems – without undermining the certainty of correctness at application level. We achieve this by introducing the notion of application dreaming.