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.

Engineering emergence for cluster configuration

Distributed applications are being deployed on ever-increasing scale and with ever-increasing functionality. Due to the accompanying increase in behavioural complexity, self-management abilities, such as self-healing, have become core requirements. A key challenge is the smooth embedding of such functionality into our systems. Natural distributed systems such as ant colonies have evolved highly efficient behaviour. These emergent systems achieve high scalability through the use of low complexity communication strategies and are highly robust through large-scale replication of simple, anonymous entities. Ways to engineer this fundamentally non-deterministic behaviour for use in distributed applications are being explored. An emergent, dynamic, cluster management scheme, which forms part of a hierarchical resource management architecture, is presented. Natural biological systems, which embed self-healing behaviour at several levels, have influenced the architecture. The resulting system is a simple, lightweight and highly robust platform on which cluster-based autonomic applications can be deployed.

A future dynamically reconfigurable automotive software system

Embedded software systems in vehicles are of rapidly increasing commercial importance for the automotive industry. Current systems employ a static run-time environment; due to the difficulty and cost involved in the development of dynamic systems in a high-integrity embedded control context. A dynamic system, referring to the system configuration, would greatly increase the flexibility of the offered functionality and enable customised software configuration for individual vehicles, adding customer value through plug-and-play capability, and increased quality due to its inherent ability to adjust to changes in hardware and software. We envisage an automotive system containing a variety of components, from a multitude of organizations, not necessarily known at development time. The system dynamically adapts its configuration to suit the run-time system constraints. This paper presents our vision for future automotive control systems that will be regarded in an EU research project, referred to as DySCAS (Dynamically Self-Configuring Automotive Systems). We propose a self-configuring vehicular control system architecture, with capabilities that include automatic discovery and inclusion of new devices, self-optimisation to best-use the processing, storage and communication resources available, self-diagnostics and ultimately self-healing. Such an architecture has benefits extending to reduced development and maintenance costs, improved passenger safety and comfort, and flexible owner customisation. Specifically, this paper addresses the following issues: The state of the art of embedded software systems in vehicles, emphasising the current limitations arising from fixed run-time configurations; and the benefits and challenges of dynamic configuration, giving rise to opportunities for self-healing, self-optimisation, and the automatic inclusion of users’ Consumer Electronic (CE) devices. Our proposal for a dynamically reconfigurable automotive software system platform is outlined and a typical use-case is presented as an example to exemplify the benefits of the envisioned dynamic capabilities.

Emergent self-organisation of wireless sensor networks

This paper describes a protocol for dynamically configuring wireless sensor nodes into logical clusters. The concept is to be able to inject an overlay configuration into an ad-hoc network of sensor nodes or similar devices, and have the network configure itself organically. The devices are arbitrarily deployed and have initially have no information whatsoever concerning physical location, topology, density or neighbourhood. The Emergent Cluster Overlay (ECO) protocol is totally self-configuring and has several novel features, including nodes self-determining their mobility based on patterns of neighbour discovery, and that the target cluster size is specified externally (by the sensor network application) and is not directly coupled to radio communication range or node packing density. Cluster head nodes are automatically assigned as part of the cluster configuration process, at no additional cost. ECO is ideally suited to applications of wireless sensor networks in which localized groups of sensors act cooperatively to provide a service. This includes situations where service dilution is used (dynamically identifying redundant nodes to conserve their resources).

Towards policy-based self-configuration of embedded systems

This paper describes work towards the deployment of flexible self-management into real-time embedded systems. A challenging project which focuses specifically on the development of a dynamic, adaptive automotive middleware is described, and the specific self-management requirements of this project are discussed. These requirements have been identified through the refinement of a wide-ranging set of use cases requiring context-sensitive behaviours. A sample of these use-cases is presented to illustrate the extent of the demands for self-management. The strategy that has been adopted to achieve self-management, based on the use of policies is presented. The embedded and real-time nature of the target system brings the constraints that dynamic adaptation capabilities must not require changes to the run-time code (except during hot update of complete binary modules), adaptation decisions must have low latency, and because the target platforms are resource-constrained the self-management mechanism have low resource requirements (especially in terms of processing and memory). Policy-based computing is thus and ideal candidate for achieving the self-management because the policy itself is loaded at run-time and can be replaced or changed in the future in the same way that a data file is loaded. Policies represent a relatively low complexity and low risk means of achieving self-management, with low run-time costs. Policies can be stored internally in ROM (such as default policies) as well as externally to the system. The architecture of a designed-for-purpose powerful yet lightweight policy library is described. A suitable evaluation platform, supporting the whole life-cycle of feasibility analysis, concept evaluation, development, rigorous testing and behavioural validation has been devised and is described.