Emergence: a paradigm for robust and scalable distributed applications

Natural distributed systems are adaptive, scalable and fault-tolerant. Emergence science describes how higher-level self-regulatory behaviour arises in natural systems from many participants following simple rulesets. Emergence advocates simple communication models, autonomy and independence, enhancing robustness and self-stabilization. High-quality distributed applications such as autonomic systems must satisfy the appropriate nonfunctional requirements which include scalability, efficiency, robustness, low-latency and stability. However the traditional design of distributed applications, especially in terms of the communication strategies employed, can introduce compromises between these characteristics. This paper discusses ways in which emergence science can be applied to distributed computing, avoiding some of the compromises associated with traditionally-designed applications. To demonstrate the effectiveness of this paradigm, an emergent election algorithm is described and its performance evaluated. The design incorporates nondeterministic behaviour. The resulting algorithm has very low communication complexity, and is simultaneously very stable, scalable and robust.

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.

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.

Generic support for policy-based self-adaptive systems

This paper presents a policy definition language which forms part of a generic policy toolkit for autonomic computing systems in which the policies themselves can be modified dynamically and automatically. Targeted enhancements to the current state of practice include: policy self-adaptation where the policy itself is dynamically modified to match environmental conditions; improved support for non autonomics-expert developers; and facilitating easy deployment of adaptive policies into legacy code. The policy definition language permits powerful expression of self-managing behaviours and facilitates a diverse policy behaviour space. Features include support for multiple versions of a given policy type, multiple configuration templates, and meta policies to dynamically select between policy instances. An example deployment scenario illustrates advanced functionality in the context of a multi policy stock trading system which is sensitive to environmental volatility.

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.

Policy-driven self-management for an automotive middleware

This paper describes work towards the deployment of self-managing capabilities into an advanced middleware for automotive systems. The middleware will support a range of futuristic use-cases requiring context-awareness and dynamic system configuration. Several use-cases are described and their specific context-awareness requirements identified. The discussion is accompanied by a justification for the selection of policy-based computing as the autonomics technique to drive the self-management. The specific policy technology to be deployed is described briefly, with a focus on its specific features that are of direct relevance to the middleware project. A selected use-case is explored in depth to illustrate the extent of dynamic behaviour achievable in the proposed middleware architecture, which is composed of several policy-configured services. An early demonstration application which facilitates concept evaluation is presented and a sequence of typical device-discovery events is worked through

Quality-of-context driven autonomicity

Optimisation in wireless sensor networks is necessary due to the resource constraints of individual devices, bandwidth limits of the communication channel, relatively high probably of sensor failure, and the requirement constraints of the deployed applications in potently highly volatile environments. This paper presents BioANS, a protocol designed to optimise a wireless sensor network for resource efficiency as well as to meet a requirement common to a whole class of WSN applications - namely that the sensor nodes are dynamically selected on some qualitative basis, for example the quality by which they can provide the required context information. The design of BioANS has been inspired by the communication mechanisms that have evolved in natural systems. The protocol tolerates randomness in its environment, including random message loss, and incorporates a non-deterministic ’delayed-bids’ mechanism. A simulation model is used to explore the protocol’s performance in a wide range of WSN configurations. Characteristics evaluated include tolerance to sensor node density and message loss, communication efficiency, and negotiation latency .

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).

A versatile policy toolkit supporting run-time policy reconfiguration

This paper describes an autonomics development tool which serves as both a powerful and flexible policy-expression language and a policy-based framework that supports the integration and dynamic composition of several autonomic computing techniques including signal processing, automated trend analysis and utility functions. Each of these technologies has specific advantages and applicability to different types of dynamic adaptation. The AGILE platform enables seamless interoperability of the different technologies to each perform various aspects of self-management within a single application. Self-management behaviour is specified using the policy language semantics to bind the various technologies together as required. Since the policy semantics support run-time re-configuration, the self-management architecture is dynamically composable. The policy language and implementation library have integrated support for self-stabilising behaviour, enabling oscillation and other forms of instability to be handled at the policy level with very little effort on the part of the application developer. Example applications are presented to illustrate the integration of different autonomics techniques, and the achievement of dynamic composition.

Embedding dynamic behaviour into a self-configuring software system

This paper describes a methodology for embedding dynamic behaviour into software components. The implications and system architecture requirements to support this adaptivity are discussed. This work is part of a European Commission funded and industry supported project to produce a reconfigurable middleware for use in automotive systems. Such systems must be trustable against illegal internal behaviour and activity with external origins, additional devices for example. Policy-based computing is used here as an example of embedded logic. A key contribution of this work is the way in which static and dynamic aspects of the system are interfaced, such that the behaviour can be changed very flexibly (even during run-time), without modification, recompilation or redeployment of the embedded application code. An implementation of these concepts is presented, focussing on achieving trust in the use of dynamic behaviour.

A run-time configurable software architecture for self-managing systems

This paper describes a highly flexible component architecture, primarily designed for automotive control systems, that supports distributed dynamically- configurable context-aware behaviour. The architecture enforces a separation of design-time and run-time concerns, enabling almost all decisions concerning runtime composition and adaptation to be deferred beyond deployment. Dynamic context management contributes to flexibility. The architecture is extensible, and can embed potentially many different self-management decision technologies simultaneously. The mechanism that implements the run-time configuration has been designed to be very robust, automatically and silently handling problems arising from the evaluation of self- management logic and ensuring that in the worst case the dynamic aspects of the system collapse down to static behavior in totally predictable ways.

Understanding changes in cardiovascular pathophysiology

Cardiovascular pathophysiological changes, such as hypertension and enlarged ventricles, reflect the altered functions of the heart and its circulation during ill-health. This article examines the normal and altered anatomy of the cardiac valves, the contractile elements and enzymes of the myocardium, the significance of the different factors associated with cardiac output, and the role of the autonomic nervous system in the heart beat. It also explores how certain diseases alter these functions and result in cardiac symptoms. Nurses can benefit from knowledge of these specific changes, for example, by being able to ask relevant questions in order to ascertain the nature of a patients condition, by being able to take an effective patient history and by being able to read diagnostic results, such as electrocardiograms and cardiac enzyme results. All this will help nurses to promote sound cardiac care based on a physiological rationale.