Self-adaptability and man-in-the-loop: a dilemma in autonomic computing systems

This paper addresses some controversial issues relating to two main questions. Firstly, we discuss 'man-in-the loop' issues in SAACS. Some people advocate this must always be so that man's decisions can override autonomic components. In this case, the system has two subsystems - man and machine. Can we, however, have a fully autonomic machine - with no man in sight; even for short periods of time? What kinds of systems require man to always be in the loop? What is the optimum balance in self-to-human control? How do we determine the optimum? How far can we go in describing self-behaviour? How does a SAACS system handle unexpected behaviour? Secondly, what are the challenges/obstacles in testing SAACS in the context of self/human dilemma? Are there any lesson to be learned from other programmes e.g. Star-wars, aviation and space explorations? What role human factors and behavioural models play whilst in interacting with SAACS?.

A policy-definition language and prototype implementation library for policy-based autonomic systems

This paper presents work towards generic policy toolkit support for autonomic computing systems in which the policies themselves can be adapted dynamically and automatically. The work is motivated by three needs: the need for longer-term policy-based adaptation where the policy itself is dynamically adapted to continually maintain or improve its effectiveness despite changing environmental conditions; the need to enable non autonomics-expert practitioners to embed self-managing behaviours with low cost and risk; and the need for adaptive policy mechanisms that are easy to deploy into legacy code. A policy definition language is presented; designed to permit powerful expression of self-managing behaviours. The language is very flexible through the use of simple yet expressive syntax and semantics, and facilitates a very diverse policy behaviour space through both hierarchical and recursive uses of language elements. A prototype library implementation of the policy support mechanisms is described. The library reads and writes policies in well-formed XML script. The implementation extends the state of the art in policy-based autonomics through innovations which include support for multiple policy versions of a given policy type, multiple configuration templates, and meta-policies to dynamically select between policy instances and templates. Most significantly, the scheme supports hot-swapping between policy instances. To illustrate the feasibility and generalised applicability of these tools, two dissimilar example deployment scenarios are examined. The first is taken from an exploratory implementation of self-managing parallel processing, and is used to demonstrate the simple and efficient use of the tools. The second example demonstrates more-advanced functionality, in the context of an envisioned multi-policy stock trading scheme which is sensitive to environmental volatility

Exploring adaptation & self-adaptation in autonomic computing systems

This panel paper sets out to discuss what self-adaptation means, and to explore the extent to which current autonomic systems exhibit truly self-adaptive behaviour. Many of the currently cited examples are clearly adaptive, but debate remains as to what extent they are simply following prescribed adaptation rules within preset bounds, and to what extent they have the ability to truly learn new behaviour. Is there a standard test that can be applied to differentiate? Is adaptive behaviour sufficient anyway? Other autonomic computing issues are also discussed.

The AGILE policy expression language for autonomic systems

This paper presents the AGILE policy expression language. The language enables powerful expression of self-managing behaviours and facilitates policy-based autonomic computing in which the policies themselves can be adapted dynamically and automatically. The language is generic so as to be deployable across a wide spectrum of application domains, and is very flexible through the use of simple yet expressive syntax and semantics. The development of AGILE is motivated by the need for adaptive policy mechanisms that are easy to deploy into legacy code and can be used by non autonomics-expert practitioners to embed self-managing behaviours with low cost and risk. A library implementation of the policy language is described. The implementation extends the state of the art in policy-based autonomics through innovations which include support for multiple policy versions of a given policy type, multiple configuration templates, and higher-level ‘meta-policies’ to dynamically select between differently configured business-logic policy instances and templates. Two dissimilar example deployment scenarios are examined.

Policy-centric integration and dynamic composition of autonomic computing techniques

This paper presents innovative work in the development of policy-based autonomic computing. The core of the work is a powerful and flexible policy-expression language AGILE, which facilitates run-time adaptable policy configuration of autonomic systems. AGILE also serves as an integrating platform for other self-management technologies 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. The various technologies are implemented as object components. Self-management behaviour is specified using the policy language semantics to bind the various components together as required. Since the policy semantics support run-time re-configuration, the self-management architecture is dynamically composable. Additional benefits include the standardisation of the application programmer interface, terminology and semantics, and only a single point of embedding is required.