Dead-zone logic in autonomic systems

Published in Evolving and adaptive intelligent systems. IEEE Conference 2014. (EAIS 2014)Dead-Zone logic is a mechanism to prevent autonomic managers from unnecessary, inefficient and ineffective control brevity when the system is sufficiently close to its target state. It provides a natural and powerful framework for achieving dependable self-management in autonomic systems by enabling autonomic managers to smartly carry out a change (or adapt) only when it is safe and efficient to do so-within a particular (defined) safety margin. This paper explores and evaluates the performance impact of dead-zone logic in trustworthy autonomic computing. Using two case example scenarios, we present empirical analyses that demonstrate the effectiveness of dead-zone logic in achieving stability, dependability and trustworthiness in adaptive systems. Dynamic temperature target tracking and autonomic datacentre resource request and allocation management scenarios are used. Results show that dead-zone logic can significantly enhance the trustability of autonomic systems

Trustworthy autonomic architecture (TAArch): Implementation and empirical investigation

This paper presents a new architecture for trustworthy autonomic systems. This trustworthy autonomic architecture is different from the traditional autonomic computing architecture and includes mechanisms and instrumentation to explicitly support run-time self-validation and trustworthiness. The state of practice does not lend itself robustly enough to support trustworthiness and system dependability. For example, despite validating system's decisions within a logical boundary set for the system, there’s the possibility of overall erratic behaviour or inconsistency in the system emerging for example, at a different logical level or on a different time scale. So a more thorough and holistic approach, with a higher level of check, is required to convincingly address the dependability and trustworthy concerns. Validation alone does not always guarantee trustworthiness as each individual decision could be correct (validated) but overall system may not be consistent and thus not dependable. A robust approach requires that validation and trustworthiness are designed in and integral at the architectural level, and not treated as add-ons as they cannot be reliably retro-fitted to systems. This paper analyses the current state of practice in autonomic architecture, presents a different architectural approach for trustworthy autonomic systems, and uses a datacentre scenario as the basis for empirical analysis of behaviour and performance. Results show that the proposed trustworthy autonomic architecture has significant performance improvement over existing architectures and can be relied upon to operate (or manage) almost all level of datacentre scale and complexity

Policy-based autonomic computing with integral support for self-stabilisation

This paper describes the AGILE technology for building self-managing systems. AGILE serves as both a policy expression language and a framework that facilitates the integration and dynamic composition of several autonomic computing techniques within a single deployment technology and supports run-time self-reconfiguration. The paper also discusses the need for self-stabilisation mechanisms for autonomic systems in order to reduce the reliance of autonomic components on external supervision and extend their behavioural scope and trustability. The self-stabilisation approach taken and the initial support mechanisms in this regard that have been integrated into AGILE are examined. A demonstration application illustrates the powerful dynamic adaptation capabilities of the technology. The self-stabilisation theme is prominent, but other aspects are also demonstrated, including dynamic reconfiguration at the policy level, automated built-in signal processing and trend analysis, the integration of policies and utility functions and the ease with which such advanced self-managing behaviour can be configured using AGILE

An adaptive service oriented architecture: Automatically solving interoperability problems.

Organizations desire to be able to easily cooperate with other companies and still be flexible. The IT infrastructure used by these companies should facilitate these wishes. Service-Oriented Architecture (SOA) and Autonomic Computing (AC) were introduced in order to realize such an infrastructure, however both have their shortcomings and do not fulfil these wishes. This dissertation addresses these shortcomings and presents an approach for incorporating (self-) adaptive behavior in (Web) services. A conceptual foundation of adaptation is provided and SOA is extended to incorporate adaptive behavior, called Adaptive Service Oriented Architecture (ASOA). To demonstrate our conceptual framework, we implement it to address a crucial aspect of distributed systems, namely interoperability. In particular, we study the situation of a service orchestrator adapting itself to evolving service providers.