Towards Certifiable Autonomic Computing Systems Part I: A Consistent and Scalable System Design

Relative to currently deployed Information Technology (IT) systems, autonomic computing systems are expected to exhibit superior control/management behaviour and high adaptability, regardless of operational context. However, a means for measuring and certifying the self-management capabilities of these systems is lacking and as result, there is no way of assessing the trustworthiness of these systems. Two things are needed to begin to address the above. The first is a consistent structure for the autonomic computing system (ACS) and a consistent architecture for the autonomic computing manager (AM). The second is a set of metrics by which the operational characteristics of these systems are to be measured within the context of the targeted application domain. In this first part of a two-part paper, a biologically inspired architecture is proposed for the autonomic computing manager. The interfaces and messages by which this architecture communicates with objects within and those without are technically defined. Also discussed in this paper is the policy structure by which the autonomic manager is configured to sense contexts and effect changes in its managed environment. For the system framework, a tree structure together with its associated protocols is proposed, implemented and used as the basis for establishing administrative and security relationships between autonomic computing elements; for resolving management conflicts; for enforcing data integrity; for ensuring data availability and for providing mechanisms that aid system scalability, robustness and extensibility, while maintaining low system complexity. This framework is achieved using standards-based objects including the Lightweight Directory Access Protocol (LDAP), Policy Core Information Model (PCIM) and a significant number of Internet Engineering Task Force (IETF) Request For Comments (RFC) standard documents. Keywords-Autonomic computing systems; Certification; Architecture; Intelligent Machine Design; LDAP;

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