Towards knowledge management in autonomic systems

Cofino, Thomas; Doǧanata, Yurdaer N.; Drissi, Youssef; Fin, T. Andrew; Kozakov, L.; Laker, M. M.

doi:10.1109/iscc.2003.1214214

Cited by 5 publications

(4 citation statements)

References 11 publications

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“…[28]. In the autonomic systems context, the knowledge includes essential part of a self-knowledge (as named in [29]) with corresponding management components like self-monitoring, self-learning, self-diagnostics, etc.…”

Section: Knowledge For Survivalmentioning

confidence: 99%

An introduction to knowledge computing

Terziyan

Шевченко

Golovianko

2014

EEJET

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Section: Knowledge For Survivalmentioning

confidence: 99%

An introduction to knowledge computing

Terziyan

Шевченко

Golovianko

2014

EEJET

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“…An error in the execution of task (3) may be caused by a broken connection between AccessManager and BusinessIntegrator. This connection is modelled as a connector that contains information on the type of protocol used (in this case JRMI), and (1) AccessManager receives user's certificate, (2) AccessManager verifies certificate, (3) AccessManager passes certificate to BusinessIntegrator, (4) BusinessIntegrator prepares login info, (5) BusinessIntegrator delegates login info to BusinessManager, (6) BusinessManager authenticates the user, (7) BusinessManager passes result to BusinessIntegrator, (8) BusinessIntegrator passes result to AccessManager, (9) AccessManager passes authentication result to Browser. Monitoring task (3) is implemented as follows.…”

Section: An Authentication Scenariomentioning

confidence: 99%

“…Acquiring domain knowledge necessary for modelbased approaches is known to be difficult [17,8]. In the application model presented in this paper, the domain knowledge is obtained from three domain experts, each with his/her own specific view to the system: system administrators, functional analysts, and software developers [11,14].…”

Section: Application Modelmentioning

confidence: 99%

Use Case Driven Approach to Self-Monitoring in Autonomic Systems

Haydarlou

Oey

Overeinder

et al. 2007

Third International Conference on Autonomic and Autonomous Systems (ICAS'07)

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Self-monitoring of autonomic distributed systems requires knowledge of the states and events of many different parts of a system. One of the main challenges is to determine which information is most crucial for analysis of a system's behaviour, and when. This paper proposes a modelbased approach to self-monitoring for which structural and behavioural models of a system are described at different levels: application, subsystem, component and class level. In this approach, a system's behaviour is monitored in the context of a hierarchy of use-cases related to these levels. The structural and behavioural models are used to automatically instrument an existing distributed system. The proposed architecture of a self-monitoring engine is described as is the implementation. The models have been specified in the Ontology Web Language (OWL) and the self-monitoring (as a part of our self-management framework) has been implemented in Java. The scenario used to illustrate the approach is that of authentication for a simplified version of a distributed portal application.

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“…In order for any system to be capable of this sort of autonomic management, it must be able to understand its own component parts and the combined effect of these parts. In essence, autonomics is about selfknowledge [3] and the usage of this knowledge to determine an appropriate action. It is our supposition that self-knowledge is essentially a function of two factors.…”

Section: Introductionmentioning

confidence: 99%

Policy and Profile: Enabling Self-knowledge for Autonomic Systems

Carroll

Strassner

Cox

et al. 2006

Lecture Notes in Computer Science

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Abstract. The standard definition of autonomics is that of self-governance, including such properties as self-configuring, self-healing and self-optimizing. To really enable self-anything, however, we must first deliver another 'self-' property -self-knowledge. We define self-knowledge as information about a system enabling it to reason on its own capabilities and actions. This knowledge can come in many forms but we propose that there are essentially two key elements: knowledge of the individual parts of the system, and knowledge about the rules that determine the interaction of these system components. This paper presents a model describing self-knowledge, with policy for defining rules and profiles to express the individual entities knowledge.

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Towards knowledge management in autonomic systems

Cited by 5 publications

References 11 publications

An introduction to knowledge computing

An introduction to knowledge computing

Use Case Driven Approach to Self-Monitoring in Autonomic Systems

Policy and Profile: Enabling Self-knowledge for Autonomic Systems

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