Analyzing policy dependencies using historical information

Analyzing policy dependencies using historical information

Autonomic computing is central to the success of IT infrastructure deployment as its complexity and pervasiveness grows. This paper addresses one aspect of policy-based autonomic computing - the issue of identifying dependencies between policies, knowledge of which is useful to the policymaker while...

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Hauptverfasser: Lotlikar, R.M., Chakravarthy, S., Vatsavai, R.R., Mohania, M.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Artificial intelligence
Computer science
Costs
Feedback
Information analysis
Logic programming
Pervasive computing
Quality of service
Runtime
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creator Lotlikar, R.M.
Chakravarthy, S.
Vatsavai, R.R.
Mohania, M.
description Autonomic computing is central to the success of IT infrastructure deployment as its complexity and pervasiveness grows. This paper addresses one aspect of policy-based autonomic computing - the issue of identifying dependencies between policies, knowledge of which is useful to the policymaker while defining or updating policies. These dependencies are determined via assesment of the impact of a policy on the sensors (measurable entities at runtime). Our approach uses a simple pragmatic model over the measured runtime information from the recent past. Both static and runtime information is combined to provide effective feedback.
doi_str_mv 10.1109/POLICY.2005.6
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subjects Artificial intelligence
Computer science
Costs
Feedback
Information analysis
Logic programming
Pervasive computing
Quality of service
Runtime
title Analyzing policy dependencies using historical information
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