Self-Configuration Framework for Networked Systems and Applications

Persistent Link:
http://hdl.handle.net/10150/195456
Title:
Self-Configuration Framework for Networked Systems and Applications
Author:
Chen, Huoping
Issue Date:
2008
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
The increased complexity, heterogeneity and the dynamism of networked systems and applications make current configuration and management tools to be ineffective. A new paradigm to dynamically configure and manage large-scale complex and heterogeneous networked systems is critically needed. In this dissertation, we present a self configuration paradigm based on the principles of autonomic computing that can handle efficiently complexity, dynamism and uncertainty in configuring networked systems and their applications. Our approach is based on making any resource/application to operate as an Autonomic Component (that means, it can be self-configured, self-healed, self-optimized and self-protected) by using two software modules: Component Management Interface (CMI) to specify the configuration and operational policies associated with each component and Component Runtime Manager (CRM) that manages the component configurations and operations using the policies defined in CMI. We use several configuration metrics (adaptability, complexity, latency, scalability, overhead, and effectiveness) to evaluate the effectiveness of our self-configuration approach when compared to other configuration techniques. We have used our approach to dynamically configure four systems: Automatic IT system management, Dynamic security configuration of networked systems, Self-management of data backup and disaster recovery system and Automatic security patches download and installation on a large scale test bed. Our experimental results showed that by applying our self-configuration approach, the initial configuration time, the initial configuration complexity and the dynamic configuration complexity can be reduced significantly. For example, the configuration time for security patches download and installation on nine machines is reduced to 4399 seconds from 27193 seconds. Furthermore our system provides most adaptability (e.g., 100% for Snort rule set configuration) comparing to hard coded approach (e.g., 22% for Snort rule set configuration) and can improve the performance of managed system greatly. For example, in data backup and recovery system, our approach can reduce the total cost by 54.1% when network bandwidth decreases. In addition, our framework is scalable and imposes very small overhead (less than 1%) on the managed system.
Type:
text; Electronic Dissertation
Keywords:
Autonomic Computing; Self-Configuration; Distributed Configuration Management
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Electrical & Computer Engineering; Graduate College
Degree Grantor:
University of Arizona
Advisor:
Hariri, Salim
Committee Chair:
Hariri, Salim

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleSelf-Configuration Framework for Networked Systems and Applicationsen_US
dc.creatorChen, Huopingen_US
dc.contributor.authorChen, Huopingen_US
dc.date.issued2008en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractThe increased complexity, heterogeneity and the dynamism of networked systems and applications make current configuration and management tools to be ineffective. A new paradigm to dynamically configure and manage large-scale complex and heterogeneous networked systems is critically needed. In this dissertation, we present a self configuration paradigm based on the principles of autonomic computing that can handle efficiently complexity, dynamism and uncertainty in configuring networked systems and their applications. Our approach is based on making any resource/application to operate as an Autonomic Component (that means, it can be self-configured, self-healed, self-optimized and self-protected) by using two software modules: Component Management Interface (CMI) to specify the configuration and operational policies associated with each component and Component Runtime Manager (CRM) that manages the component configurations and operations using the policies defined in CMI. We use several configuration metrics (adaptability, complexity, latency, scalability, overhead, and effectiveness) to evaluate the effectiveness of our self-configuration approach when compared to other configuration techniques. We have used our approach to dynamically configure four systems: Automatic IT system management, Dynamic security configuration of networked systems, Self-management of data backup and disaster recovery system and Automatic security patches download and installation on a large scale test bed. Our experimental results showed that by applying our self-configuration approach, the initial configuration time, the initial configuration complexity and the dynamic configuration complexity can be reduced significantly. For example, the configuration time for security patches download and installation on nine machines is reduced to 4399 seconds from 27193 seconds. Furthermore our system provides most adaptability (e.g., 100% for Snort rule set configuration) comparing to hard coded approach (e.g., 22% for Snort rule set configuration) and can improve the performance of managed system greatly. For example, in data backup and recovery system, our approach can reduce the total cost by 54.1% when network bandwidth decreases. In addition, our framework is scalable and imposes very small overhead (less than 1%) on the managed system.en_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
dc.subjectAutonomic Computingen_US
dc.subjectSelf-Configurationen_US
dc.subjectDistributed Configuration Managementen_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineElectrical & Computer Engineeringen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorHariri, Salimen_US
dc.contributor.chairHariri, Salimen_US
dc.contributor.committeememberRozenblit, Jerzy W.en_US
dc.contributor.committeememberAkoglu, Alien_US
dc.identifier.proquest2553en_US
dc.identifier.oclc659748480en_US
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