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Role-Based Autonomic Systems

Role-Based Autonomic Systems

Haibin Zhu
Copyright: © 2012 |Pages: 20
ISBN13: 9781466602649|ISBN10: 1466602643|EISBN13: 9781466602656
DOI: 10.4018/978-1-4666-0264-9.ch010
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MLA

Zhu, Haibin. "Role-Based Autonomic Systems." Breakthroughs in Software Science and Computational Intelligence, edited by Yingxu Wang, IGI Global, 2012, pp. 165-184. https://doi.org/10.4018/978-1-4666-0264-9.ch010

APA

Zhu, H. (2012). Role-Based Autonomic Systems. In Y. Wang (Ed.), Breakthroughs in Software Science and Computational Intelligence (pp. 165-184). IGI Global. https://doi.org/10.4018/978-1-4666-0264-9.ch010

Chicago

Zhu, Haibin. "Role-Based Autonomic Systems." In Breakthroughs in Software Science and Computational Intelligence, edited by Yingxu Wang, 165-184. Hershey, PA: IGI Global, 2012. https://doi.org/10.4018/978-1-4666-0264-9.ch010

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Abstract

Autonomic Computing is an emerging computing paradigm used to create computer systems capable of self-management in order to overcome the rapidly growing complexity of computing systems management. To possess self-* properties, there must be mechanisms to support self-awareness, that is an autonomic system should be able to perceive the abnormality of its components. After abnormality is checked, processes of self-healing, self-configuration, self-optimization, and self-protection must be completed to guarantee the system works correctly and continuously. In role-based collaboration (RBC), roles are the major media for interaction, coordination, and collaboration. A role can be used to check if a player behaves well or not. This paper investigates the possibility of using roles and their related mechanisms to diagnose the behavior of agents, and facilitate self-* properties of a system.

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