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Formal Aspects of Self-* in Autonomic Networked Computing Systems

  • Phan Cong-Vinh
Chapter

Abstract

A new computing paradigm is currently on spot: autonomic computing (AC), which is inspired by the human autonomic nervous system. AC is characterized by its self-* facets such as self-configuration, self-healing, self-optimization, and self-protection. The overarching goal of AC is to realize computer systems, and thus networked computing systems, that can manage themselves without direct human interventions. Meeting this grand challenge of autonomic computing requires a fundamental approach to the notion of self-*. To this end, taking advantage of the categorical approach we establish, in this chapter, a firm formal basis for modeling self-* in autonomic networked computing systems, developing self-* monoid, category of self-* monoids, and series of self-* facets. All of these are to achieve formal aspects of the self-*.

Keywords

Formal Aspect Contextual Data Autonomic Computing Favorite Subject Categorical Language 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Notes

Acknowledgments

Thank you to the anonymous reviewers for their helpful comments and valuable suggestions which have contributed to the final preparation of the chapter. As always, I am deeply indebted to Professor Jonathan P. Bowen, Head of the Centre for Applied Formal Methods (CAFM) at London South Bank University (LSBU) in United Kingdom, for a constant source of inspiration and encouragement for the work which culminated in the publication of this chapter.

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Copyright information

© Springer-Verlag US 2009

Authors and Affiliations

  1. 1.London South Bank UniversityLondon SE1 0AAUK

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