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First International Conference on Autonomic Computing (ICAC'04)   pp. 206-213
Autonomic Self-Optimization According to Business Objectives
Sarel Aiber, IBM Haifa Research Lab
Dagan Gilat, IBM Haifa Research Lab
Ariel Landau, IBM Haifa Research Lab
Natalia Razinkov, IBM Haifa Research Lab
Aviad Sela, IBM Haifa Research Lab
Segev Wasserkrug, IBM Haifa Research Lab

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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICAC.2004.19
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Abstract
A central challenge in the runtime management of computing environments is the necessity to keep these environments continuously optimized. In this paper we introduce a new paradigm, which focuses on self-optimization according to high-level business objectives such as maximizing revenues. It replaces the more traditional optimizations that are based upon IT measures such as resource availability. A general, autonomous process is defined to enable such optimizations, and a set of technologies and methodologies is introduced to support the implementation of such a process. The paper concludes with two types of validation tests carried out on an eCommerce site, that demonstrate the value and applicability of this approach.
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Citation:  Sarel Aiber, Dagan Gilat, Ariel Landau, Natalia Razinkov, Aviad Sela, Segev Wasserkrug, "Autonomic Self-Optimization According to Business Objectives," icac, pp. 206-213,  First International Conference on Autonomic Computing (ICAC'04),  2004