By Topic

Self-Adaptive Techniques for the Load Trend Evaluation of Internal System Resources

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Casolari, S. ; Dept. of Inf. Eng., Univ. of Modena & Reggio Emilia, Reggio Emilia ; Colajanni, M. ; Tosi, S.

Modern distributed systems that have to avoid performance degradation and system overload require several runtime management decisions for load balancing and load sharing, overload and admission control, job dispatching and request redirection. As the external workload and the internal resource behavior of the modern system is highly complex and variable, self-adaptive techniques require a stable vision of the system behavior. In this paper we propose a trend model that guarantees a robust interpretation for load-aware decision algorithms. Various experimental results in a Web cluster demonstrate that the proposed models and algorithms guarantee better stability of the load and a reduction of the response time experienced by the users.

Published in:

Autonomic and Autonomous Systems, 2009. ICAS '09. Fifth International Conference on

Date of Conference:

20-25 April 2009