Scheduled System Maintenance:
On May 6th, single article purchases and IEEE account management will be unavailable from 8:00 AM - 5:00 PM ET (12:00 - 21:00 UTC). We apologize for the inconvenience.
By Topic

A diagnosis module based on statistic and QoS techniques for self-healing architectures supporting WS based applications

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

6 Author(s)
Moo-Mena, F. ; Fac. de Mat. Periferico, Univ. Autonoma de Yucatan, Merida, Mexico ; Garcilazo-Ortiz, J. ; Basto-Diaz, L. ; Curi-Quintal, F.
more authors

In literature it is common to find that a self-healing architecture is made up basically of three modules: monitoring, diagnosis, and recovery. Of these three modules, the diagnosis module represents a crucial point, since in this one the state that keeps the system is established. Nevertheless, a standardized way does not exist to implement this module in this kind of architecture. In this paper we propose a strategy of implementation of diagnosis module based on statistic methods by using box plot diagrams. This technique allows us to calibrate the parameters of quality of service (QoS) in a Web services based application. This way, based on the values of QoS, the diagnosis module determines if the system is stable or if a QoS degradation is presented.

Published in:

Cyber-Enabled Distributed Computing and Knowledge Discovery, 2009. CyberC '09. International Conference on

Date of Conference:

10-11 Oct. 2009