By Topic

Reinforcement learning-based dynamic adaptation planning method for architecture-based self-managed software

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

2 Author(s)
Dongsun Kim ; Dept. of Comput. Sci. & Eng., Sogang Univ., Seoul ; Sooyong Park

Recently, software systems face dynamically changing environments, and the users of the systems provide changing requirements at run-time. Self-management is emerging to deal with these problems. One of the key issues to achieve self-management is planning for selecting appropriate structure or behavior of self-managed software systems. There are two types of planning in self-management: off-line and on-line planning. Recent discussion has focused on off-line planning which provides static relationships between environmental changes and software configurations. In on-line planning, a software system can autonomously derive mappings between environmental changes and software configurations by learning its dynamic environment and using its prior experience. In this paper, we propose a reinforcement learning-based approach to on-line planning in architecture-based self-management. This approach enables a software system to improve its behavior by learning the results of its behavior and by dynamically changing its plans based on the learning in the presence of environmental changes. The paper presents a case study to illustrate the approach and its result shows that reinforcement learning-based on-line planning is effective for architecture-based self-management.

Published in:

Software Engineering for Adaptive and Self-Managing Systems, 2009. SEAMS '09. ICSE Workshop on

Date of Conference:

18-19 May 2009