By Topic

Automated Resource Management Framework for Adjusting Business Service Capability

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)
Yonglin Xia ; Chinese Acad. of Sci., Beijing ; Jun Wei

The value of business service is depended on efficient resource management in meeting service level agreements (SLAs) with clients and other business objectives. Agreement based resource management in service environment enable service provider to know customer demand in advance and allocate the required resources for the service. However, traditional resource management scheduling systems for the service model have tended to be statically configured and to be non-adaptive at runtime, and have addressed coordination across resources in a limited fashion. In this paper we present a novel resource management framework in which resources can be flexible assigned to business process tasks in an efficient and adaptive way to adjust business service capability when service requirements change. The framework also uniformly accommodates an extensible set of resource types that may be both fine-grained and abstract. In addition, it is highly configurable and extensible in terms of pluggable strategies, and supports flexible runtime adaptation to fluctuating application demand and resource availability. It thus comprises a QoS driven and potentially autonomic resource management facility.

Published in:

Asia-Pacific Service Computing Conference, The 2nd IEEE

Date of Conference:

11-14 Dec. 2007