IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Autonomic Business-Driven Dynamic Adaptation of Service-Oriented Systems and the WSPolicy4MASC Support for Such Adaptation

Autonomic Business-Driven Dynamic Adaptation of Service-Oriented Systems and the WSPolicy4MASC Support for Such Adaptation
View Sample PDF
Author(s): Vladimir Tosic (The University of New South Wales, Australia and The University of Western Ontario, Canada)
Copyright: 2010
Volume: 1
Issue: 1
Pages: 17
Source title: International Journal of Systems and Service-Oriented Engineering (IJSSOE)
Editor(s)-in-Chief: Wuhui Chen (Sun Yat-sen University, China)
DOI: 10.4018/jssoe.2010092105

Purchase


Abstract

When a need for dynamic adaptation of an information technology (IT) system arises, often several alternative approaches can be taken. Maximization of technical quality of service (QoS) metrics (e.g., throughput, availability) need not maximize business value metrics (e.g., profit, customer satisfaction). The goal of autonomic business-driven IT system management (BDIM) is to ensure that operation and adaptation of IT systems maximizes business value metrics, with minimal human intervention. The author presents how his WS-Policy4MASC language for specification of management policies for service-oriented systems supports autonomic BDIM. WS-Policy4MASC extends WS-Policy with new types of policy assertions: goal, action, probability, utility, and meta-policy assertions. Its main distinctive characteristics are description of diverse business value metrics and specification of policy conflict resolution strategies for business value maximization according to various business strategies. The author’s decision making algorithms use this additional WS-Policy4MASC information to choose the adaptation approach best from the business viewpoint.

Related Content

Nalinee Sophatsathit. © 2026. 14 pages.
Min Jiang. © 2026. 16 pages.
Samar El Sayad, Ahmed Diab, Mohamed Fawzy Elsayed, Laila Aladwey. © 2026. 31 pages.
Zhengdong Hou. © 2026. 13 pages.
Gevorg Harutyunyan, Karen Nersisyan, Lilit Galstyan, Lilik Beglaryan, Mikayel Mikayelyan, Grigor Manukyan. © 2026. 20 pages.
Azadeh Amoozegar, Ali Nouri Lata, Mohammad Falahat, Sara Ravan Ramzani, Sedigheh Shakib, Mohamadreza Jafary, Mohd Hanafi Mohd Yasin. © 2026. 21 pages.
Jingmiao Liu, Xiaoshuang Hou. © 2026. 22 pages.
Body Bottom