This research has been sponsored by the U.S. Air Force Research Laboratory under contract FA8750-08-C-0022.
Special Issue Paper
Dynamic policy-driven quality of service in service-oriented information management systems†
Article first published online: 14 JUL 2011
Copyright © 2011 John Wiley & Sons, Ltd.
Software: Practice and Experience
Special Issue: Component and service-oriented distributed embedded real-time systems: Extended papers from ISORC 2010
Volume 41, Issue 12, pages 1459–1489, November/December 2011
How to Cite
Loyall, J. P., Gillen, M., Paulos, A., Bunch, L., Carvalho, M., Edmondson, J., Schmidt, D. C., Martignoni III, A. and Sinclair, A. (2011), Dynamic policy-driven quality of service in service-oriented information management systems. Softw: Pract. Exper., 41: 1459–1489. doi: 10.1002/spe.1101
- Issue published online: 20 OCT 2011
- Article first published online: 14 JUL 2011
- Manuscript Accepted: 20 APR 2011
- Manuscript Revised: 11 MAR 2011
- Manuscript Received: 30 JUL 2010
- service-oriented architecture;
- quality of service;
- information management
SOA middleware has emerged as a powerful and popular distributed computing paradigm because of its high-level abstractions for composing systems and encapsulating platform-level details and complexities. Control of some details encapsulated by SOA middleware is necessary, however, to provide managed QoS for SOA systems that require predictable performance and behavior. This paper presents a policy-driven approach for managing QoS in SOA systems called QoS enabled dissemination (QED). QED includes services for: (1) specifying and enforcing the QoS preferences of individual clients; (2) mediating and aggregating QoS management on behalf of competing users; and (3) shaping information exchange to improve real-time performance. We describe QED's QoS services and mechanisms in the context of managing QoS for a set of Publish-Subscribe-Query information management services. These services provide a representative case study in which CPU and network bottlenecks can occur, client QoS preferences can conflict, and system-level QoS requirements are based on higher level, aggregate end-to-end goals. We also discuss the design of several key QoS services and describe how QED's policy-driven approach bridges users to the underlying middleware and enables QoS control based on rich and meaningful context descriptions, including users, data types, client preferences, and information characteristics. In addition, we present experimental results that quantify the improved control, differentiation, and client-level QoS enabled by QED. Copyright © 2011 John Wiley & Sons, Ltd.