Dynamic policy-driven quality of service in service-oriented information management systems

SUMMARY SOA middleware has emerged as a powerful and popular distributed computing paradigm because of its high‐level ions for composing systems and encapsulating platform‐level details and complexities. Control of some details encapsulated by SOA middleware is necessary, however, to provide managed...

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Bibliographic Details
Published in:Software, practice & experience practice & experience, 2011-11, Vol.41 (12), p.1459-1489
Main Authors: Loyall, Joseph P., Gillen, Matthew, Paulos, Aaron, Bunch, Larry, Carvalho, Marco, Edmondson, James, Schmidt, Douglas C., Martignoni III, Andrew, Sinclair, Asher
Format: Article
Language:English
Subjects:
Clients
Computer programs
Distributed processing
Dynamical systems
Dynamics
Information management
Middleware
Networks
quality of service
service-oriented architecture
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Summary:SUMMARY SOA middleware has emerged as a powerful and popular distributed computing paradigm because of its high‐level ions 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.
ISSN:0038-0644
1097-024X
1097-024X
DOI:10.1002/spe.1101