The Power of Events: An Introduction to Complex Event Processing in Distributed Enterprise Systems
The Power of Events: An Introduction to Complex Event Processing in Distributed Enterprise Systems
Workflow management with service quality guarantees
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
IEEE Internet Computing
A Nonblocking Algorithm for Shared Queues Using Compare-and-Swap
IEEE Transactions on Computers
Quality driven web services composition
WWW '03 Proceedings of the 12th international conference on World Wide Web
Obstruction-Free Synchronization: Double-Ended Queues as an Example
ICDCS '03 Proceedings of the 23rd International Conference on Distributed Computing Systems
QoS-Aware Middleware for Web Services Composition
IEEE Transactions on Software Engineering
A Semantic Publish/Subscribe System
CEC-EAST '04 Proceedings of the E-Commerce Technology for Dynamic E-Business, IEEE International Conference
An approach for QoS-aware service composition based on genetic algorithms
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Java Concurrency in Practice
Temporal management of RFID data
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Policy-Driven Exception-Management for Composite Web Services
CEC '05 Proceedings of the Seventh IEEE International Conference on E-Commerce Technology
Compiled Query Execution Engine using JVM
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
High-performance complex event processing over streams
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Model analysis for business event processing
IBM Systems Journal
ICSOC'06 Proceedings of the 4th international conference on Service-Oriented Computing
Service composition (re)binding driven by application–specific qos
ICSOC'06 Proceedings of the 4th international conference on Service-Oriented Computing
ICSOC'06 Proceedings of the 4th international conference on Service-Oriented Computing
QoS-aware middleware for ubiquitous and heterogeneous environments
IEEE Communications Magazine
Event-Driven Quality of Service Prediction
ICSOC '08 Proceedings of the 6th International Conference on Service-Oriented Computing
Is collaborative QoS the solution to the SOA dependability dilemma?
Architecting dependable systems VII
Generalized aggregate Quality of Service computation for composite services
Journal of Systems and Software
A causal model to predict the effect of business process evolution on quality of service
Proceedings of the 9th international ACM Sigsoft conference on Quality of software architectures
Adaptive Web Services Monitoring in Cloud Environments
International Journal of Web Portals
Bloom filter-based workflow management to enable QoS guarantee in wireless sensor networks
Journal of Network and Computer Applications
AFAWS: An Agent based Framework for Autonomic Web Services
Multiagent and Grid Systems - Development of service-based and agent-based computing systems
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Quality of Service (QoS) information for Web services is essential to QoS-aware service management and composition. Currently, most QoS-aware solutions assume that the QoS for component services is readily available, and that the QoS for composite services can be computed from the QoS for component services. The issue of how to obtain the QoS for component services has largely been overlooked. In this paper, we tackle this fundamental issue. We argue that most of QoS metrics can be observed/computed based on service operations. We present the design and implementation of a high-performance QoS monitoring system. The system is driven by a QoS observation model that defines IT- and business-level metrics and associated evaluation formulas. Integrated into the SOA infrastructure at large, the monitoring system can detect and route service operational events systemically. Further, a model-driven, hybrid compilation/interpretation approach is used in metric computation to process service operational events and maintain metrics efficiently. Experiments suggest that our system can support high event processing throughput and scales to the number of CPUs.