Joint scheduling and admission control for ATS-based switching nodes
SIGCOMM '92 Conference proceedings on Communications architectures & protocols
C4.5: programs for machine learning
C4.5: programs for machine learning
A measurement-based admission control algorithm for integrated services packet networks
SIGCOMM '95 Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment
Journal of the ACM (JACM)
Measurement-based admission control with aggregate traffic envelopes
IEEE/ACM Transactions on Networking (TON)
IEEE Transactions on Knowledge and Data Engineering
Machine Learning
Providing QoS Customization in Distributed Object Systems
Middleware '01 Proceedings of the IFIP/ACM International Conference on Distributed Systems Platforms Heidelberg
Extracting decision trees from trained neural networks
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
A Hybrid Control Design for QoS Management
RTSS '03 Proceedings of the 24th IEEE International Real-Time Systems Symposium
The case for using middleware to manage diverse soft real-time schedulers
M3W Proceedings of the 2001 international workshop on Multimedia middleware
QoS Management Through Adaptive Reservations
Real-Time Systems
Traffic classification on the fly
ACM SIGCOMM Computer Communication Review
Predicting Performance on a Loosely Controlled Event System
COMPSAC '08 Proceedings of the 2008 32nd Annual IEEE International Computer Software and Applications Conference
Matching Service Requirements to Empirical Capability Models in Service-Oriented Architectures
COMPSAC '08 Proceedings of the 2008 32nd Annual IEEE International Computer Software and Applications Conference
Event-Driven Modeling and Testing of Web Services
COMPSAC '08 Proceedings of the 2008 32nd Annual IEEE International Computer Software and Applications Conference
Admission Control for Distributed Complex Responsive Systems
ISPDC '09 Proceedings of the 2009 Eighth International Symposium on Parallel and Distributed Computing
Toward scalable real-time messaging
IBM Systems Journal
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The software in modern systems has become too complex to make accurate predictions about their performance under different configurations. Real-time or even responsiveness requirements cannot be met because it is not possible to perform admission control for new or changing tasks if we cannot tell how their execution affects the other tasks already running. Previously, we proposed a resource-allocation middleware that manages the execution of tasks in a complex distributed system with real-time requirements. The middleware behavior can be modeled depending on the configuration of the tasks running, so that the performance of any given configuration can be calculated. This makes it possible to have admission control in such a system, but the model requires knowledge of run-time parameters. We propose the utilization of machine-learning algorithms to obtain the model parameters, and be able to predict the system performance under any configuration, so that we can provide a full admission control mechanism for complex software systems. In this paper, we present such an admission control mechanism, we measure its accuracy in estimating the parameters of the model, and we evaluate its performance to determine its suitability for a real-time or responsive system.