Continuous-time hidden Markov models for network performance evaluation
Performance Evaluation
Self-Managed Systems: an Architectural Challenge
FOSE '07 2007 Future of Software Engineering
Toward Runtime Self-adaptation Method in Software-Intensive Systems Based on Hidden Markov Model
COMPSAC '07 Proceedings of the 31st Annual International Computer Software and Applications Conference - Volume 02
A framework for QoS-aware binding and re-binding of composite web services
Journal of Systems and Software
A journey to highly dynamic, self-adaptive service-based applications
Automated Software Engineering
Self-adaptive software: Landscape and research challenges
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Software Engineering for Self-Adaptive Systems: A Research Roadmap
Software Engineering for Self-Adaptive Systems
Qos-driven runtime adaptation of service oriented architectures
Proceedings of the the 7th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering
Performance aware open-world software in a 3-layer architecture
Proceedings of the first joint WOSP/SIPEW international conference on Performance engineering
PLASMA: a plan-based layered architecture for software model-driven adaptation
Proceedings of the IEEE/ACM international conference on Automated software engineering
QoS driven dynamic binding in-the-many
QoSA'10 Proceedings of the 6th international conference on Quality of Software Architectures: research into Practice - Reality and Gaps
Enhancing a QoS-based self-adaptive framework with energy management capabilities
Proceedings of the joint ACM SIGSOFT conference -- QoSA and ACM SIGSOFT symposium -- ISARCS on Quality of software architectures -- QoSA and architecting critical systems -- ISARCS
Analysis of bursty workload-aware self-adaptive systems
ICPE '12 Proceedings of the 3rd ACM/SPEC International Conference on Performance Engineering
QoS and energy management with Petri nets: A self-adaptive framework
Journal of Systems and Software
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Service Oriented Architecture (SOA) is a paradigm where applications are built on services offered by third party providers. Behavior of providers evolves and makes a challenge the performance prediction of SOA applications. A proper decision about when a provider should be substituted can dramatically improve the performance of the application. We propose hidden Markov models (HMM) to help service integrators to foretell the current state of third-parties. The paper leverages different algorithms that change providers based on predictions about their states. We also integrate these algorithms and HMMs in an architectural solution to coordinate them with other challenges in the SOA world.