Hidden Markov modeling for network communication channels
Proceedings of the 2001 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Quality Control for Scalable Media Processing Applications
Journal of Scheduling
An Open Framework for Dynamic Reconfiguration
Proceedings of the 26th International Conference on Software Engineering
Dynamic Service Composition in Pervasive Computing
IEEE Transactions on Parallel and Distributed Systems
A component model for dynamic adaptive systems
International workshop on Engineering of software services for pervasive environments: in conjunction with the 6th ESEC/FSE joint meeting
User Interface Migration between Mobile Devices and Digital TV
HCSE-TAMODIA '08 Proceedings of the 2nd Conference on Human-Centered Software Engineering and 7th International Workshop on Task Models and Diagrams
Exploring approaches to dynamic adaptation
Proceedings of the 3rd International DiscCoTec Workshop on Middleware-Application Interaction
OPEN: open pervasive environments for migratory interactive services
Proceedings of the 12th International Conference on Information Integration and Web-based Applications & Services
Dynamic QoS Management and Optimization in Service-Based Systems
IEEE Transactions on Software Engineering
Fundamental design issues for the future Internet
IEEE Journal on Selected Areas in Communications
Maximizing user utility in video streaming applications
IEEE Transactions on Circuits and Systems for Video Technology
OPEN Platform for Migration of Interactive Services: Architecture and Evaluation
International Journal of Adaptive, Resilient and Autonomic Systems
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A dynamically changing state of the run-time environment impacts the performance of networked applications and furthermore influences the user-perceived quality of the applications. By migrating the application between the user's devices that give different user experiences, a good overall user experience can be maintained, without loosing the application session. It is non-trivial for a system to automatically choose the best device for migration. The choice must maximize the user experience quality and take into account that a migration delays the user's work-flow and even may fail. Moreover, the environment state is not directly observable, and needs to be estimated which leads to inaccuracy. We model the automatic migration trigger as a stochastic optimization problem and we propose to use a hidden Markov model combined with a Markov Decision Process (MDP) to solve the problem. The solution generates policies to choose target device for migration that gives the optimal user experience. We analyse these policies in simulation experiments and derive conclusions on which scenarios the model-based approach performs better than a greedy approach, also when considering inaccurate state estimation.