Integer and combinatorial optimization
Integer and combinatorial optimization
ICON '00 Proceedings of the 8th IEEE International Conference on Networks
A Practical User Mobility Prediction Algorithm for Supporting Adaptive QoS in Wireless Networks
ICON '99 Proceedings of the 7th IEEE International Conference on Networks
Move: mobility with persistent network connections
Move: mobility with persistent network connections
The design and implementation of Zap: a system for migrating computing environments
OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
Cruz: Application-Transparent Distributed Checkpoint-Restart on Standard Operating Systems
DSN '05 Proceedings of the 2005 International Conference on Dependable Systems and Networks
Dimensioning aWide-Area Thin-Client Computing Network Supporting Mobile Users
ICNS '06 Proceedings of the International conference on Networking and Services
Grid design for mobile thin client computing
Future Generation Computer Systems
A Generic Adaptation Framework for Mobile Communication
International Journal of Adaptive, Resilient and Autonomic Systems
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Thin clients are lightweight devices from which all hardware, not related to input and output, is removed. Applications are executed on remote servers that render the graphical output and send it back to the client. As the reaction on user events can appear on the screen only after a two-way path delay, thin client computing can suffer from a high latency that degrades the user experience. We therefore propose that the application follows the user through the network by migrating to a server near enough to the user. In this paper, a theoretical model and heuristics are presented to efficiently select servers for mobile users, in order to minimize the number of migrations and the corresponding application downtime. A sample scenario is presented, which clearly exposes the trade-off between the number of migrations and the average client-server latency. We then detail a theoretical model to determine the optimal allocation of applications to servers, in order to minimize the number of handovers. This model is based on the knowledge of the exact user movements and is only useful in an off-line setting. As this is impossible in real-time, several heuristics are presented. Their performance is compared and validated against the theoretical model.