Wireless and Mobile Network Architectures
Wireless and Mobile Network Architectures
Scheduling Disciplines in Cellular Data Services with Probabilistic Location Errors
ICN '01 Proceedings of the First International Conference on Networking-Part 1
Feedback Control with Queueing-Theoretic Prediction for Relative Delay Guarantees in Web Servers
RTAS '03 Proceedings of the The 9th IEEE Real-Time and Embedded Technology and Applications Symposium
How Unfair can Weighted Fair Queuing be?
ISCC '00 Proceedings of the Fifth IEEE Symposium on Computers and Communications (ISCC 2000)
Real-Time Resource Reservation for Synchronized Multimedia Object over Wireless LAN
ISORC '02 Proceedings of the Fifth IEEE International Symposium on Object-Oriented Real-Time Distributed Computing
QoS-Oriented Packet Scheduling for Wireless Multimedia CDMA Communications
IEEE Transactions on Mobile Computing
The role of Internet technology in future mobile data systems
IEEE Communications Magazine
Wireless mobile communications at the start of the 21st century
IEEE Communications Magazine
Providing quality of service over a shared wireless link
IEEE Communications Magazine
Architecture for mobility and QoS support in all-IP wireless networks
IEEE Journal on Selected Areas in Communications
Technical Communication: Feedback QoS control scheme for wireless network applications
Computers and Electrical Engineering
Hi-index | 0.00 |
Multi-functional and high-quality services are indispensable for providing responsive information services in a highly interactive e-learning system. This work presents a problem-solving mechanism using closed-loop scheduling discipline to achieve QoS e-learning applications. In the closed-loop schedule, the feedback mechanism supports wireless mobile communications services with dynamic QoS requirements. This work presents a closed-loop architecture by cascading the open-loop schedule, the QoS probe, the Proportional-Integral-Derivative (PID) controller and the feedback mechanism. In this architecture, the relationship between input and output is defined using a Lagrange λ -calculus module. The module estimates the future QoS according to the current scheduling, while the controller parameters are tuned according to the system status to achieve dynamic scheduling. Simulation results with e-learning activities demonstrate that the closed-loop schedule outperforms existing disciplines in terms of service delay and system utilization.