Friday, July 26
The traffic carried by developing packet-based, high-speed communication networks is statistical and diverse in its nature. Network designers must maintain adequate quality of service to the individual users while efficiently utilizing network resources. Traditional mathematical techniques for modeling traffic and resource allocation methods are proving to be inadequate in effectiveness and/or complexity, so much current research is focusing on emerging techniques. The minisymposium includes talks on self-similar traffic models, performance prediction, feedback rate control design, and fuzzy logic control.
Traffic Modeling and Control for High Speed Communication Networks
Organizer: David W. Petr
University of Kansas
- Models of Fractal Traffic
- Arnie Neidhardt, Bellcore
- Real-Time Detection of Quality of Service Violations in High-Speed Networks
- Victor Frost; and Hongbo Zhu, University of Kansas
- Design of a Closed Loop Feedback Control for ABR Service
- Aleksandar Kolarov; and G. Ramamurthy, NEC USA Inc.
- Self-Tuning Fuzzy Control for Available Bit Rate (ABR) Traffic
- David W. Petr, Organizer; and Qingyang Hu, University of Kansas