Proceedings of the seventh international conference (1990) on Machine learning
Using local models to control movement
Advances in neural information processing systems 2
IEEE INFOCOM '92 Proceedings of the eleventh annual joint conference of the IEEE computer and communications societies on One world through communications (Vol. 2)
SIGCOMM '92 Conference proceedings on Communications architectures & protocols
ATM scheduling with queuing delay predictions
SIGCOMM '93 Conference proceedings on Communications architectures, protocols and applications
Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment
Journal of the ACM (JACM)
Multidimensional binary search trees used for associative searching
Communications of the ACM
Introduction to Stochastic Dynamic Programming: Probability and Mathematical
Introduction to Stochastic Dynamic Programming: Probability and Mathematical
Learning to Predict by the Methods of Temporal Differences
Machine Learning
Internet protocol traffic analysis with applications for ATM switch design
Internet protocol traffic analysis with applications for ATM switch design
ATM scheduling with queuing delay predictions
SIGCOMM '93 Conference proceedings on Communications architectures, protocols and applications
A methodology and algorithms for the design of hard real-time multitasking ASICs
ACM Transactions on Design Automation of Electronic Systems (TODAES)
A technique for QoS-based system partitioning
ASP-DAC '00 Proceedings of the 2000 Asia and South Pacific Design Automation Conference
On-line evolvable fuzzy system for ATM cell-scheduling
Journal of Systems Architecture: the EUROMICRO Journal
| Hi-index | 0.01 |
Efficient utilization of cell switched networks supporting diverse applications will require service disciplines that are well designed for the particular quality of service constraints and traffic mix, a difficult task in view of the paucity of information about the expected traffic. We demonstrate the use of on-line dynamic programming in an adaptive cell scheduling mechanism that can easily be engineered to meet arbitrary quality of service constraints. When the objective is to minimize the total cell loss rate, our algorithm, urgency scheduling, compares favorably with the optimal earliest deadline first algorithm. For more complex quality of service constraints where optimal scheduling algorithms are unavailable, the simulations show urgency scheduling can provide significant increases in the usable bandwidth of a link. The learning techniques we develop are quite general and should be readily applicable to other network control problems.