ATM Scheduling with Queuing Delay Predictions

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.

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