Robust multiclass signaling overload control

We propose multi-class signaling overload control algorithms, for telecommunication switches, that are robust against different input traffic patterns and system upgrades. In order to appropriately measure the system load when several classes of signaling traffic are present, we first introduce the concept of equivalent system load measure that converts the multiple system measures associated with different classes of traffic into a single measure with respect to a pre-defined base class. We use this measure to develop three multi-class overload detection and measurement algorithms. Next, we develop a new algorithm for partitioning the allowable equivalent system load across multiple traffic classes, using a strict priority scheme. Using simulations of call flows from mobile telecommunications standards, we compare different multi-class overload algorithms under a variety of overload conditions. Our simulation results indicate that our algorithm that measures system load using a combination of request acceptance rate and processor occupancy provides highly reactive and robust overload control. Last, for the purpose of making the overload control algorithms more robust, we propose a measurement-based simple regression technique to dynamically estimate key system parameters. We find that estimates derived in this manner converge rapidly to their true values.