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.

Telecommunication switches implement overload controls to maintain call throughput and delay at acceptable levels during periods of high load. Existing work has mostly focused on controls under sustained overload-they do not meet the demands of modern telecommunication systems where the increased number of services and mobile subscribers often creates fast changing hot spots. We introduce new algorithms that are designed to be highly reactive to sudden bursts of load. One algorithm is a modified version of RED for signaling traffic that measures the queue size. The second algorithm uses two measures: call acceptance rate and processor occupancy. Using simulations of realistic system models, we compare these new algorithms with each other and an existing algorithm that uses processor occupancy only. Our simulation results and qualitative arguments show that the combination of acceptance rate and processor occupancy results in a highly reactive and robust signaling overload control.