Gopal N. Kumar

Statistical algorithms in fault detection and prediction: Toward a healthier network

Very high reliability/availability at affordable cost requires a proactive approach to system faults and failures. This calls for sophisticated fault detection algorithms that ultimately could evolve into fault prediction strategies. This paper presents statistical algorithms — the Operational Fault Detection (OFD) class of algorithms — toward reaching these goals. OFD algorithms analyze system performance metrics to detect fault signatures. The concept behind OFD is to raise alarms for conditions that adversely impact customer revenue or system performance. Initial versions of OFD, deployed in the field, count meaningful events and raise alarms when a test statistic, based on the event counts, exceeds a predefined threshold. Setting the thresholds required human intervention. This is considered time consuming by our customers, even though the concepts of OFD have been well received. This paper suggests a new generation — the second-generation OFD — that is inherently adaptive and requires minimal human intervention. These new algorithms are designed to detect system performance degradations, paving the way to more mature fault prediction strategies. Detecting degradations is a precursor to fault predictions, as degradations are often early signatures of potentially catastrophic faults.

QoS control for streaming service in UMTS networks

This paper addresses the end-to-end quality of service (QoS) architecture and mechanisms for Universal Mobile Telecommunications System (UMTS) networks. It presents specific QoS control mechanisms and algorithms for network performance engineering for real time services, in particular streaming applications. The paper concentrates on QoS control in the UMTS terrestrial radio access network (UTRAN) since it is often a bottleneck in end-to-end UMTS bearer performance, especially in the initial stages of network deployment. It discusses several QoS implementation mechanisms, including air interface resource and congestion control, call admission control, mobility control, backhaul bandwidth management, and network element queuing control. Simulation results are presented to show the effectiveness of these controls, and ways they can be used to guarantee streaming bearer performance. In addition, real measurement results are given for a commercial end-to-end UMTS network.