Monitoring QoS distribution in multimedia networks

Introduction P roviding quality of service (QoS) guarantees is an important requirement for multimedia networks. To maintain agreed QoS, it is not sufficient to just commit resources because QoS degradation can be caused by many factors and is often unavoidable, e.g. any fault or weakening of the performance of a network element may result in the degradation of contracted QoS. Thus, performance management is required to ensure that the contracted QoS is sustained.1 To date, there has been a considerable amount of research within the field of QoS management support for multimedia networks, including the service model,2 QoS control3 and QoS architecture,4 approaches. However, one limitation still exists: the lack of distributed monitoring mechanisms to support QoS guarantees.4 The intention of QoS monitoring research is to allow a network manager to track the ongoing QoS, compare monitored QoS against expected performance, detect possible QoS degradation, and then tune network resources accordingly to sustain the delivered QoS.4 Since the real-time flow of a multimedia application may cross several network segments that provide different levels of QoS, in order to locate the segment(s) causing possible QoS degradation, QoS monitoring should be based on QoS distribution monitoring instead of end-to-end monitoring, i.e. a network manager should be capable of monitoring the distribution of QoS experienced by the flow in different network segments in order that the manager can locate the cause of possible QoS degradation. This paper presents two schemes for QoS distribution monitoring. They are the relevant monitor (RM)-based scheme and improved relevant monitor (IRM)-based scheme. With these schemes, when monitoring a real-time flow, a network manager can locate relevant monitors that are metering the flow, and retrieve traffic information from them simultaneously. By consolidating the information from these monitors that are embedded in different network segments, not only can end-to-end QoS be monitored, but the QoS distribution in different network segments for this flow can also be derived. Based on these schemes, the network manager can locate the cause of possible QoS degradation and thus control the network accordingly. The rest of this paper is organized as follows. The next section presents the challenges involved in QoS monitoring and gives an outline of previous work in the areas of application-level monitoring and QoS monitoring. The third section introduces two new schemes, RM-based and IRM-based, for QoS distribution monitoring. The fourth section describes CORBA-based implementations of the two schemes which show their feasibility. The fifth section provides the implementation details of our prototypes and some results. The methods for deriving QoS related parameters and for synchronizing traffic displays are also introduced in this section. After this, the sixth section presents a qualitative comparison among monitoring mechanisms surveyed in the second section and presented in the third section. The final section offers some concluding remarks.