Experimentation with Event-Based Methods of Adaptive Quality of Service Management

Many complex distributed applications require quality of service (QoS) guarantees on the end-to-end transfer of information across a distributed system. A major problem faced by any system, or infrastructure, providing QoS guarantees to such applications is that resource requirements and availability may change at run-time. Consequently, adaptive resource (and, hence, service) management mechanisms are required to guarantee quality of service to these applications. This paper describes different methods of adaptive quality of service management, implemented with the eventbased mechanisms offered by the Dionisys quality of service infrastructure. Dionisys allows applications to influence: (1) how service should be adapted to maintain required quality, (2) when such adaptations should occur, and (3) where these adaptations should be performed. In Dionisys, service managers execute application-specific functions to monitor and adapt service (and, hence, resource usage and allocation), in order to meet the quality of service requirements of adaptable applications. This approach allows service managers to provide service in a manner specific to the needs of individual applications. Moreover, applications can monitor and pin-point resource bottlenecks, adapt their requirements for heavily-demanded resources, or adapt to different requirements of alternative resources, in order to improve or maintain their overall quality of service. Likewise, service managers can cooperate with other service managers and, by using knowledge of application-specific resource requirements and adaptation capabilities, each service manager can make better decisions about resource allocation. Using a real-time client-server application, built on top of Dionisys, we compare alternative strategies for adapting and coordinating CPU and network services. In this fashion, we demonstrate the importance of flexibility in quality of service management. This work is supported in part by DARPA through the Honeywell Technology Center under contract numbers B09332478 and B09333218, and by the British Engineering and Physical Sciences Research Council with grant number 92600699.