In a heterogeneous distributed environment where multiple applications compete and share a limited amount of system resources, applications tend to suffer from variations in resource availability, and are desired to adapt their behavior to the resource variations of the system beyond a minimum Quality of Service (QoS) guarantee. On one hand, current adaptation mechanisms built within an application have the disadvantage of lacking global information to preserve fairness among all applications. On the other hand, an adaptive resource management built within the operating system ignores the data semantics of the application. Hence we believe that a proper adaptive behavior of QoS can be achieved in a middleware framework, having data semantics of the application as well as understanding underlying resource management dynamics. We present a novel control-based middleware framework to enhance QoS adaptations by dynamic control and reconfigurations to the internal functionalities of a distributed multimedia application. Based on a strict model defining QoS metrics, and the Task Flow Model describing the application structure, a Task Control Model is developed based on the control theory. The control theory is applied to the design of Adaptation Tasks to devise control policies for changes of resource requests by individual applications, hence providing graceful degradation or upgrade over a shared resource within a required QoS range, or in extreme cases enforcing reconfiguration process beyond the QoS range. Our assumptions here are that (1) a resource reservation/allocation occurs to preserve the minimal QoS requirement of an application, and (2) not all resource capacity is allocated to reserved service. The adaptation happens over the non-reserved shared capacity. Using this approach, we are able to reason about and validate analytically system attributes such as the stability, agility, fairness and equilibrium values of the control actions over shared resources. Our validation is not only analytical, but also experimental. We have developed an experimental clientserver visual tracking system to evaluate our middleware framework. In order to maintain tracking precision in a specified range, the middleware framework controls the tracking application according to the current system dynamics. We show that our framework improves the adaptive abilities of the application, while the adaptive actions are stable, flexible and configurable according to the needs of individual applications. Furthermore, we show a quantitative improvement of resource utilization in comparison to over-allocation approach when QoS guarantees in range are required.
For example, Li and Nahrstedt presented a fuzzy-controller on a sender node that dynamically adjusts the sending rate in a distributed visual tracking system REF .
A Control-Based Middleware Framework for Quality of Service Adaptations
IEEE Journal on Selected Areas in Communications
Computer Science