A quality of service architecture that combines resource reservation and application adaptation

Reservation and adaptation are two well-known and effective techniques for enhancing the end-to-end performance of network applications. However, both techniques also have limitations, particularly when dealing with high-bandwidth, dynamic flows: fixed-capability reservations tend to be wasteful of resources and hinder graceful degradation in the face of congestion, while adaptive techniques fail when congestion becomes excessive. We propose an approach to quality of service (QoS) that overcomes these difficulties by combining features of reservations and adaptation. In this approach, a combination of online control interfaces for resource management, a sensor permitting online monitoring, and decision procedures embedded in resources enable a rich variety of dynamic feedback interactions between applications and resources. We describe a QoS architecture, GARA, that has been extended to support these mechanisms, and use three examples of application-level adaptive strategies to show how this framework can permit applications to adapt both their resource requests and behavior in response to online sensor information.

[1]  Klara Nahrstedt,et al.  A control-based middleware framework for quality-of-service adaptations , 1999, IEEE J. Sel. Areas Commun..

[2]  Van Jacobson,et al.  A Two-bit Differentiated Services Architecture for the Internet , 1999, RFC.

[3]  David L. Black,et al.  An Architecture for Differentiated Service , 1998 .

[4]  Kang G. Shin,et al.  Understanding and improving TCP performance over networks with minimum rate guarantees , 1999, TNET.

[5]  Frank Siqueira,et al.  Delivering QoS in open distributed systems , 1999, Proceedings 7th IEEE Workshop on Future Trends of Distributed Computing Systems.

[6]  Klara Nahrstedt,et al.  A distributed resource management architecture that supports advance reservations and co-allocation , 1999, 1999 Seventh International Workshop on Quality of Service. IWQoS'99. (Cat. No.98EX354).

[7]  Jeffrey S. Vetter,et al.  Autopilot: adaptive control of distributed applications , 1998, Proceedings. The Seventh International Symposium on High Performance Distributed Computing (Cat. No.98TB100244).

[8]  A. L. Narasimha Reddy,et al.  Realizing throughput guarantees in a differentiated services network , 1999, Proceedings IEEE International Conference on Multimedia Computing and Systems.

[9]  Henning Schulzrinne,et al.  Comparison of Adaptive Internet Multimdia Applications , 1999 .

[10]  Daniel P. Siewiorek,et al.  A resource allocation model for QoS management , 1997, Proceedings Real-Time Systems Symposium.

[11]  Zheng Wang,et al.  An Architecture for Differentiated Services , 1998, RFC.

[12]  Calton Pu,et al.  Adaptive Resource Management via Modular Feedback Control , 1999 .

[13]  Gregor von Laszewski,et al.  Distance Visualization: Data Exploration on the Grid , 1999, Computer.

[14]  Giorgio Ventre,et al.  Distributed advance reservation of real-time connections , 1997, Multimedia Systems.

[15]  Henning Schulzrinne,et al.  The Loss-delay Based Adjustment Algorithm: a Tcp-friendly Adaptation Scheme , 1998 .

[16]  Raj Yavatkar,et al.  Integrated CPU and network-I/O QoS management in an endsystem , 1998, Comput. Commun..

[17]  Klara Nahrstedt,et al.  QualProbes: Middleware QoS Profiling Services for Configuring Adaptive Applications , 2000, Middleware.

[18]  J. Le Boudec,et al.  Scalable resource reservation for the Internet , 1997, Proceedings of International Conference on Protocols for Multimedia Systems - Multimedia Networking.