Autonomous Decentralized Flow Control in High-Speed Networks with Inhomogeneous Configurations

SUMMARY Recent growth in computer communications has led to an increased requirement for high-speed backbone networks. In such highspeed networks, the principle adopted for a time-sensitive flow control mechanism should be that of autonomous decentralized control. In this mechanism, each node in a network manages its local traffic flow only on the basis of the local information directly available to it, although it is desirable that the individual decisions made at each node lead to high performance of the network as a whole. In our previous studies, we have investigated the behavior of local packet flows and the global performance achieved when a node is congested, and proposed the diffusion-type flow control model. However, since we used a simple and homogeneous network model in the evaluation, the results cannot be generalized. In this paper, we propose an extension of the diffusion-type flow control model in order to apply it to networks with inhomogeneous configurations. We show simulation results for two cases: different propagation delays and multiple bottlenecks. Both results show that the proposed diffusion-type flow con

[1]  Jean C. Walrand,et al.  Fair end-to-end window-based congestion control , 2000, TNET.

[2]  Danny Raz,et al.  Global optimization using local information with applications to flow control , 1997, Proceedings 38th Annual Symposium on Foundations of Computer Science.

[3]  Ramesh Johari,et al.  End-to-end congestion control for the internet: delays and stability , 2001, TNET.

[4]  Masaki Aida,et al.  Stability and adaptability of autonomous decentralized flow control in high-speed networks , 2003, The Sixth International Symposium on Autonomous Decentralized Systems, 2003. ISADS 2003..

[5]  Leandros Tassiulas,et al.  A Simple Rate Control Algorithm for Maximizing Total User Utility. , 2001, INFOCOM 2001.

[6]  Masaki Aida,et al.  Stability Analysis for Global Performance of Flow Control in High-Speed Networks Based on Statistical Physics , 1999 .

[7]  Steven H. Low,et al.  Optimization flow control—I: basic algorithm and convergence , 1999, TNET.

[8]  Debasis Mitra,et al.  Adaptive Algorithms for Feedback-Based Flow Control in High Speed, Wide-Area ATM Networks , 1995, IEEE J. Sel. Areas Commun..

[9]  R. Srikant,et al.  A decentralized adaptive ECN marking algorithm , 2000, Globecom '00 - IEEE. Global Telecommunications Conference. Conference Record (Cat. No.00CH37137).

[10]  Yossi Azar,et al.  Local optimization of global objectives: competitive distributed deadlock resolution and resource allocation , 1994, Proceedings 35th Annual Symposium on Foundations of Computer Science.

[11]  Baruch Awerbuch,et al.  Converging to approximated max-min flow fairness in logarithmic time , 1998, Proceedings. IEEE INFOCOM '98, the Conference on Computer Communications. Seventeenth Annual Joint Conference of the IEEE Computer and Communications Societies. Gateway to the 21st Century (Cat. No.98.

[12]  Masaki Aida,et al.  Stability of autonomous decentralized flow control schemes in high-speed networks , 2002, Proceedings 22nd International Conference on Distributed Computing Systems Workshops.

[13]  Toshiharu Sugawara,et al.  Traffic Control Scheme under the Communication Delay of High-speed Networks , 1996 .

[14]  Debasis Mitra,et al.  Optimal design of windows for high speed data networks , 1990, Proceedings. IEEE INFOCOM '90: Ninth Annual Joint Conference of the IEEE Computer and Communications Societies@m_The Multiple Facets of Integration.

[15]  Steven H. Low,et al.  An IP implementation of optimization flow control , 1998, IEEE GLOBECOM 1998 (Cat. NO. 98CH36250).