ABR Congestion Control in ATM Networks Using Neural Networks
ICN '01 Proceedings of the First International Conference on Networking-Part 2
Flow control in the high-speed Thunder and Lightning ATM network
Computer Communications
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** Central Bureau of Statistics, IndonesiaAbstract: The ATM Forum has chosen a rate-based scheme as an approach to congestion control for Available Bit Rate (ABR) services. So far, many rate-based schemes, such as Forward Explicit Congestion Notification (FECN), Backward Explicit Congestion Notification (BECN), and Proportional Rate Control Algorithm (PRCA), has been proposed. In FECN and BECN, which use negative feedback rate control, the over-all network congestion collapse may occur, if all notification cells in backward direction experience extreme congestion. The PRCA use positive feedback to solve the drawbacks of the FECN and BECN, but unfair distribution of available bandwidth among Virtual Connections (VCs) may occur. To resolve the problems of the existing rate-based schemes, in this paper, we propose a new adaptive congestion control scheme called the Self Detective Congestion Control (SDCC) scheme. We show that the SDCC scheme can achieve good fairness performance among connection classes existing in the network. In transient behavior, the SDCC scheme offers fast access to available bandwidth, which is a sensible requirement, particularly in LAN and MAN environments. Furthermore, by allocating control cells based on networks scales, the scheme is able to control a number of greedy sources with moderate size buffers.