Efficient flow and congestion control for self-similar traffic in ATM networks

Asynchronous Transfer Mode (ATM) has emerged as one of the most promising solutions for the next generation networks since being adopted as the transfer mode of broadband integrated services digital networks (B-ISDN). With the advent of the high speed, multimedia networks, ATM must support applications with diverse traffic characteristics and quality of service (QoS) requirements. An accurate traffic characterization and modeling is, therefore, of primary importance in implementing effective flow control strategies and in making efficient use of network resources in ATM networks.; Recent studies have verified self-similar or fractal-like behaviors of the traffic over local and wide area networks, which implies that it is more appropriate to model this traffic using a self-similar process than using a traditional Poisson-based process. In this Ph.D. research, we investigate the properties of self-similar processes in great detail. We present a queueing model with a fractional Gaussian noise arrival process and deterministic service time. This queueing model is radically distinct from conventional queueing models whose arrival process does not take into account the self-similarity of incoming traffic. Our simulation results show that the latter leads to a substantial amount of inaccuracy in terms of network performance. Based on the queueing model, we propose a preventive flow control scheme suited for self-similar traffic using a Connection Admission Control (CAC). This CAC takes into account the Hurst parameter of traffic sources. The numerical results show that the proposed CAC ensures the QoS and achieves more admitted connections than the peak rate allocation CAC does.; In this research, we also propose a rate-based flow control scheme suited for real-time traffic. The main goal of the flow control scheme is to increase the network utilization with a margin of degradation in cell loss ratio. The proposed flow control scheme predicts the evolution of buffer occupancy over time using a linear predictor. We use a Proportional-plus-Integral-plus-Derivative (PID) controller to update the optimum sending rate at the transmitter dynamically. The adaptive policy attempts to keep the buffer occupancy for each virtual channel at a steady level, and the simulation results show that the proposed scheme works effectively against network congestion.