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ÐThis paper considers the support of hard real-time connections in ATM networks. In an ATM network, a set of hard realtime connections can be admitted only if the worst case end-to-end delays of cells belonging to individual connections are less than their deadlines. There are several approaches to managing the network resources in order to meet the delay requirements of connections. This paper focuses on the use of traffic regulation to achieve this objective. Leaky buckets provide simple and userprogrammable means of traffic regulation. An efficient optimal algorithm for selecting the burst parameters of leaky buckets to meet connections' deadlines is designed and analyzed. The algorithm is optimal in the sense that it always selects a set of burst parameters whose mean value is minimal and by which the delay requirements of hard real-time connections can be met. The exponential size of the search space makes this problem a challenging one. The algorithm is efficient through systematically pruning the search space. There is an observed dramatic improvement in the system performance in terms of the connection admission probability when traffic is regulated using this algorithm. Index TermsÐATM network, hard real-time communication, network delay analysis, traffic regulation.

In this paper u e study the effect of the output link scheduling disciplin6 of an A T M switch on ihe ability of an ATM L A N lo admit real-time connections. Three ouiput link scheduling policies are studied: First Come Farst Served (FCFS), Round Robin (RR), and Packei-by-packet Generalized Processor Sharing (PGPS). Wc derive connection admission criteria for the threc: scheduling policies. To evaluate the performance of the three scheduling policies, we introduce the metric of admission probability. The admission probability giws the probability that a randomly chosen set of real-lime connections will be admitted into the network. The admisszon probability allows system designers l o .study the performance of different scheduling policies over a wide range of network loads. W e ohservc ihat the performance of the ihree scheduling policies 1s sensitive to message deadlines. When the dcadlinr~s are small, PGPS outperforms both R R and FCFS, and R R outperforms FCFS.When the deadlines are large, all three scheduling policies perform the slime. We also note that although PGPS is better thari RR 2nd FCFS most of the time, its improved perfonmnct is achieved at the cost of high Implementation coniplexity and run time overheads.

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