Uncertainty Measures associated with Fuzzy Rules for Connection Admission Control in ATM Networks

Abstract

This paper describes the application of Fuzzy Logic to Connection Admission Control (CAC) in Asynchronous Transfer Mode (ATM) broadband communications networks. CAC is a traffic control function that decides whether or not to admit a new connection on to the network, subject to ensuring the required quality of service of all the connections. Observations of the traffic in the ATM link (examples) are used to acquire knowledge on the behaviour of the ATM traffic. From this knowledge, the Fuzzy Logic based CAC (FCAC) can, then, infer the maximum expected ratio of cells lost per cells sent for a given connection in the presence of a particular traffic scenario. Uncertainty measures associated with each of the fuzzy rules enable to measure the uncertainty generated by the number of positive and negative examples for a rule. This way, not only the matching rule(s) for a certain input but also the uncertainty measure for this rule(s) will influence the fuzzily inferred output. A study is made to evaluate the cell loss ratio for an ATM link carrying variable bit rate traffic; the results obtained with the FCAC are compared with results obtained using analytical CAC algorithms.