Queueing Systems: Theory and Applications
On the use of a stochastic estimator learning algorithm to the ATM routing problems: a methodology
ICCC '95 Proceedings of the 12th international conference on computer communication on Information highways : for a smaller world and better living: for a smaller world and better living
The use of learning algorithms in ATM networks call admission control problem: a methodology
ICCC '95 Proceedings of the 12th international conference on computer communication on Information highways : for a smaller world and better living: for a smaller world and better living
Real-time estimation of UPC parameters for arbitrary traffic sources in ATM networks
INFOCOM'96 Proceedings of the Fifteenth annual joint conference of the IEEE computer and communications societies conference on The conference on computer communications - Volume 1
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The traffic policing in ATM networks is one of the most critical preventive congestion control mechanisms. It intends to ensure that each source conforms to its traffic parameters negotiated during the Call Admission Control phase. In this paper, we enhance the known Leaky Bucket mechanism with a Learning Algorithm in order to police the distribution of the traffic, observing the values that the counter of the Leaky Bucket takes. As it will be shown, tighter and faster control is achieved by the proposed methodology for any type of traffic source, resulting in more statistical gain and better guarantee of the QoS constraints.