Statistical CAC Methods in ATM

Admission control is a very useful tool for a network operator. It enables effective link utilization with QoS guaranty. Without doubts, CAC function will be important part in evolution of next generation networks. The question, how to choose suitable CAC method as admission control, is crucial for effective exploitation of CAC function. In this paper, we compare three statistical CAC methods providing their suitability as control for specific traffic: Method of Effective Bandwidth, Diffusion Approximation Method and Gaussian Approximation Method

Statistical multiplexing and connection admission control in ATM networks

Asynchronous Transfer Mode (ATM) technology is widely employed for the transport of network traffic, and has the potential to be the base technology for the next generation of global communications. Connection Admission Control (CAC) is the effective traffic control mechanism which is necessary in ATM networks in order to avoid possible congestion at each network node and to achieve the Quality-of-Service (QoS) requested by each connection. CAC determines whether or not the network should accept a new connection. A new connection will only be accepted if the network has sufficient resources to meet its QoS requirements without affecting the QoS commitments already made by the network for existing connections. The design of a high-performance CAC is based on an in-depth understanding of the statistical characteristics of the traffic sources