Estimation-based call admission control with delay and loss guarantees in ATM networks

Call admission control (CAC) has been accepted as a potential solution for supporting a variety of traffic sources demanding different quality of service guarantees in asynchronous transfer mode networks. Basically, CAC is required to consume a minimum of time and space to make call acceptance decisions. A CAC algorithm is presented based on a novel estimation method, called quasilinear dual-class correlation (QLDC). All heterogeneous traffic calls are initially categorised into various classes. According to the number of calls in each traffic class, QLDC conservatively and precisely estimates the cell delay and cell loss ratio for each traffic class via simple vector multiplication. These vectors are computed in advance from the results of three dual arrival queuing models, M^[N(1/])+Isup [N(2/])/D/1/K, M₁ ^[N(1/])+Msub 2/^[N(2/])D/1/K and I₁^[N(1/])+Isub 2/^[N(2/])D/1/K, where M and T represent the Bernoulli process and the interrupted Bernoulli process, respectively. Consequently, the authors´ QLDC-based CAC, as is shown, yields a low time complexity O(C) (in vector multiplications) and space complexity O(WC²) (in bytes), where C is the total number of traffic classes and W is the total number of aggregate load levels. Numerical examples are also employed to justify that the QLDC-based estimated results profoundly agree with the simulation results in both the single-node and end-to-end cases