An adaptive, dynamic buffer management (ADBM) approach for input buffers in ATM networks

Current literature on input buffer management reveals that, in representative ATM networks under highly bursty traffic conditions, the fuzzy thresholding approach yields lower cell loss rate at the cost of lower throughput. Also, under less bursty traffic, the traditional fixed thresholding approach achieves higher throughput at the expense of higher cell loss rate. The translation of this finding into practice, termed adaptive dynamic input buffer management (ADBM), is the objective of this paper. The argument is that, given that the traffic conditions are constantly changing, to achieve efficiency during actual operation, the network control must dynamically switch, at every ATM switch, under the call processor´s control, between the two input buffer management techniques, dictated by the nature of the traffic at the inputs of the corresponding switch. In order to best characterize the nature of the incoming traffic, the ADBM technique relies on the use of a counter and a choice of a time interval. The counter best determines the burstiness nature of the input traffic by counting the number of cells that are intercepted at the input of the switch over a defined time interval. The challenge posed by this proposition lies in the very definition of burstiness in that the time interval must approach, in the limit, zero or the resolution of time in the network. To address this challenge, a 15-node representative ATM network is modeled in an asynchronous, distributed simulator and, simulated on a network of workstations under realistic traffic stimuli. Burstiness indices are measured for the synthetic, stochastic traffic at the inputs of every ATM switch as a function of the progress of simulation for different choices of time interval values. Simulation results reveal superior performance for ADBM, with a throughput of 74.77% that is higher than even the pure fixed scheme, and cell drop rate of 2.21% that is lower than that of the pure fuzzy scheme. In essence, ADBM successfully integrates the best characteristics of the fuzzy and fixed thresholding schemes