On the use of genetic algorithms in the medium access control of broadcast communication networks

Time division multiple access protocols suffer from poor performance when the offered traffic is bursty. In this paper, an adaptive time division multiple access protocol, which is capable of operating efficiently under bursty traffic conditions, is introduced. According to the proposed protocol, the station which is granted permission to transmit at each time slot is selected by means of a variation of the well-known population-based incremental learning (PBIL) genetic algorithm. The choice probability of the selected station is updated by taking into account the network feedback information. In this way, the proposed protocol is always capable of being adapted to the sharp changes of the station´s traffic. Extensive simulation results are presented which indicate that the proposed protocol achieves a significantly higher performance than other well-known time division multiple access protocols when operating under bursty traffic conditions.