Distributed protocols for ad hoc wireless LANs: a learning-automata-based approach
An ad hoc learning-automata-based protocol for wireless LANs, capable of operating efficiently under bursty traffic conditions, is introduced. According to the proposed protocol, the mobile station that is granted permission to transmit is selected by means of learning automata. At each station, the learning automaton takes into account the network feedback information in order to update the choice probability of each mobile station. The proposed protocol is compared via simulation to TDMA and IEEE 802.11 under bursty traffic conditions. Ad hoc learning-automata-based protocol (AHLAP) is shown to exhibit superior performance compared to TDMA in all cases. Compared to IEEE 802.11, the burstier the network traffic, the larger the performance increase of AHLAP. Furthermore, the implementation of AHLAP is more easier than that of IEEE 802.11.
learning automata ad-hoc self-adaptive wlan mac