Learning automata-based polling protocols for wireless LANs

Abstract

A learning automata-based polling (LEAP) protocol for wireless LANs, capable of operating efficiently under bursty traffic conditions, is introduced. We consider an infrastructure wireless LAN, where the access point (AP) is located at the center of a cell which comprises a number of mobile stations. According to the proposed protocol, the mobile station that is granted permission to transmit is selected by the AP by means of a learning automaton. The learning automaton takes into account the network feedback information in order to update the choice probability of each mobile station. It is proved that the learning algorithm asymptotically tends to assign to each station a portion of the bandwidth proportional to the station's needs. LEAP is compared to the randomly addressed polling and group randomly addressed polling protocols and is shown to exhibit superior performance under bursty traffic.