Bio-inspired self-adaptive rate control for multi-priority data transmission over WLANs

In Wireless Local Area Networks (WLANs), the unpredictable injection of traffic load and the limitations of DCF based bandwidth allocation may result in network congestion. Also the Quality of Service (QoS) of data flows with different priorities may not be strictly guaranteed. In order to support service differentiation and guarantee QoS of data transmission over WLANs, based on the extended Lotka–Volterra (LV) biological competitive model, a bio-inspired self-adaptive rate control approach for multi-priority data transmission is proposed in this paper. This approach guides data flows to compete for network bandwidth in the way of a native ecosystem. As a result, both service differentiation and QoS can be guaranteed, simultaneously. In particular, it also achieves higher bandwidth utilization. Then the proposed approach is applied to four categories of data flows defined in the EDCA protocol, the allocated bandwidth of each category is optimized through model parameters (i.e. competition coefficients among categories) optimization. Extensive simulation studies have been conducted to show the superior performance of the proposed approach. Under the recommended model parameter values, the total bandwidth utilization is maximized up to 93% compared with 60–70% achieved by the EDCA protocol, whilst maintaining the service differentiation of multi-priority flows. 2014 Elsevier B.V. All rights reserved.