Adaptive RTO for Handshaking-based MAC Protocols in Underwater Acoustic Networks
Résumé
Underwater acoustic networks (UANs) are attracting interest in recent decades.The unique characteristics of the underwater acoustic channel, such as long propagationdelay, delay variance, and high bit error rate, present challenges for themedium access control (MAC) protocol design in UANs. Most existing mediumaccess control protocols ignore the delay variance which prevents the accurateestimation of round trip time (RTT). The expected RTT value can be used to computethe Retransmission Time-Out (RTO) or the waiting time in MAC. The estimationof RTT is also meaningful for Automatic Repeat re-Quest (ARQ) schemebecause the system should ensure reliable data transmissions in the presence ofhigh bit error rate in the underwater acoustic channel. By analyzing the impact ofRTO on throughput under the effect of delay variance, we conclude that the fixedRTO is inefficient and RTO should be adaptively set to improve the throughput.We present a novel approach of predicting the RTT using a Bayesian dynamiclinear model, and then adjust RTO adaptively according to the predicted values.Simulation results show that the predicted values can adapt quickly to the sample RTT values. Under the effect of RTT fluctuations, the Bayesian algorithm offersperformance gains in terms of throughput and prediction performance, comparingwith Karn’s algorithm. Our study highlights the value of predicting the RTT usingBayesian approach in underwater acoustic networks.