Link Prediction and Route Selection Based on Channel State Detection in UASNs

Abstract

In Underwater Acoustic Sensor Networks (UASNs), data route is often disrupted by link interruption which will further lead to incorrect data transmission due to high propagation delay, Doppler effect, and the vulnerability of water environment in acoustic channel. So how to correctly transmit data when there are interrupted links on the data path is just the issue Delay Tolerant Networks (DTNs) aim to solve. In this paper, we propose a model to predict link interruption and route interruption in UASNs by the historical link information and channel state obtained by periodic detection. A method of decomposing and recomposing routes hop by hop in order to optimize route reselection is also presented. Moreover, we present a back-up route maintenance scheme to keep back-up routes with fresh information. In case of single route, we advance the idea to utilize the periodicity of environmental changes to help predict link interruption. In the simulation, we make comparisons on node energy consumption, end-to-end delay as well as bit error rate with and without link prediction. It can be derived that the network performance is significantly improved with our mechanism, so that our mechanism is effective and efficient while guaranteeing reliable data transmission.