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Certain Investigations on Energy-Efficient Fault Detection and Recovery Management in Underwater Wireless Sensor Networks

机译:水下无线传感器网络中节能故障检测和恢复管理的一定调查

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In recent years, underwater wireless sensor networks (UWSNs) have been widely applied to aquatic and military applications. Network survivability is an essential attribute to be considered in UWSN circumstance and various stratifications like node survivability, connectivity and rapid fault node detection and recovery. However, efficient and accurate fault tolerance mechanisms are required to prolong the network survivability in UWSN. In this research work, the energy-efficient fault detection and recovery management (EFRM) approach is proposed for the UWSN with relatively better network survivability. The hidden Poisson Markov model has been incorporated in EFRM to achieve efficient fault detection throughout the whole network. Thereafter, the recovered node can be selected by using the analytical network process model which facilitates to recover the larger number of nodes in the damaged region. The simulation results manifest that when the fault probability is 40%, the detection accuracy of the proposed EFRM is over 99%, and the false positive rate is below 2%. The detection accuracy is improved by up to 12% when compared with the existing state-of-the-art schemes.
机译:近年来,水下无线传感器网络(UWSNS)已广泛应用于水生和军事应用。网络生存能力是在UWSN环境中考虑的基本属性和节点生存能力,连接和快速故障节点检测和恢复等各种分层。然而,需要高效和准确的容错机制来延长UWSN中的网络生存能力。在本研究工作中,为UWSN提出了节能故障检测和恢复管理(EFRM)方法,具有相对更好的网络生存能力。隐藏的泊松马尔可夫模型已在EFRM中纳入EFRM,以实现整个网络的有效故障检测。此后,可以通过使用分析网络过程模型来选择恢复的节点,这便于恢复损坏区域中的较大数量的节点。仿真结果表明,当故障概率为40%时,所提出的EFRM的检测精度超过99%,假阳性率低于2%。与现有的最先进的方案相比,检测精度高达12%。

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