计算机科学
计算机网络
路由协议
水下
网络数据包
节点(物理)
信任管理(信息系统)
布线(电子设计自动化)
声传感器
延迟(音频)
无线传感器网络
可靠性(半导体)
低延迟(资本市场)
水声通信
路径(计算)
分布式计算
计算机安全
工程类
电信
功率(物理)
海洋学
物理
结构工程
量子力学
声学
地质学
作者
Rongxin Zhu,Azzedine Boukerche,Lijuan Feng,Qiuling Yang
出处
期刊:Ad hoc networks
[Elsevier]
日期:2023-10-01
卷期号:149: 103212-103212
被引量:5
标识
DOI:10.1016/j.adhoc.2023.103212
摘要
Underwater Acoustic Sensor Networks (UASNs) are widely applied in marine based applications, but traditional security mechanisms are not feasible due to the underwater sensor nodes’ limited constraints and capabilities. Moreover, few existing routing protocols for underwater sensor networks considered underwater transmision limited constraints. In this paper, we propose T-SAPR, a trust management-based secure routing protocol with AUV-aided path repairing that addresses these challenges. T-SAPR uses an attention-based long short-term memory (LSTM) to build a trust model that considers node trust, communication trust, and environment surrounding’s trust. T-SAPR evaluates trust evidence to measure the trust level of the sensor nodes in the network and uses energy, packet delivery ratio, and latency jointly to seek optimal routing policies in the reward function of Q-Learning. Additionally, we propose a repairing mechanism with the assistance of AUVs to improve the reliability of UASNs in cases of multiple sensor node failures or the detection of malicious nodes. Evaluation results show that T-SAPR identifies malicious nodes by detecting their anomalous behavior while improving the packet delivery ratio and energy efficiency by 13.3% and 48.1% as compared to existing algorithms such as GEDAR, TADR-EAODV, and AFSA-ACOA-SCP.
科研通智能强力驱动
Strongly Powered by AbleSci AI