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DIEER: Delay-Intolerant Energy-Efficient Routing with Sink Mobility in Underwater Wireless Sensor Networks

机译:DIEER:水下无线传感器网络中具有接收器移动性的不延迟的节能路由

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摘要

Underwater Wireless Sensor Networks (UWSNs) are an enabling technology for many applications in commercial, military, and scientific domains. In some emergency response applications of UWSN, data dissemination is more important, therefore these applications are handled differently as compared to energy-focused approaches, which is only possible when propagation delay is minimized and packet delivery at surface sinks is assured. Packet delivery underwater is a serious concern because of harsh underwater environments and the dense deployment of nodes, which causes collisions and packet loss. Resultantly, re-transmission causes energy loss and increases end-to-end delay ( ). In this work, we devise a framework for the joint optimization of , , ( ) and for reducing nodal propagation delay, maximizing throughput, improving network lifetime, and minimizing energy consumption. To evaluate our technique, we simulate the three-dimensional (3-D) underwater network environment with mobile sink and dense deployments of sensor nodes with varying communication radii. We carry out scalability analysis of the proposed framework in terms of network lifetime, throughput, and packet drop. We also compare our framework to existing techniques, i.e., Mobicast and iAMCTD protocols. We note that adapting varying based on node density in a range of network deployment scenarios results in a reduced number of re-transmissions, good energy conservation, and enhanced throughput. Furthermore, results from extensive simulations show that our proposed framework achieves better performance over existing approaches for real-time delay-intolerant applications.
机译:水下无线传感器网络(UWSN)是一种启用技术,可用于商业,军事和科学领域的许多应用。在UWSN的某些紧急响应应用程序中,数据分发更为重要,因此,与以能量为中心的方法相比,这些应用程序的处理方式有所不同,只有当传播延迟最小化并确保在表面接收器处传输数据包时,才有可能。由于恶劣的水下环境和节点的密集部署,水下的数据包传送是一个严重的问题,这会导致冲突和数据包丢失。结果,重传会导致能量损失并增加端到端延迟()。在这项工作中,我们设计了一个框架,用于,,()的联合优化以及减少节点传播延迟,最大化吞吐量,延长网络寿命并最小化能耗。为了评估我们的技术,我们使用移动接收器和具有可变通信半径的传感器节点密集部署来模拟三维(3-D)水下网络环境。我们根据网络生存期,吞吐量和数据包丢失对提议的框架进行可伸缩性分析。我们还将框架与现有技术进行比较,例如Mobicast和iAMCTD协议。我们注意到,在一系列网络部署方案中,根据节点密度进行变化适应会减少重传次数,节省能源,并提高吞吐量。此外,大量仿真结果表明,我们提出的框架相对于实时延迟不容忍应用的现有方法具有更好的性能。

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