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首页> 外文期刊>Procedia Computer Science >AEDG: AUV-aided Efficient Data Gathering Routing Protocol for Underwater Wireless Sensor Networks
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AEDG: AUV-aided Efficient Data Gathering Routing Protocol for Underwater Wireless Sensor Networks

机译:AEDG:用于水下无线传感器网络的AUV辅助高效数据收集路由协议

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Underwater Wireless Sensor Networks (UWSNs) are getting growing interest because of wide-range of applications. Most applications of these networks demand reliable data delivery over longer period in an efficient and timely manner. However, resource- constrained nature of these networks makes routing in a harsh and unpredictable underwater environment challenging. Most existing schemes either employ mobile sensors or a Mobile Sink (MS). However, cost of movement and sensors make such schemes infeasible. MS based schemes are not suitable for delay-sensitive large-scale applications. Unlike prior work, this paper presents a novel AUV-aided Efficient Data Gathering Routing Protocol (AEDG) for reliable data delivery. To prolong network lifetime, AEDG employs an Autonomous Underwater Vehicle (AUV) to collect data from gateways. To minimize energy consumption, we use a Shortest Path Tree (SPT) algorithm while associating sensor nodes with the gateways and devise a criterion to limit the association count of nodes. Moreover, the role of gateways is rotated to balance the energy consumption. To prevent data loss, AEDG allows dynamic data collection time to AUV depending up the count of member sensors for each gateway. Moreover, we formulate a MILP model, that increases network throughput as well as conserves energy by limiting the assignment of member nodes. The performance of the AEDG is validated through simulations. Simulation results demonstrate the effectiveness of AEDG in terms of various performance metrics.
机译:由于应用范围广泛,水下无线传感器网络(UWSN)引起了越来越多的兴趣。这些网络的大多数应用都要求以有效,及时的方式在更长的时间内可靠地传递数据。然而,这些网络的资源受限性质使得在恶劣且不可预测的水下环境中进行路由具有挑战性。大多数现有方案都采用移动传感器或移动接收器(MS)。然而,运动和传感器的成本使得这种方案不可行。基于MS的方案不适用于对延迟敏感的大规模应用。与以前的工作不同,本文提出了一种新颖的AUV辅助高效数据收集路由协议(AEDG),用于可靠的数据传递。为了延长网络寿命,AEDG使用了自动水下航行器(AUV)从网关收集数据。为了最大程度地减少能耗,我们在将传感器节点与网关相关联的同时使用了最短路径树(SPT)算法,并设计了一个标准来限制节点的关联数。而且,网关的角色被轮换以平衡能耗。为了防止数据丢失,AEDG允许动态数据收集时间到AUV,具体取决于每个网关的成员传感器数量。此外,我们制定了MILP模型,该模型通过限制成员节点的分配来增加网络吞吐量并节省能源。 AEDG的性能已通过仿真验证。仿真结果证明了AEDG在各种性能指标方面的有效性。

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