面向IoUT网络的高效接收方发起的协同MAC协议

Tarpan Paul, Md. Tareq Mahmud, Md. Obaidur Rahman
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引用次数: 2

摘要

在水下环境探测和监测领域,水下物联网(Internet of underwater Things, IoUT)发挥着重要的作用。由于具有挑战性的IoUT环境,为传统地面网络设计的介质访问控制(MAC)协议无法在IoUT网络中有效地发挥作用。长传播延迟、高信道衰落和有限的带宽限制了无线电波在水下的使用。为了克服这些限制,声波是首选。此外,传感器的能量有限,在水下更换电池也不容易。因此,针对IoUT网络设计的基于重传和多传概念的MAC协议,由于传输延迟较高、带宽利用率较低、占空比较长,能效较低。在本文中,我们提出了一种节能的接收器发起的合作(E2RIC) MAC协议用于IoUT网络,其中数据接收器是自主水下航行器(AUV)。为了保证能源效率、通信可靠性和更高的传感器寿命,AUV为每个发送节点选择一个最优的合作者/中继器,通过消除重传和多次传输的概念来进行协同数据通信。与最先进的MAC方案相比,提议的e2ricc -MAC协议在能耗、整体网络吞吐量和端到端延迟方面表现出相当大的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
E2RIC: Energy-Efficient Receiver-Initiated Cooperative MAC Protocol for IoUT Networks
In the field of exploration and monitoring the underwater environment, the Internet of Underwater Things (IoUT) shows a significant influence nowadays. Due to the challenging IoUT environment, medium access control (MAC) protocols designed for traditional terrestrial networks cannot perform effectively in IoUT networks. Long propagation delay, high channel fading and limited bandwidth refrain radio waves to underwater usage. To overcome these limitations, acoustic waves are preferred. Moreover, a sensor has limited energy and battery replacement is not easy under water. Hence, retransmission and multiple transmission concept-based MAC protocols designed for IoUT networks are found energy inefficient due to suffering from higher transmission delay, lower bandwidth utilization and longer duty cycle. In this paper, we propose an Energy-Efficient Receiver-Initiated Cooperative (E2RIC) MAC Protocol for IoUT Networks where the data receiver is an autonomous underwater vehicle (AUV). To ensure energy efficiency, communication reliability and higher sensor lifetime, the AUV selects an optimal cooperator/relay for each of the sender nodes to perform cooperative data communication by eliminating retransmission and multiple transmission concepts. In comparison to the state-of-the-art MAC schemes, the proposed E2RIC-MAC protocol exhibits considerable improvements in terms of energy consumption, overall network throughput, and end-to-end latency.
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