SCAD College of Engineering and Technology, Tirunelveli, India.
Department of Computer Science and Engineering, Annai Vailankanni College of Engineering, Kanyakumari, India.
Sci Rep. 2023 Jul 4;13(1):10810. doi: 10.1038/s41598-023-37952-x.
For the conservation and sustainable use of the oceanic environment, monitoring of underwater regions is ineluctable and is effectuated with the aid of an underwater wireless sensor network. It is accoutered with smart equipment, vehicles and sensors and utilized for the transmission of acquired data from the monitoring region and forwarded to the sink nodes (SN) where the data are retrieved. Moreover, data transmission from sensor nodes to SN is complicated by the aquatic environment's inherent complexities. To surpass those issues, the work in this article focusesto propose a Hybrid Cat Cheetah optimization algorithm (HCOA) that purveys the energy efficient clustering based routing. The network is then partitioned into numerous clusters, each of which is led by a cluster head (CH) and comprised of many sub-clusters (CM). Based on the factors such as distance and residual energy the CH selection is optimized and collects data from the respective CMs and forwarded to the SN with a multi-hop transmission approach. The proposed HCOA chooses the optimized multi-hop route from the CH to SN. Thus mitigates the complexities over multi-hop routing and CH selection. Simulations are effectuated in the NS2 simulator and analyzed the performance. The results of the study show that the proposed work has significant advantages over state-of-the-art works in terms of network lifetime, packet delivery ratio, and energy consumption. The energy consumption of the proposed work is 0.2 J with a packet delivery ratio is 95%.The network life time of proposed work, with respect to the coverage area around 14 km is approximately 60 h.
为了保护和可持续利用海洋环境,对水下区域的监测是不可避免的,这需要借助水下无线传感器网络来实现。该网络配备了智能设备、车辆和传感器,用于传输从监测区域采集的数据,并转发到接收节点(SN),在那里可以检索到数据。此外,由于水下环境固有的复杂性,传感器节点到 SN 的数据传输变得复杂。为了克服这些问题,本文的工作重点是提出一种混合猫猎豹优化算法(HCOA),提供基于能量有效的聚类路由。然后,网络被划分为多个簇,每个簇由一个簇头(CH)领导,由多个子簇(CM)组成。根据距离和剩余能量等因素,优化 CH 的选择,并从各个 CM 收集数据,采用多跳传输方式转发到 SN。所提出的 HCOA 从 CH 到 SN 选择优化的多跳路由。从而减轻了多跳路由和 CH 选择的复杂性。在 NS2 模拟器中进行了仿真,并对性能进行了分析。研究结果表明,与现有技术相比,所提出的工作在网络寿命、分组投递率和能量消耗方面具有显著优势。所提出的工作的能量消耗为 0.2J,分组投递率为 95%。在大约 14km 的覆盖区域内,所提出的工作的网络寿命约为 60 小时。