Sea lion optimization algorithm based node deployment strategy in underwater acoustic sensor network,International Journal of Communication Systems

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Sea lion optimization algorithm based node deployment strategy in underwater acoustic sensor network
International Journal of Communication Systems ( IF 1.7 ) Pub Date : 2021-01-12 , DOI: 10.1002/dac.4723
Kamal Kumar Gola ₁ , Nishant Chaurasia ₂ , Bhumika Gupta ₃ , Deepak Singh Niranjan ₄

Affiliation

In the ocean, huge number of sensor nodes (SNs) are located to transfer the information between other nodes using the Underwater Acoustic Sensor Network (UASN) framework. An underwater acoustic communication technique is utilized by this UASN to exchange the information. Because of environmental conditions and adverse channel, the SNs in UASN may have link breakages. Likewise, maximum target coverage rate for SN deployment is considered as another issue. So it is very essential to create a strong communication system in underwater together with the different kind of variations in ocean environment. As a result, the system will perform better data transmission with the severely fluctuating underwater communication conditions. In this paper, a latest optimization algorithm named as Sea Lion Optimization (SLO) procedure is proposed to discover the optimal location for SN in underwater communication. This algorithm optimally places the acoustic SNs based on the maximum connectivity rate by finding the targeted optimal position. The Matlab tool is utilized for implementation purpose, and the different kinds of parameters like connectivity rate, coverage rate, and delay are taken to evaluate the performance of proposed methodology. Moreover, the existing methods like deployment scheme, Connected Dominating set based depth computation Approach (CDA) approach, and distributive approach are taken to contrast the performance of proposed methodology. When compared to the previous algorithms, our proposed methodology achieves 95% connectivity ratio for varying number of acoustic SNs.

中文翻译：

水下声传感器网络中基于海狮优化算法的节点部署策略

在海洋中，使用水下声学传感器网络（UASN）框架定位了大量传感器节点（SN），以在其他节点之间传输信息。该UASN利用水下声学通信技术来交换信息。由于环境条件和不利的信道，UASN中的SN可能存在链路中断。同样，SN部署的最大目标覆盖率也被视为另一个问题。因此，在水下创建强大的通信系统以及海洋环境的各种变化非常重要。结果，该系统将在水下通信条件剧烈波动的情况下执行更好的数据传输。在本文中，提出了一种新的名为Sea Lion Optimization（SLO）过程的优化算法，以发现水下通信中SN的最佳位置。该算法通过找到目标最佳位置，基于最大连接率来优化放置声学SN。Matlab工具用于实现目的，并采用不同类型的参数（如连接率，覆盖率和延迟）来评估所提出方法的性能。此外，采用现有方法（如部署方案，基于连接控制集的深度计算方法（CDA）方法和分布式方法）来对比所提出方法的性能。当与以前的算法相比时，我们提出的方法可以实现95％的连通率，适用于变化数量的声学SN。

更新日期：2021-02-12

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