Congestion centric multi-objective reptile search algorithm-based clustering and routing in cognitive radio sensor network,Transactions on Emerging Telecommunications Technologies

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Congestion centric multi-objective reptile search algorithm-based clustering and routing in cognitive radio sensor network
Transactions on Emerging Telecommunications Technologies ( IF 2.5 ) Pub Date : 2022-08-22 , DOI: 10.1002/ett.4629
D. Sunitha ₁ , Kavitha Rani Balmuri ₂ , Rocío Pérez de Prado ₃ , Parameshachari Bidare Divakarachari ₄ , R. Vijayarangan ₅ , K. L. Hemalatha ₆

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In recent trends, Cognitive Radio Sensor Networks (CRSNs) are investigated in-depth and getting momentum in all types of applications. CRSN can make use of the underutilized frequency spectrum in a suitable manner. Due to the above-mentioned advantage, the scholars have initiated to study of the domain of cognitive radio routing. Network congestion produces transmission delays and packet loss, as well as time and energy wasted on recovery. In order to fulfill the energy efficiency and network lifetime in CRSN, Congestion Centric Multi-Objective Reptile Search Algorithm (CC-MORSA)-based Clustering and Routing are used. The main objective of proposed CC-MORSA is to improve the lifetime by minimizing the distance among the designated Cluster Head nodes which creates the fitness function by multiple objectives like energy, distance, and load. This technique is appropriate for common sensor nodes in coordinated communications infrastructure and large networks. The simulation results are analyzed through MATALB in terms of remaining energy (999.5 J), average delay (0.36 s), Packet Delivery Ratio (99.8%), Energy Consumption (24.1 J), Throughput (0.98 Mbps), routing overhead (0.54), and Packet Loss Rate (0.2%). From the outcomes, it shows that the presented CC-MORSA outperformed conventional Stability-Aware Cluster-based Routing and Drop Factor-Based Energy Efficient Routing technique.

中文翻译：

认知无线电传感器网络中基于拥塞中心的多目标爬虫搜索算法的聚类和路由

在最近的趋势中，认知无线电传感器网络（CRSN）得到了深入研究，并在所有类型的应用中获得了发展势头。CRSN可以以适当的方式利用未充分利用的频谱。由于上述优点，学者们开始了认知无线电路由领域的研究。网络拥塞会产生传输延迟和数据包丢失，以及恢复时浪费的时间和精力。为了满足CRSN中的能源效率和网络寿命，使用基于拥塞中心多目标爬虫搜索算法（CC-MORSA）的聚类和路由。所提出的 CC-MORSA 的主要目标是通过最小化指定簇头节点之间的距离来提高寿命，从而通过能量、距离和负载等多个目标创建适应度函数。该技术适用于协调通信基础设施和大型网络中的常见传感器节点。通过 MATALB 对剩余能量（999.5 J）、平均延迟（0.36 s）、数据包送达率（99.8%）、能耗（24.1 J）、吞吐量（0.98 Mbps）、路由开销（0.54）等方面进行了仿真结果分析和丢包率 (0.2%)。结果表明，所提出的 CC-MORSA 优于传统的基于稳定性感知集群的路由和基于丢弃因子的节能路由技术。

更新日期：2022-08-22

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