Wireless Sensor Networks (WSNs) have an important role in establishing the communication between the Internet of things (IoT) devices. Routing is an important research field in the WSN as it helps in finding the suitable paths for the communication. This paper proposes a multipath routing algorithm based on the optimization approach. The proposed routing algorithm has two important phases, namely, Cluster head selection and multipath routing. Initially, the cluster head selection is carried out by the kernel based Fuzzy C Means (kernel FCM) algorithm. Then, the multipath routing is established by the newly developed Rider Salp Swarm Optimization algorithm (RSSA), which is the integration of the Rider Optimization Algorithm (ROA) and Salp Swarm Algorithm (SSA). The fitness function of the proposed RSSA is designed by considering the several factors, such as energy, QoS and trust. The simulation of the proposed work is carried out using different WSN setups, and the results are compared with several comparative techniques. From the results, it can be summarized that the proposed RSSA based multipath routing has better performance with values of 0.2526, 0.0764, 0.5, and 26 for delay, energy, throughput and number of alive nodes, respectively.

中文翻译：

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WSN中多跳路由的改进骑手优化算法

无线传感器网络（WSN）在建立物联网（IoT）设备之间的通信中具有重要作用。路由是WSN中的重要研究领域，因为它有助于找到合适的通信路径。本文提出了一种基于优化方法的多路径路由算法。所提出的路由算法具有两个重要阶段，即簇头选择和多路径路由。最初，簇头选择是通过基于内核的模糊C均值（内核FCM）算法执行的。然后，通过新开发的Rider Salp Swarm优化算法（RSSA）建立多路径路由，该算法是Rider优化算法（ROA）和Salp Swarm算法（SSA）的集成。建议的RSSA的适应度函数是通过考虑以下几个因素而设计的，例如能源，QoS和信任度。使用不同的WSN设置对拟议工作进行了仿真，并将结果与​​几种比较技术进行了比较。从结果可以总结出，所提出的基于RSSA的多路径路由具有更好的性能，其延迟，能量，吞吐量和活动节点数分别为0.2526、0.0764、0.5和26。