In general, WMSN follows many-to-one technique to transmit the data and to sense the information. There occurs a rapid increase in congestion or network traffic due to the generation of a large number of sensors. Moreover, the performances are jeopardized due to transmission and a high rate of packet losses. In order to address such shortcomings, this paper aims in developing a Hybrid Red Deer Salp Swarm (HRDSS) based routing approach. The HRDSS approach is the integration of a red deer and the salp swarm optimization algorithm. The work outlined in this paper is to minimize four different objectives namely packet loss, memory, delay and expected transmission cost. The main intention of the multi-objective function involves generating a diverse optimal solution set that is utilized to evaluate the trade-off among various objectives. We also presented the simulation results for two different scenarios comprising of the network grid and the optimization test functions that are carried out to determine the effectiveness of the system. In addition to this, the comparative analysis is done and the results reveal that the proposed HDRSS approach provides the best optimal routing path when compared with various approaches.

通常，WMSN遵循多对一技术来传输数据和感知信息。由于大量传感器的产生，拥塞或网络流量迅速增加。而且，由于传输和高分组丢失率，性能受到损害。为了解决这些缺点，本文旨在开发一种基于混合马鹿群（HRDSS）的路由方法。HRDSS方法是将马鹿与小群优化算法集成在一起。本文概述的工作是最小化四个不同的目标，即数据包丢失，内存，延迟和预期的传输成本。多目标函数的主要目的涉及生成多样化的最佳解决方案集，该解决方案集可用于评估各种目标之间的权衡。我们还介绍了两种不同情况的仿真结果，包括网络网格和确定系统有效性的优化测试功能。除此之外，进行了比较分析，结果表明，与各种方法相比，所提出的HDRSS方法提供了最佳的最佳路由路径。