The use of mobile devices has been growing rapidly and at the same time mobile applications has attained increasing popularity. Moreover, mobile services have introduced unexpected demands on the infrastructure of mobile and wireless networking. Recently, Mobile Sensor Networks (MSNs) has developed a class of popular sensor network where mobility has the major responsibility in executing the application. Since the deployment of a sensor network is not completely static, the mobility factor has plenty of challenges which have to be solved including coverage, connectivity, and energy consumption. The aim of this article is to design a robust procedure to handle the challenges of mobile sensors network by providing a secure and energy-efficient communication. In this article swarms of sensors are able to move while maintaining the optimal distance among sensor nodes.The security and energy of the signal transmission has been enhanced using multi-path link routing protocol (MLRP) and a hybrid-based TEEN (H-TEEN) protocol. Transmitted signalshave been classified via a recurrent neural networks (RNN). The simulation results show that this proposed model is able to effectively detect malicious nodes and balance the energy so that the lifespan of MSN can be prolonged.

移动设备的使用一直在迅速增长，同时移动应用程序也越来越受欢迎。此外，移动服务对移动和无线网络的基础设施提出了意想不到的需求。最近，移动传感器网络 (MSN) 开发了一类流行的传感器网络，其中移动性主要负责执行应用程序。由于传感器网络的部署不是完全静态的，因此移动性因素有很多必须解决的挑战，包括覆盖范围、连接性和能耗。本文的目的是设计一个强大的程序，通过提供安全和节能的通信来应对移动传感器网络的挑战。在本文中，成群的传感器能​​够在保持传感器节点之间最佳距离的同时移动。使用多路径链路路由协议 (MLRP) 和基于混合的 TEEN (H-TEEN) 增强了信号传输的安全性和能量) 协议。传输的信号已通过循环神经网络 (RNN) 进行分类。仿真结果表明，该模型能够有效地检测恶意节点并平衡能量，从而延长MSN的生命周期。