Efficient energy consumption is one of the main problems in wireless sensor networks routing protocols. Since the sensor nodes have limited battery level and memory space, it is important to manage these resources efficiently. Although there are studies in this subject in recent years, it is lacking in concurrent and real-time environments with multi-agents. The importance of this issue is increasing more especially for decentralized IoT systems. This paper presents a novel routing protocol based on ant colony optimization for multi-agents that manages network resources adequately in real-time conditions. The proposed method is used, both to find the next destination of ants, and to manage pheromone update and evaporation rate operators. This method takes into account some key parameters such as remaining energy, buffer size, traffic rate, and distance when selecting the next destination under different conditions. The proposed method finds the optimal paths with low energy consumption thereby prolonging the network lifetime in concurrent and parallel conditions. The simulation results of the proposed method have given good results, in terms of network lifetime and energy consumption, when compared with other ant colony optimization (ACO)-based routing protocols.

高效的能耗是无线传感器网络路由协议中的主要问题之一。由于传感器节点的电池电量和存储空间有限，因此有效管理这些资源非常重要。尽管近年来对此主题进行了研究，但是在多代理的并发和实时环境中仍然缺乏。这个问题的重要性尤其是对于分散式物联网系统而言越来越重要。本文提出了一种基于蚁群优化的多智能体路由协议，该协议能够在实时条件下充分管理网络资源。使用所提出的方法，既可以找到蚂蚁的下一个目的地，又可以管理信息素更新和蒸发速率算子。此方法考虑了一些关键参数，例如剩余能量，缓冲区大小，流量速率，在不同条件下选择下一个目的地时的距离和距离。所提出的方法找到了低能耗的最佳路径，从而延长了并行和并行条件下的网络寿命。与其他基于蚁群优化（ACO）的路由协议相比，该方法的仿真结果在网络寿命和能耗方面都给出了良好的结果。