MAP-ACO: An efficient protocol for multi-agent pathfinding in real-time WSN and decentralized IoT systems

Abstract

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.