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Heavy network traffic with a large number of sensor nodes causes high average energy consumption, a long average transmission delay, and a short network lifetime. To prevent this problem, we proposed and established an optimal path selection method for an Internet of Things (IoT) network based on an ant routing algorithm. The optimal path selection model considers the network lifetime and mobile distance, and analyzes node coverage conditions and communication energy consumption of all sensor nodes. The model is solved by an ant routing principle that finds the optimal path to a food source (a target node) with the maximum probability by considering the ant pheromone concentration (with a moving target node). We apply this principle to an IoT network. First, we divide a network monitoring area into several grids of the same size. Then, we repeat a process based on the principle until the network lifetime is greater than or equal to the time threshold to find the optimal path of a moving convergence node. Our simulation demonstrates that the optimal path model reduces the average energy consumption to reach the node, shortens the average transmission time to the node, and prolongs the network lifetime. The optimized routing model demonstrates a high data throughput and a stable operation.

Optimized Routing Model of Sensor Nodes in Internet of Things Network