6 Conclusions
This paper proposed the IACO routing algorithm, which is an extended ACO. The algorithm establishes and updates the pheromone concentration of the gradient field and path by broadcasting messages and exchanging hops between neighbor nodes in the whole network. Next, data transmission, delay packet loss rate, and node residual energy are determined by calculating the corresponding probability of the neighbor nodes. Routing is selected by considering both the shortest path and highest residual energy. In the routing maintenance process, data are transferred to increase the pheromone concentration. Therefore, the energy consumption of the whole network is closer to the average while data packets are sent along the shortest paths. Consequently, the lifetime of network is effectively prolonged. Moreover, the control of special regions cannot be lost because of the rapid death of nodes along the shortest path.
According to the requirements of applications using the IACO, the QoS is divided into three levels according to the data transmission delay, data transmission reliability, and the network energy consumption. Then, IACO is used to design the wireless sensor routing algorithm, and the optimal path are selected according to the QoS level. A simulation experiment was used to test the performance of the algorithm. The simulation results show that the IACO algorithm not only reduces the data transmission delay and improves the data forwarding efficiency, but also reduces the data packet loss rate, reduces the energy consumption of the network, and prolongs the overall network performance and resource utilization.
