Abstract
In the large scale monitoring application of the IoT, the power carried by a single sensor node is limited, and it may not be replenished in the later stage. Therefore, it is required that the sensor nodes should save power when working, and the power consumption among the sensor nodes should be balanced to avoid the early death of some nodes and the occurrence of monitoring blind spots in the monitor area. Communication is the main part of power loss for sensor nodes. For this reason, this paper introduces a new low power energy balanced clustering routing scheme. Firstly, the sparrow search algorithm is improved by adding adaptive sine function and Cauchy random number to raise the search capability of the discoverer; The standard normal distribution random number is used to enhance the vigilant escape from the limit of local optimal value. Then the enhanced SSA algorithm can be used for cluster head selection. A fitness function with five key parameters is constructed by using the residual energy, the member number within a cluster, the intra-cluster distance in a cluster, the distance among clusters, and the distance from cluster head to base station, which effectively realizes the energy consumption balance among sensors in each round. At the same time, in the data forwarding stage, the multi-hop forwarding rules are designed to further reduce energy loss, greatly delay the arrival of the first dead node, and keep the sensor node working in the low power mode for a long time. Experimental results show that this scheme not only significantly prolongs the sensor lifetime, but also balances the power consumption among sensor nodes. This scheme provides a new idea for IoT sensor nodes to work in low power and ultra long standby mode, especially suitable for large scale and long term deployment scenarios such as ecological monitoring and industrial equipment state perception.