To improve the energy efficiency and prolong the life cycle of Wireless Sensor Network (WSN), a WSN hierarchical routing algorithm based on Fuzzy C-Means (FCM) clustering and Swarm Intelligence (FCM-SI) was proposed. Firstly, FCM clustering algorithm was adopted to cluster the network, which optimized the distance between common nodes and Cluster Heads (CH). Then, Artificial Bee Colony (ABC) algorithm with three parameters was used to select the optimal CH. At last, Ant Colony Optimization (ACO) algorithm was adopted to search the multi-hop path between CH and Base Station (BS), which took energy consumption and load balancing into consideration. The simulation results show that compared with the algorithms of Improved Low Energy Adaptive Cluster Hierarchy (I-LEACH) based on uniform clustering, Low Energy Adaptive Cluster Hierarchy (LEACH) based on ABC (ABC-LEACH) and LEACH based on ACO (ANT-LEACH), the network life cycle of FCM-SI is prolonged by 65.2%, 49.6%, and 29.0% under initial network conditions with 100 nodes deployed in 100 m*100 m area. FCM-SI can effectively prolong network life and improve energy efficiency.

To deal with the problems of unbalanced energy consumption of nodes, short network lifetime and tardy update of parent nodes' status information during steady state in the IPv6 Routing Protocol for Low-power and lossy network (RPL), an Energy Balancing RPL (EB-RPL) with battery estimation strategy was proposed. Firstly, a new routing metric combing expected transmission count and node residual energy was presented, with which nodes can adaptively adjust the network topology at different stages. Secondly, a battery estimation method based on energy consumption rate of the parent node was designed, thus the child nodes can calculate the power consumption of the parent node and make the correct routing decision without increasing the additional overhead of control messages. Finally, the performance of EB-RPL was compared and analyzed through experiments. The simulation results show that compared with RPL, EB-RPL can significantly reduce the standard deviation of power between nodes at the same level, and the average network lifetime is respectively prolonged by 29.4% and 39.4% on average with different interpacket intervals and network sizes. EB-RPL can effectively achieve energy balance and significantly extend network lifetime.