Clustering of sensor nodes is one of the prominent methods applied to Wireless Sensor Networks (WSN). In the cluster-based WSN scenario, the sensor nodes are assembled to generate clusters. The sensor nodes are composed of limited battery power. Therefore, energy efficiency in WSN is crucial. A load of sensor node and its distance from base station (BS) are the significant factors of energy consumption. Therefore, load balancing according to the transmission distance is necessary for WSN. In this paper, we propose a load-balanced clustering algorithm using Fuzzy C means (FCM) algorithm and an energy-efficient routing approach using BAT-algorithm (FC-RBAT). The cluster heads (CHs) are selected according to the score of the sensor node from each cluster. After selection of the CHs, the BAT-inspired routing algorithm is applied on the CHs. The best routing path from each CH to the BS is obtained from the proposed approach. The simulations are conducted on evaluation factors such as energy consumption, active sensor nodes per round, the sustainability of the network and the standard deviation of a load of the sensor node. It is observed that FC-RBAT outperforms compared algorithms, namely EAUCF, DUCF and SGA, under the evaluation factors.

传感器节点的群集是应用于无线传感器网络（WSN）的重要方法之一。在基于群集的WSN场景中，传感器节点被组装以生成群集。传感器节点由有限的电池电量组成。因此，WSN中的能源效率至关重要。传感器节点的负载及其与基站（BS）的距离是能耗的重要因素。因此，WSN需要根据传输距离进行负载平衡。在本文中，我们提出了一种使用模糊C均值（FCM）算法的负载均衡群集算法和一种采用BAT算法（FC-RBAT）的节能路由方法。根据每个群集中传感器节点的得分选择群集头（CH）。选择了CH后，将BAT启发式路由算法应用于CH。从每个CH到BS的最佳路由路径是从所提出的方法中获得的。在评估因素上进行仿真，例如能耗，每轮活动的传感器节点，网络的可持续性以及传感器节点负载的标准偏差。可以看出，在评估因素下，FC-RBAT的性能优于比较算法，即EAUCF，DUCF和SGA。