WSN plays a major role in the design of IoT system. In today’s internet era IoT integrates the digital devices, sensing equipment and computing devices for data sensing, gathering and communicate the data to the Base station via the optimal path. WSN, owing to the characteristics such as energy constrained and untrustworthy environment makes them to face many challenges which may affect the performance and QoS of the network. Thus, in WSN based IoT both security and energy efficiency are considered as herculean design challenges and requires important concern for the enhancement of network life time. Hence, to address these problems in this paper a novel secure energy aware cluster based routing algorithm named Trusted Energy Efficient Fuzzy logic based clustering Algorithm (TEEFCA) has been proposed. This algorithm consists of two major objectives. Firstly, the trustworthy nodes are identified, which may act as candidate nodes for cluster based routing. Secondly, the fuzzy inference system is employed under the two circumstances namely selection of optimal Cluster Leader (CL) and cluster formation process by considering the following three parameters such as (i) node’s Residual Energy level (ii) Cluster Density (iii) Distance Node BS. From, the experiment outcomes implemented using MATLAB it have been proved that TEEFCA shows significant improvement in terms of power conservation, network stability and lifetime when compared to the existing cluster aware routing approaches.

中文翻译：

---

物联网WSN中使用模糊逻辑的可信能源感知集群路由

WSN在物联网系统的设计中起着重要作用。在当今的互联网时代，物联网将数字设备，传感设备和计算设备集成在一起，以进行数据传感，通过最佳路径收集数据并将其传达给基站。由于能量受限和不可信环境等特性，WSN使其面临许多挑战，可能会影响网络的性能和QoS。因此，在基于WSN的IoT中，安全性和能源效率都被认为是严峻的设计挑战，并且对于延长网络寿命至关重要。因此，为解决这些问题，本文提出了一种新颖的基于安全能量感知簇的路由算法，称为基于可信能效模糊逻辑的簇算法（TEEFCA）。该算法包括两个主要目标。首先，确定可信赖节点，该可信赖节点可用作基于集群的路由的候选节点。其次，在两种情况下采用模糊推理系统，即选择最佳的簇首（CL）和通过考虑以下三个参数，例如（i）节点的剩余能级（ii）簇密度（iii）距离节点BS。从使用MATLAB实现的实验结果可以证明，与现有的群集感知路由方法相比，TEEFCA在功率节省，网络稳定性和寿命方面显示出显着的提高。模糊推理系统是在两种情况下采用的，即选择最佳的簇首（CL）和通过考虑以下三个参数来形成簇的过程，例如（i）节点的剩余能量水平（ii）簇密度（iii）距离节点BS。从使用MATLAB实现的实验结果可以证明，与现有的群集感知路由方法相比，TEEFCA在功率节省，网络稳定性和寿命方面显示出显着的提高。模糊推理系统是在两种情况下采用的，即选择最佳的簇首（CL）和通过考虑以下三个参数来形成簇的过程，例如（i）节点的剩余能量水平（ii）簇密度（iii）距离节点BS。从使用MATLAB实现的实验结果可以证明，与现有的群集感知路由方法相比，TEEFCA在功率节省，网络稳定性和寿命方面显示出显着的提高。