This paper presents the versatile approach, called Neural-Fuzzy based Effective Clustering (NFEC), for Large-Scale wireless sensor network (WSN) with Mobile Sink. The proposed protocol NFEC presents the effectiveness of existing approaches with proposed NFEC in terms of stability period and network lifetime for homogeneous and heterogeneous network environment. The NFEC protocol utilizes the concept of Neural-Fuzzy based model to enhance the network performance while considering the effect of random waypoint mobility in Sink/Base Station. The nature of the proposed NFEC is adaptive and can be varied accordingly for homogeneous and heterogeneous scalable WSN. The simulations analyse the performance of NFEC protocol with existing protocols.

本文介绍了一种通用方法，称为基于神经模糊的有效聚类 (NFEC)，用于具有移动接收器的大规模无线传感器网络 (WSN)。提议的协议 NFEC 在同构和异构网络环境的稳定期和网络寿命方面展示了现有方法与提议的 NFEC 的有效性。NFEC 协议利用基于 Neural-Fuzzy 的模型的概念来增强网络性能，同时考虑 Sink/Base Station 中随机路点移动性的影响。所提出的 NFEC 的性质是自适应的，并且可以为同构和异构可扩展 WSN 相应地改变。仿真分析了 NFEC 协议与现有协议的性能。