Abstract—Dynamic Routing in Wireless Sensor Networks (WSNs) has played a significant task in research for the recent years. Energy consumption and data delivery in time are the major parameters with the usage of sensor nodes that are significant criteria for these networks. The location of sensor nodes must not be prearranged. Clustering in WSN is a key methodology which is used to enlarge the life-time of a sensor network. It consists of numerous real-time applications. The features of WSNs are minimized the consumption of energy. Soft computing techniques can be included to accomplish improved performance. This paper surveys the modern trends in routing enclose fuzzy logic and Neuro-fuzzy logic based on the clustering techniques and implements a comparative study of the numerous related methodologies. Keywords—Wireless sensor networks, clustering, fuzzy logic, neuro-fuzzy logic, energy efficiency. I. INTRODUCTION N WSNs, routing consists of both heterogeneous and homogeneous systems with a huge number of tiny devices called sensor node. Each device will have the responsibility of sensing, computation and secure communication [1], [85]. Devices are cooperating to each other and the sensor will autonomously sense the data. Two components are used in the wireless network aggregation; point and base station [3]. Further, nodes have rigorously limited computation, storage and power capabilities. However, they will tolerate numerous challenges [6]. The position of sensor nodes cannot be pre- determined because they are deployed randomly. The sensors are battery driven and deployed in unmanned environments, requiring energy conservation. The sensors are mostly mobile [2]. Static routing algorithms fail in WSNs. Random deployment may result in holes which are regions without enough working sensors. Clustering is one of the techniques to extend the network lifetime. In a clustering protocol, the geologically neighboring nodes are gathered into virtual groups called “clusters” [9], [65]. Each cluster has one Cluster Head (CH) and other nodes are called cluster nodes. Instead of direct communication with the destination, all the cluster nodes send data to the CH [88]. Clustering algorithms can be based on some criteria like Harold Robinson Y. is an Associate Professor with the Department of Computer Science and Engineering, SCAD College of Engineering and Technology, India (e-mail: yhrobinphd@gmail.com). Golden Julie is an Assistant Professor, Department of Computer Science and Engineering, Anna University, Chennai, India (e-mail: goldenjuliephd@gmail.com). battery nodes power, mobility, network size, speed, distance and direction [4], [5]. Low Energy Adaptive Clustering Hierarchy (LEACH) is one of the most well-known energy efficient clustering algorithms for WSNs [7], [66]. The operation of LEACH has two stages; setup phase and steady phase. To minimize the packet overhead, the steady-state segment considers data aggregation [12] for secure transmission. Besides LEACH, various clustering algorithms have been proposed for homogeneous WSNs [8], [86]. Fig. 1 illustrates the architecture for the WSNs. Fig. 1 Architecture of WSNs II. ROUTING PROTOCOLS Routing is the process of forwarding data from source to destination. Routing occurs in network layer. Routing involves two activities. One is identifying the path for forwarding the data; second is transferring the packet without error [10], [11], [87]. A lot of attributes to the sink will select the best path for transfer the packet using packet control messages [15], [76]. Subsequently, transferring packet from the source to the destination also hold various attributes for forwarding data successfully. Each packet should deliver the data without any error or security issues to the destination for finding optimal path [18], [77]. The delivered packet uses some standard metric to evaluate the correct and efficient path [89]. They are, Flat network routing, Hierarchical routing, and Location based routing as shown in Fig. 2. Y. Harold Robinson, E. Golden Julie A Comparative Study on Fuzzy and Neuro-Fuzzy Enabled Cluster Based Routing Protocols for Wireless Sensor Networks I World Academy of Science, Engineering and Technology International Journal of Computer and Information Engineering Vol:10, No:10, 2016 1913 International Scholarly and Scientific Research & Innovation 10(10) 2016 scholar.waset.org/1307-6892/10008316 International Science Index, Computer and Information Engineering Vol:10, No:10, 2016 waset.org/Publication/10008316