ANVESAK ISSN : 0378 – 4568 UGC CARE Group 1 Journal Vol. 54, No.2(II) July – December : 2024 143 AN EFFICIENT CH SELECTION & DATA AGGREGATION TO MAXIMIZE THROUGHPUT IN WIRELESS SENSOR NETWORKS Kaitha Dileep Reddy, Research Scholar, Department of Computer Science and Engineering, University College of Engineering, Osmania University, Hyderabad, Telangana, India. dileepkaitha0702@gmail.com Dr.V B Narasimha, Assistant Professor, Department of Computer Science and Engineering, University College of Engineering, Osmania University, Hyderabad, Telangana, India. Abstract In recent years, there has been an increasing focus on developing energy-efficient routing algorithms for wireless sensor networks. Due to the limited power resources in sensor nodes, conserving energy is crucial for both individual node longevity and the overall network lifespan. Energy efficiency is a significant concern in wireless sensor networks, particularly due to the high energy consumption associated with transmission tasks, especially over long distances. It has been demonstrated that clustered routing strategies are effective in maximizing network lifespan while minimizing transmission energy. Clustering serves as an efficient data collection technique that aims to reduce energy consumption. In a clustered network, each node sends its gathered data to a specific cluster head. The cluster head then consolidates the data from all member nodes and transmits it to the base station (sink), either in a compressed or uncompressed form. This data transfer occurs in a multi-hop network setting, passing through multiple cluster heads. However, cluster heads near the sink often experience early energy depletion due to the intensive inter-cluster relay. Congestion in network nodes exacerbates issues such as increased packet loss and energy consumption. Routing algorithms must prioritize load balancing among diverse sensor nodes and energy efficiency to enhance network longevity. In response to these challenges, this study introduces a distributed fuzzy-based relay selection mechanism and a K-means clustering algorithm with optimal Cluster Head (CH) selection. The CH selection algorithm employs channel quality and distance to CH characteristics to identify CHs. A distributed fuzzy system, considering link superiority factors, route weight, and node adjacency, is utilized to select relay nodes. The proposed technique undergoes evaluation and comparison with current methods, focusing on metrics such as lifespan, energy consumption, throughput, packet delivery ratio, and end-to-end latency. Simulation results indicate that the proposed strategy outperforms comparable strategies across various parameters. Keywords: WSN, Cluster head selection, optimal relay node selection, Fuzzy system, Network lifetime. I. Introduction Sensor nodes are placed strategically across space to provide interconnections in a Wireless Sensor Network (WSN) without the need for physical wiring [1]. These sensor nodes function as part of the wireless sensor network (WSN) and sense the surrounding environment. They then use their communication components to wirelessly transfer the data they have seen to other nodes and the Base Station (BS), which is a designated sink point [2]. Once the incoming data has been aggregated, the BS may be used as a supervisory control processor, an access point for a human interface, or a gateway to other networks. The WSN may gather data concurrently from many sites of interest dispersed across large territories thanks to the cooperative efforts of several sensor nodes [3]. However, despite all of its benefits, WSNs' applicability is severely limited by the energy constraints placed on the sensors. Sensor node energy consumption is mostly related to data processing, environmental sensing, and wireless communication [4]. As a result, power saving is the primary goal of most routing protocols created for WSNs. Because wired network routing techniques are primarily focused on providing high-quality service (QoS), they are not appropriate for wireless sensor networks (WSNs) in practice [5]. As a result, several protocols have been developed to overcome the problems associated with data routing in sensor networks.