International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-9 Issue-1, November 2019 3564 Retrieval Number: L37991081219/2019©BEIESP DOI: 10.35940/ijitee.A3799.119119 Published By: Blue Eyes Intelligence Engineering & Sciences Publication WSN Clustering Based on EECI (Energy Efficient Clustering using Interconnection) Method Gajendran Malshetty, Basavaraj Mathapati Abstract- in WSN, clustering gives an effective way to enhance the network lifetime. Moreover It has been observed that the clustering algorithm utilizes the two main technique first is selection of cluster head and cycling it periodically in order to distribute the energy among the clusters and this in terms increases the lifetime of network. Another challenge comes with this is minimize the energy consumption. In past several algorithm has been proposed to increase the lifetime of the network and energy consumption, however these methodologies lacks from efficiency. In this paper, we have proposed a methodologies named as EE-CI (Energy Efficient Clustering using Interconnection), along with the random updation. Here the networks are parted into different clusters, the cluster updation are done based on the CHC scheme. Moreover, in proposed methodology cluster updation and data sample is determined through the change in sensor data. Here we propose a method for sampling sensor and CHC for selecting the cluster head to balance the energy and improvise the energy efficiency. Moreover, the proposed methodology is evaluated and the result is demonstrated by considering the Leach as existing methodology, experiments results shows that the proposed methodology outperforms the existing methodology. Keywords: WSN, Clustering, EECI. I. INTRODUCTION Wireless sensor Networks are the networks that are made up of several distributed micro devices that are embedded with the several sensing abilities, the device with sensing abilities are known as sensors [1]. These sensors are used for sensing the data node and sending back to the application or the end users. The technologies related to the WSN were introduced almost two decades ago and since then there has been many research from the academia point of view as well as the industrial point of view. WSN constitutes three main component, the architectural view of the WSN starts with the sensor node. These sensor nodes have the several attributes such as they have the limited power supply which is fulfilled by the battery and these sensor nodes can be deployed randomly , their main task is to collected the data and send the data to the further i.e. base station . When any data are sensed through the sensor node of the event detection takes place, the data are received by the Base Station, which is the second component of the WSN. Base station receives the data and by using the multi-hop architecture [2]. Moreover, the third component is the end user or the application. The below diagram shows the typical WSN architecture. Revised Manuscript Received on November 05, 2019. Gajendran Malshetty, Assistant Professor, Computer Science & Engineering, Appa Institute of Engineering & Technology, Kalaburgi. Dr. Basavaraj Mathapati, Professor, Computer Science & Engineering, Appa Institute of Engineering & Technology, Kalaburgi, India. Sensor Nodes WSN Gateway Internet Application Figure 1 Typical WSN architecture Moreover the Wireless sensor networks are equipped with the limited power supply i.e. battery, and hence any other power resources are not required from the outside [3]. This scenario has made essential for the WSNs to function in the efficient manner in order to improvei8se the lifetime of the network. WSNs are capable of solving the many real time issue and implemented in various areas such as defense where the WSN are placed in the battlefield for monitoring the soldier movement, vehicles and transmits the data related to the battle [4, 5]. In Environmental application, it is used for monitoring the oceans, volcanoes, forest and glaciers and others [6, 7]. It is also applicable for monitoring he Structural monitoring such as tunnels, flyovers, bank and bridges [8], other application such as in agriculture field for monitoring the crops and the automatic watering system, which helps in the reduction of wastage[9]-[14]. Similarly, on health environment it is applied for scaling the Blood pressure breath rate and hear rate [15-17]. Therefore, it can be said that WSN is a vast emerging technology that has gained the enormous popularity. In case of the clustering environment the fields are parted into the various groups, these are known as clusters, every cluster has a particular leader named as CH (Cluster Head) [18]. The CH performs the data processing after receiving the data from the cluster member, this is done for discarding the redundant data and only the absolute data is transmitted. All this is done to save the energy as energy consumption is consider as one of the prime factor in case of WSN .For energy consumption several methods have been proposed in the past, which has helped in the achieving the better lifetime of the network, and the energy consumption. Clustering is introduced for the energy consumption, clustering is applicable. In this research work, we have proposed a methodology to improvise the clustering performance. Here our intention is to form the balanced as well as the stable clusters.