EEECARP: Efficient Energy Clustering Adaptive Routing Procedure for Wireless Sensor Networks

EEECARP: Efficient Energy Clustering Adaptive Routing Procedure for Wireless Sensor Networks

Venkata Ramana Sarella (Research Scholar, Department of CS & SE, Andhra University, Visakhapatnam, India), P.V.G.D. Prasad Reddy (Department of CS&SE, College of Engineering, Andhra University, Visakhapatnam, India), S. Krishna Rao (CRR Engineering College, Department of IT, Eluru, India) and Preethi Padala (Department of IT, NIT K, Mangalore, India)
Copyright: © 2017 |Pages: 14
DOI: 10.4018/JGIM.2017100108
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Abstract

WSN is a promising approach for variety of different real time applications. Different Routing protocols for WSNs are very effective challenge in present days because of scalability, efficient energy utilization and robustness in large number of wireless sensor networks with consists of more number of sensor nodes. LEATCH is a traditional routing protocol for energy optimization in WSNs. However, LEATCH cannot scale performance for large scale wireless sensor networks and difficulty to apply effective utilization of real time wireless sensor networks. So, in this paper the authors propose to develop a novel Energy Efficiency and Event Clustering Adaptive Routing Protocol (EEECARP) for WSN. The main designing feature of their proposed approach is as follows: Energy Efficiency, Dynamic Event Clustering and multi hop relay configuration with residual energy available on relay nodes in wireless sensor networks. The simulation results show that authors' routing protocol achieves convenient and effective better performance in formation of clusters with relay sensor nodes in wireless sensor networks.
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1. Introduction

Wireless Sensor Network (WSN) is a wide range of large sensor nodes. WSN is defined as a network of devices that can communicate to monitor the information from different wireless links. Based on their behavior specification different types of wireless sensor networks include as Terrestrial WSNs, Underground WSNs, Underwater WSNs, Multimedia WSNs and Mobile WSNs. Here we consider both terrestrial and underground WSNs for energy optimization in communication and other proceeding works. WSNs involve a number of small battery-powered gadgets frequently to obtain various sorts of useful information from wireless communication (Visvanathan A, 2005). These gadgets sense physical qualities, such as sound, moisture, pressure, luminosity, temperature, or chemical focus, and transfer the collected information to a Base Station (BS) for further research or research implementation for communication. Energy outlay is a well-known of the biggest constraints of the transmission sensor node and this limitation combined by typical deployment of wealthy number of nodes have added copious challenges to the diamond in the rough and powers that be of receiver sensor networks. They are truly used for solitary environment monitoring in areas to what place providing electrical capacity is difficult. Therefore, the devices crave to be powered by batteries and extra energy sources. Because ordnance energy is restrictive, they consider of clustering techniques for energy close is such of the hottest topics in WSNs. WSNs have been effectively implemented in strategic fight situations, environment tracking, security systems, and so on. Since WSNs involve many receptors with limited power, an energy-efficient network method is an essential consideration in WSN programs. Energy is significance in WSNs. Procedure for relay configuration of sensor nodes with communication as shown in Figure 1.

Figure 1.

Hierarchal architecture implementation of WSNs with relay sensor nodes

Relay configuration of each sensor node may appear in Figure 1 with Cluster Head (CH), Base Station (BS) and Source and Destination to communication multi-level data transmission in wireless sensor networks. Process of information deviated from one to several flow transmissions from sensors location to main host (Sensor Sink). In this manner, most guiding computations suggested for exclusively hired systems are not specifically material to WSNs without comprehensive modifications (Visvanathan A. 2005). This encourages the concept purpose of achieving biggest throughput with smaller sized than normal mal energy usage in settings and perform of guiding conferences for WSNs (QUANG, V. T, 2008),(Quang V, 2008) Typically Low Energy Flexible Group Go (LEACH) is one of the most well-known requested course-plotting techniques for wireless sensor implementation techniques. Many techniques were introduced for energy optimization in wireless sensor networks. But LEATCH is an essential approach in cluster head based energy optimization when compare to existing approaches in wireless sensor networks. The concept is to kind categories of the sign nodes centered on the acquired sign strength and use regional CHs (cluster heads) as wireless routers to the strain (base station). This will preserve power since the alerts will only be done by such team brings rather than all sign nodes. LEACH distinguishes the whole program into several categories, and the run time of program is utilized many models. In each circular, the nodes in a team cope to be team go according to a pre-specified specifications. LEACH is a more mature clustering course-plotting specifications, but it still has issue of brief achievements initiatives and is low-level of load-balancing. The group go is chosen arbitrarily in LEACH, and this is likely to bring some of the ineffective sub clustering plans. In this research, we provide the best remedy in the power intake of the unique method and thus the system will have a longer life-time. To model energy usage, three essential conditions of a hub can be distinguished: discovering, data planning and data communication. Among them, data communications spend crucial way of measuring energy while transferring or getting packages. Reducing the amount of correspondences by cleaning out or gathering excess recognized details will extra a lot of energy, which gradually encourages the network longevity.

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