Development of an Improved Multi-Hop Routing Protocol in Wireless Sensor Networks Based on Cluster Head Load Balancing Technique.
Abstract
conservation in sensor networks (wsns) is a key of research aimed at addressing the of efficient energy . This is due to the fact that the sensor nodes (sns) have limited energy. The limited energy has to be utilized efficiently in order to provide a longer network lifetime for the wireless sensor network (wsn).
To reduce energy consumption in wsns, an improved multi-hop routing protocol (meemrp) in wsns based on cluster head (ch) load balancing technique was developed in this research work.
The protocol used the residual energy (re) of cluster heads (chs) and adopted an election energy threshold (tnhch) to reduce the energy consumption of the sns in the network, thereby increasing the network lifetime.
This research work was carried out on Matlab r2015b and the performance of the improved protocol was compared in terms of network lifetime (node death percentage), energy consumption percentage, and a number of packets received at the base station (bs) in a homogeneous wsn.
Results obtained from simulation showed that meemrp achieved an average percentage improvement of the network lifetime, energy consumption percentage, and the number of packets received at the bs by 1.77%, 4.83%, and 7.41% respectively in a 200m by 200m network field.
Also, results obtained from simulations showed that meemrp in a 400m by 400m network field improved the network lifetime, energy consumption percentage, and the number of packets received at the bs by 10.65%, 9.2%, and 12.5% respectively. Two network field scenarios were used to test the scalability of the improved protocol.
The results of this research work showed that meemrp has a better network lifetime, better energy consumption and more number of packets received at the bs when compared with an existing energy-efficient multi-hop routing protocol (eemrp) in a wsn.
Introduction
Background of Study
A Wireless Sensor Network (WSN) is a network that is composed of hundreds of sensor devices that communicate over wireless channels (Vijayan & Raaza, 2016). This communication is governed by unique routing protocols (Vijayan & Raaza, 2016).
The sensors are equipped with data processing and communicating capabilities with a sensing circuitry that is able to sense environmental conditions such as temperature, pressure, humidity levels, etc, and convert them to electrical signals.
These conditions help to tell certain details about the surrounding environment. The sensors transmit their sensed data via an inbuilt transmitter as electromagnetic signals to a designated base station (BS) either directly (Akkaya & Younis, 2005) or through an intermediate node (Gupta et al., 2017).
Network lifetime is an important metric in wsns. It is the maximum period of time that sensor nodes (sns) are alive after they have been deployed in the field (Jan et al., 2013). Network lifetime can also be defined in terms of first node death time, half of nodes alive and last node death (Wang et al., 2012). It is necessary to have sns alive for as long as possible.
This is essential in order to avoid sensor holes in the network area. Wsns are often deployed in areas or regions that are not easily accessible (Jan et al., 2013). Batteries are therefore not easily replaced or recharged.
This necessitates the need for energy conservation in the nodes in order to maximize network lifetime and ensure that the network is not partitioned (Gupta et al., 2017) so as to avoid sensor voids or holes (More & Raisinghani, 2016). To reduce the energy dissipation in the sensor network, clustering of sns is One of the methods employed (Nayyar & Gupta, 2014).
Clustering in WSN is employed as a technique to provide balance among sns within the network so as to reduce the energy consumption of individual sns (Nayyar & Gupta, 2014).
References
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