Modified radio model for clustering wireless sensor network

Abstract

Wireless Sensor Network (WSN) is a new and fast advancing technology, which is opening up many opportunities in the field of remote sensing and data monitoring. In spite of the numerous applications of WSN, issues related to determining a suitable and accurate radio model that will foster energy conservation in the network limit the performance of WSN routing protocols. A number of radio models have been proposed to improve the performance of WSN routing protocols. However, the underlying assumptions and inaccurate configuration of these radio models make them inefficient and often lead to mismanagement of scarce energy and computational resources. This research addresses these challenges by proposing a modified radio model that adapts to the frequent changes in the location of the object that the sensor nodes is tracking and is robust enough to report reliable data to the base station despite fluctuations due to signal interference. The impact of incorporating stepwise energy level and specialized data transmission schemes in the proposed radio model was also investigated in this research. Key design features were identified and selected, thereafter model of proposed radio model for cluster-based routing was analyzed. Thus, proposed radio model for cluster-based routing was developed. The performance of the proposed radio model was evaluated using OMNET++ and MATLAB and the results obtained were benchmarked against Low-Energy Adaptive Clustering Hierarchy (LEACH) and Power-Efficient Gathering in Sensor Information Systems (PEGASIS). The simulation shows that the performances of the proposed Low-Energy Adaptive Clustering Hierarchy-Improved (LEACH-IMP) developed in this research are more efficient when compared to existing clustering routing protocols with respect to energy consumption, number of links faults, number of packets received, signal interference, and network lifetime. LEACH-IMP shows an improvement of 30.72% and 38.10% over LEACH in terms of energy consumption and number of link faults respectively. Moreover, LEACH-IMP shows an improvement of 29.21%, 9.28% and 53.16% over LEACH in terms of number of received packets, signal interference and network lifetime respectively. Similarly, when benchmarked against PEGASIS, LEACH-IMP shows an improvement of 17.93% and 20.24% in terms of energy consumption and number of link faults respectively. Furthermore, LEACH-IMP shows an improvement of 12.02%, 2.22% and 14.38% over PEGASIS in terms of number of received packets, signal interference and network lifetime respectively. Therefore, the LEACH-IMP developed in this research is assessed to be robust enough to report reliable data to the central monitoring system for the end user despite the fluctuations in signal strength.