Abstract

Recently, Pulse Coupled Oscillator (PCO)-based travelling waves have attracted substantial attention by researchers in wireless sensor network (WSN) synchronization. Because WSNs are generally artificial occurrences that mimic natural phenomena, the PCO utilizes firefly synchronization of attracting mating partners for modelling the WSN. However, given that sensor nodes are unable to receive messages while transmitting data packets (due to deafness), the PCO model may not be efficient for sensor network modelling. To overcome this limitation, this paper proposed a new scheme called the Travelling Wave Pulse Coupled Oscillator (TWPCO). For this, the study used a self-organizing scheme for energy-efficient WSNs that adopted travelling wave biologically inspired network systems based on phase locking of the PCO model to counteract deafness. From the simulation, it was found that the proposed TWPCO scheme attained a steady state after a number of cycles. It also showed superior performance compared to other mechanisms, with a reduction in the total energy consumption of 25%. The results showed that the performance improved by 13% in terms of data gathering. Based on the results, the proposed scheme avoids the deafness that occurs in the transmit state in WSNs and increases the data collection throughout the transmission states in WSNs.

Highlights

  • The rising research trend in the area of micro-electrical mechanical systems (MEMS) over the years has provoked scholarly attention focused on wireless sensor network (WSN)

  • Similar to the other schemes for achieving energy efficiency, the performance of our Travelling Wave Pulse Coupled Oscillator (TWPCO) scheme was measured in relation to two significant effects: the effect of the number of sensor nodes and the effect of the packet size

  • The results showed that the WSN started with the sink and five sensor nodes, from 1 to 5, at cycle = 0 in the simulation

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Summary

Introduction

The rising research trend in the area of micro-electrical mechanical systems (MEMS) over the years has provoked scholarly attention focused on WSNs. WSNs can be described as small and inexpensive devices with sensing, processing and transmitting capabilities concerning environmental phenomena of interest. WSNs can be described as small and inexpensive devices with sensing, processing and transmitting capabilities concerning environmental phenomena of interest They have various application prospects, including use in military, industrial and agricultural monitoring systems [1]. In a network of sensor nodes, the wireless sensors collaboratively sense the environment, detect the phenomenon of interest, and eventually forward the data to a dedicated base station in synchronization. Among the models that have been extensively investigated in recent years for such collaborative.

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