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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Hybrid Clustering and Routing Algorithm with Threshold-Based Data Collection for Heterogeneous Wireless Sensor

Muhammad Bilal1, Ehsan Ullah Munir1, Fawaz Khaled Alarfaj2

  • 1Department of Computer Science, COMSATS University Islamabad, Wah Campus, Wah Cantt 47010, Pakistan.

Sensors (Basel, Switzerland)
|July 28, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a novel hybrid clustering and routing algorithm for the Internet of Things (IoT) using wireless sensor networks (WSNs). The proposed energy-efficient model enhances network stability and load balancing for smart devices.

Keywords:
centralized networksdeletiondistributed networksnetwork heterogeneitythreshold

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • The Internet of Things (IoT) aims to connect diverse devices for automated data generation.
  • Wireless Sensor Networks (WSNs) are crucial for IoT, but energy efficiency is a key challenge for network lifetime.
  • Existing routing protocols often struggle with concurrent data collection and energy expenditure in heterogeneous networks.

Purpose of the Study:

  • To propose a hybrid clustering and routing algorithm for heterogeneous wireless sensor networks (WSNs) in IoT applications.
  • To enhance energy efficiency and prolong network lifetime by reducing unnecessary data transmission.
  • To improve network stability, load balancing, and end-to-end delay in dense and large-scale WSN deployments.

Main Methods:

  • Developed a hybrid clustering and routing algorithm integrating homogeneous and heterogeneous nodes.
  • Implemented a threshold-based data collection mechanism to minimize data transmission.
  • Extended the multi-hop model to ensure network stability in complex network environments.

Main Results:

  • The proposed model demonstrates improved load balancing compared to TSEP, TDEEC, LEACH, and TEEN.
  • Significant enhancements in end-to-end delay were observed.
  • Effective reduction in energy consumption through threshold-based data transmission was achieved.

Conclusions:

  • The hybrid clustering and routing algorithm offers a promising solution for energy-efficient data collection in heterogeneous WSNs.
  • The threshold-based approach effectively conserves energy by transmitting data only when significant changes occur.
  • The model provides superior performance in terms of network stability and efficiency for IoT applications.