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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

Summary

This summary is machine-generated.

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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.

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:

Keywords:

centralized networks deletion distributed networks network heterogeneity threshold

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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.