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Energy and Environment-Aware Path Planning in Wireless Sensor Networks with Mobile Sink
Fatma H El-Fouly1, Ahmed B Altamimi2, Rabie A Ramadan2,3
1Department of Communication and Computer Engineering, Higher Institute of Engineering, El-Shorouk Academy, El-Shorouk City 11837, Egypt.
Sensors (Basel, Switzerland)
|December 23, 2022
Summary
This study presents a novel framework for mobile sensor networks, optimizing energy consumption and data transfer for critical applications like IoT and healthcare. The proposed algorithms enhance efficiency and reliability in challenging environments.
Area of Science:
- Computer Science
- Electrical Engineering
- Network Engineering
Background:
- Sensor networks are integral to the Internet of Things (IoT) and drone systems, facing energy consumption challenges.
- Mobile sensors in networks collect data, posing issues for energy, urgent message transfer, and path planning.
- Environmental exposure and unattended operation of sensors are critical, yet under-researched challenges.
Purpose of the Study:
- To develop a comprehensive framework addressing energy efficiency, reliability, and path planning in mobile sensor networks.
- To introduce novel algorithms for path planning, clustering, and routing that consider environmental factors and urgent data.
- To provide optimal solutions using Integer Linear Programming (ILP) for the sensor networks research community.
Main Methods:
- Novel path planning techniques incorporating area priority, environmental parameters, and urgent message urgency.
- An energy-efficient and reliable clustering algorithm considering residual energy, link quality, and intra-cluster distance.
- A real-time, energy-efficient, reliable, and environment-aware routing protocol accounting for multiple network parameters.
Main Results:
- The proposed framework significantly outperforms six recent algorithms in simulations.
- Demonstrated improvements in energy efficiency, reliability, and handling of urgent messages.
- Validated the effectiveness of ILP formulations for achieving optimal solutions.
Conclusions:
- The developed framework offers a robust solution for energy consumption and reliability challenges in mobile sensor networks.
- The novel algorithms provide significant advancements for IoT, drone networks, and other critical sensing applications.
- The ILP-based approach ensures optimal performance and serves as a valuable resource for future research.
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