Efficient load balancing and energy conservation protocol for WSN based on DBDQN and wild geeze migration optimization algorithm

Key Points

• Improved energy conservation is achieved through a novel protocol based on deep reinforcement learning and optimization algorithms.
• The study shows a notable increase in load balancing efficiency, enhancing overall sensor network performance by up to 20%.
• Assessment using the wild geese migration optimization algorithm demonstrates potential for scalable deployment in various environments.
• These findings highlight the need for further development in energy management approaches for wireless sensor networks.