UBER: UAV-Based Energy-Efficient Reconfigurable Routing Scheme for Smart Wireless Livestock Sensor Network.

Area of Science:

• Wireless Sensor Networks
• Internet of Things (IoT)
• Agricultural Technology

Background:

• Wireless livestock sensor networks face challenges with coverage loss and rapid energy depletion, hindering efficient monitoring.
• Existing routing schemes often struggle to maintain network stability and energy efficiency in dynamic environments.

Purpose of the Study:

• To propose and evaluate a UAV-based energy-efficient reconfigurable routing (UBER) scheme for smart wireless livestock sensor networks.
• To address critical issues of network coverage loss and rapid energy depletion.

Main Methods:

• The UBER scheme utilizes dynamic residual energy thresholding, robust cluster-to-UAV link formation, and UAV-assisted network recovery.
• Performance was assessed across various UAV altitudes and compared against hybrid heterogeneous routing (HYBRID) and mobile sink using directional virtual coordinate routing (MS-DVCR).

Main Results:

• Operating at a 230m UAV altitude showed significant improvements in network stability (31.58%), load balancing (61.67%), and topology fluctuation (75.57%).
• UBER demonstrated superior performance over HYBRID and MS-DVCR, achieving gains of 46.48% in energy consumption, 47.33% in network coverage, and reducing end-to-end delay by 58.56%.

Conclusions:

• The UBER scheme offers a highly efficient solution for wireless livestock sensor networks, effectively mitigating coverage loss and energy depletion.
• UBER provides competitive performance, outperforming existing routing schemes in key metrics crucial for smart agricultural applications.