ACTOR: Adaptive Control of Transmission Power in RPL

Area of Science:

• Internet of Things (IoT) networking
• Wireless communication protocols
• Network performance optimization

Background:

• RPL (Routing Protocol for Low-Power and Lossy Networks) is the standard for IoT but underutilizes device transmission power.
• Optimizing transmission power in RPL is complex due to dynamic wireless links and constrained IoT resources.
• Dynamic assessment of parameters like packet collisions, energy, hops, and interference is crucial for power adaptation.

Purpose of the Study:

• Introduce Adaptive Control of Transmission Power for RPL (ACTOR) to dynamically optimize transmission power in IoT networks.
• Enhance throughput in dense IoT networks through passive exploration of transmission power levels.
• Improve overall network efficiency and stability.

Main Methods:

• Implemented ACTOR, a novel approach for dynamic transmission power control in RPL.
• Utilized bandit theory solutions (UCB, Discounted UCB) to accelerate exploration and ensure optimality.
• Integrated mechanisms for blacklisting suboptimal power levels and stabilizing network topology.

Main Results:

• ACTOR improved packet delivery ratio by nearly 20% in testbed experiments.
• Reduced node transmission power by up to 10 dBm.
• Demonstrated significant reductions in parent switches, indicating a more stable topology.
• Simulations showed up to 50% improvement in end-to-end delay, packet delivery, and energy consumption across various scenarios.

Conclusions:

• ACTOR effectively optimizes transmission power in RPL networks, outperforming standard RPL and benchmarks.
• The proposed method enhances throughput, reduces energy consumption, and stabilizes network topology in dense IoT environments.
• ACTOR offers a promising solution for improving the performance and efficiency of low-power and lossy networks.