Distributed Channel Allocation and Time Slot Optimization for Green Internet of Things

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• Power saving is critical for energy-constrained Internet of Things (IoT) networks in sustainable smart cities.
• Efficient resource utilization, including channels and time slots, is key to reducing interference and energy consumption.
• Existing solutions often require central coordination, which is not ideal for distributed IoT environments.

Purpose of the Study:

• To propose a joint channel allocation and time slot optimization solution for IoT networks.
• To enable distributed operation using only local information, eliminating the need for central coordination.
• To enhance network throughput and energy efficiency while balancing node lifetime.

Main Methods:

• A channel ranking algorithm for nodes to assess available channels based on properties.
• A distributed channel allocation algorithm where nodes select channels using rankings and residual energy.
• Joint optimization of sleeping and spectrum sensing durations to maximize throughput and meet energy constraints.

Main Results:

• Nodes are allocated appropriate channels based on residual energy, promoting balanced network lifetime.
• The network achieves rapid convergence to collision-free transmission through distributed learning.
• Dynamic time slot optimization leads to significant improvements in overall network throughput.

Conclusions:

• The proposed distributed solution effectively manages resources in IoT networks for smart cities.
• It enhances energy efficiency, network lifetime, and throughput without central control.
• The approach is validated through theoretical analysis and extensive simulations.