Forwarding in Energy-Constrained Wireless Information Centric Networks.

Area of Science:

• Computer Science
• Network Engineering
• Smart City Technologies

Background:

• Host-centric network architectures face challenges in large-scale Internet of Things (IoT) deployments, particularly within smart city contexts.
• High sensor density in smart cities leads to significant energy demands, necessitating improved energy management strategies.
• Existing Information Centric Networks (ICNs) offer potential but require adaptation for energy-constrained wireless environments.

Purpose of the Study:

• To propose an efficient forwarding scheme for energy-constrained wireless ICNs tailored for IoT applications in smart cities.
• To enhance energy management by considering device characteristics, energy levels, and network context.
• To improve content delivery quality and network longevity in mobile environments.

Main Methods:

• Developed a forwarding strategy integrating packet domain analysis, neighborhood evaluation, and dynamic node sleeping/waking mechanisms.
• Adapted ICN concepts to optimize data forwarding based on device parameters and network conditions.
• Utilized real-world urban mobility datasets from "Ria de Aveiro" and Porto for simulation-based evaluation.

Main Results:

• Demonstrated significant improvements in network content availability.
• Achieved substantial overall energy savings.
• Showcased a consequent increase in overall network lifetime.

Conclusions:

• The proposed forwarding scheme effectively addresses energy constraints in wireless ICNs for IoT smart cities.
• The strategy enhances network performance by optimizing energy usage and content delivery.
• This approach offers a viable solution for sustainable and efficient smart city networks.