Distance-Based Queuing for Scalable and Reliable Linear Wireless Sensor Networks in Smart Cities.

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• Linear Wireless Sensor Networks (LWSNs) face reliability and scalability challenges due to high packet loss probabilities (PLP) for nodes distant from the sink.
• This issue critically impacts Smart City applications requiring timely data collection for effective decision-making.
• Prior research has not adequately addressed this specific problem, focusing instead on general network performance improvements.

Purpose of the Study:

• To propose a novel Distance-Based Queuing (DBQ) scheme for MAC protocols in LWSNs.
• To enhance network reliability and scalability by mitigating the impact of node distance on packet loss.
• To ensure consistent packet loss probabilities across all network nodes without additional local processing or signaling.

Main Methods:

• Developed a Distance-Based Queuing (DBQ) scheme for integration into MAC protocols.
• Created an analytical model to theoretically evaluate the DBQ scheme's performance.
• Conducted extensive discrete-event simulations to validate the proposed scheme under various conditions.

Main Results:

• The DBQ scheme ensures that all nodes experience the same average packet loss probability (PLP), irrespective of their hop distance to the sink.
• Demonstrated significant improvements in network reliability and scalability.
• Showcased consistent throughput across all nodes, regardless of traffic intensities and network sizes.

Conclusions:

• The Distance-Based Queuing (DBQ) scheme effectively addresses the PLP limitations in LWSNs.
• DBQ offers a practical solution for enhancing the reliability and scalability of LWSNs, particularly for Smart City applications.
• The proposed scheme provides a uniform experience for all nodes, improving overall network performance and data collection efficiency.