Data Gathering Techniques in WSN: A Cross-Layer View.

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• Wireless sensor networks (WSNs) and the Internet of Things (IoT) have seen exponential growth in scale and application diversity.
• Data collection is a primary function, often involving resource-constrained and diverse devices across various communication layers.
• Existing solutions struggle to scale with the increasing number of connected devices.

Purpose of the Study:

• To provide a comprehensive cross-layer review of data gathering in WSN and IoT networks.
• To highlight essential milestones and foundational solutions in WSN and IoT data collection.
• To focus on recent state-of-the-art research for scalable and efficient network functionality.

Main Methods:

• Literature review of WSN and IoT data gathering techniques.
• Analysis of cross-layer approaches for network communication.
• Examination of recent advancements and their impact on scalability and efficiency.

Main Results:

• Identification of key challenges in data gathering across all network layers.
• Overview of historical and current solutions for WSN and IoT data collection.
• Emphasis on the need for scalable, energy-efficient, and cost-effective solutions.

Conclusions:

• WSN and IoT data gathering requires innovative, scalable, and energy-efficient solutions.
• Cross-layer perspectives are crucial for addressing the complexities of modern networks.
• Future research should leverage technological advancements for improved network performance and user-friendliness.