A Greedy Scanning Data Collection Strategy for Large-Scale Wireless Sensor Networks with a Mobile Sink

Area of Science:

• Computer Science
• Wireless Sensor Networks
• Network Protocols

Background:

• Mobile sinks are crucial for data collection in wireless sensor networks (WSNs).
• Traditional multihop transmission leads to energy inefficiency and 'hot spot' problems in real-time applications.
• Predetermined or random sink trajectories fail to optimize energy consumption.

Purpose of the Study:

• To propose a novel greedy scanning data collection strategy (GSDCS) for WSNs.
• To reduce routing energy consumption by minimizing the total length of data transmission paths.
• To enhance energy efficiency in real-time and event-driven WSN applications.

Main Methods:

• Dynamic adjustment of the mobile sink's trajectory based on network conditions.
• Identifying and moving towards areas with a higher density of source nodes.
• Analyzing and simulating the GSDCS performance against existing methods.

Main Results:

• GSDCS significantly reduces the need for long-distance data uploads from source nodes.
• The strategy proves effective in event-driven scenarios by adapting to changing event areas.
• Analytical and simulation results demonstrate superior performance compared to conventional approaches.

Conclusions:

• GSDCS offers a more energy-efficient data collection method for WSNs.
• Dynamic trajectory adjustment is key to optimizing energy usage in mobile sink networks.
• The proposed strategy shows promise for real-time and event-driven WSN applications.