Modeling and Analyzing Urban Sensor Network Connectivity Based on Open Data

Area of Science:

• Computer Science
• Network Engineering
• Urban Planning

Background:

• Optimizing wireless sensor network topology is key for efficient data transmission.
• Open data sources offer new possibilities for modeling urban sensor networks.
• Real location data is essential for accurate network infrastructure representation.

Purpose of the Study:

• To develop and evaluate algorithms for modeling heterogeneous urban sensor networks using open data.
• To construct and analyze static and dynamic network topologies based on real-world data.
• To investigate the characteristics of urban network structures through simulation.

Main Methods:

• Utilizing open data sources for real location data of networked and sensing devices.
• Developing algorithms to transform device location data into graph-based network connectivity models.
• Constructing static and dynamic network topologies in four Polish cities.
• Conducting multidimensional simulation-based analysis.

Main Results:

• Successful transformation of device location data into graph-based network connectivity models.
• Construction of static and dynamic network topologies for four major Polish cities.
• Simulation-based analysis revealing characteristics of modeled urban network structures.
• Validation of the approach using real-world, frequently updated data.

Conclusions:

• Open data sources are effective for modeling urban wireless sensor network topologies.
• The proposed algorithms and architecture provide a robust method for network analysis.
• The findings support more accurate and dynamic network infrastructure representations.
• Further research directions for network optimization and analysis are identified.