Efficient Interactive Global Cellular Signal Strength Visualization

• Published in: IEEE transactions on big data Vol. 8; no. 5; pp. 1209 - 1219
• Main Authors: Ma, Mengyu, Chen, Luo, Ouyang, Xue, Liu, Xiaoran, Li, Jun, Jing, Ning
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.10.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Base stations; Big Data; Cascading style sheets; Cellular signal strength; Data visualization; Information flow; parallel computing; Power consumption; Real time; Real-time systems; Signal strength; spatial analysis; Spatial databases; Urbanization; Visualization
• ISSN: 2332-7790; 2332-7790; 2372-2096
• DOI: 10.1109/TBDATA.2020.3029559

Cellular Signal Strength (CSS), defined as the signal power received by mobile phones, is an important aspect of geographic information flow analysis, because the density of such information can reflect the urbanization variables such as population, gross domestic product, built-up area, electric power consumption, etc. Despite the importance, the real-time analysis of global CSS distribution remains a challenging problem due to the large data scale. In this article, a Display-driven Computing (DisDC) technique is designed and applied to provide efficient large scale interactive CSS visualization, generating results by calculating the value of each pixel that directly for display. Specifically, we present an efficient CSS measurement algorithm, which introduces spatial indexes and a corresponding query strategy; besides, an optimized parallel computing architecture is proposed to ensure the ability of real-time visualization. Experiments show that our approach obviously outperforms traditional methods and is capable of handling more than 40 million base stations in real-time. Moreover, an online demonstration is provided at https://github.com/MemoryMmy/CSSMap .