Sharing Big Data Storage for Air Traffic Management

Yang, Hengyi; Huang, Yongqiang

doi:10.1109/iccc56324.2022.10065656

Cited by 1 publication

(1 citation statement)

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“…Keller et al [5] introduced a system for combining heterogeneous air traffic management with semantic integration techniques, which transforms data from disparate source formats into a unified semantic representation of ontology-based triplets. Liu et al [6] implemented seamless communication and mutual cooperation between civil aviation systems through information sharing, which could support collaborative decision-making of air traffic management and improve the capacity of airspace systems. Lu et al [7] proposed an integration architecture of cloud computing and blockchain for ATM systems, in which it pointed out the advantages of the new technology architecture over the traditional architecture of existing ATM systems.…”

Section: Related Workmentioning

confidence: 99%

An Improvement for Spatial-Temporal Queries of ATMGRAPH

Zhiyuan,

Boyang

2023

IJACSA

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As a knowledge graph for the field of ATM (Air Traffic Management), ATMGRAPH integrates aviation information from various sources, and provides a new way to comprehensively analyze ATM data, but the storage schema of ATMGRAPH is inefficient for trajectory-related queries which have typical spatial-temporal characteristics, thus cannot meet the application requirements. This paper presents an improved storage model of ATMGRAPH, specifically, we design a cluster structure to connect trajectory points and spatial-temporal information to speed up trajectory-related queries, and we link flights, airports, and weather information in an effective way to speed up weather-related queries. We create a dataset of about 10,000 real domestic flights, and build a knowledge graph of it which contains about 11.66 million triplets. Experimental results show that ATM knowledge graph constructed by this storage model can significantly improve the efficiency of spatial-temporal related queries.

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Section: Related Workmentioning

confidence: 99%