Journal
IEEE ACCESS
Volume 8, Issue -, Pages 113003-113010Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2020.2996740
Keywords
Routing; Geometry; Satellites; Earth; Complex networks; Scalability; Space vehicles; Integrated satellite-terrestrial network; hyperbolic geometry; network mapping; greedy forwarding
Categories
Funding
- PCL Future Greater-Bay Area Network Facilities for Large-scale Experiments and Applications [LZC0019]
- Natural Science Foundation of China (NSFC) [61671001]
- Research and Development Key Program of Guangdong Province [2019B010137001]
- National Keystone Research and Development Program of China [2017YFB0803204]
- Shenzhen Research Programs [JSGG20170824095858416, JCYJ20190808155607340]
- Shenzhen Municipal Development and Reform Commission (Disciplinary Development Program for Data Science and Intelligent Computing)
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The integrated satellite-terrestrial network has the characteristics of large scale, complex, high dynamic and heterogeneousness. Adopting traditional routing methods in the integrated satellite-terrestrial network will cause problems of poor scalability and large routing overhead. Greedy forwarding strategy based on network mapping with hyperbolic geometry works well in large scale network. However, there is no study on applying the network mapping with hyperbolic geometry to complex networks beyond two dimensions, including the integrated satellite-terrestrial network. Based on the method of spherical polar projection, this paper proposes a hyperbolic coordinates mapping algorithm in three-dimensional geographic space suitable for the integrated satellite-terrestrial network. This algorithm gives nodes of heterogeneous layers in the integrated satellite-terrestrial network a unified expression based on four-dimensional hyperbolic coordinates, which helps to quickly identify and locate nodes without global information distribution and scheduling when routing. The routing strategy using greedy forwarding strategy based on this algorithm only costs low storage overhead, as it does not need routing tables. Simulations demonstrate that the performance of the algorithm is hardly affected by the exponential expansion of the network size, which means the property of scalability is excellent. Also, it is stable under heterogeneous network structure, and maintains a stable routing success rate for optimal path selection around 93% with a time complexity of O(n).
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