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A novel scheme of cross‐network radio resources scheduling in SAGN based on unified resources mapping and genetic algorithm
Author(s) -
Li Zhongguo,
Yang Fuxing,
Lin Wenliang,
Wang Ke,
Deng Zhongliang,
Yu Xiaoyi,
Fan Liangliang,
Gu Lei
Publication year - 2021
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.4844
Subject(s) - computer science , distributed computing , scheduling (production processes) , quality of service , computer network , exploit , virtual network , heterogeneous network , real time computing , wireless network , wireless , telecommunications , computer security , operations management , economics
Summary To decrease human deaths in the disaster and ensure the efficiency of emergency aid, high accuracy logistics can play an important role. To achieve this target, anytime and anywhere communications would contribute to rapid information interaction on situation monitoring of logistics. Space‐air‐ground network (SAGN) is the network combined with satellite network, aerial network, and territorial network, which can achieve global communication coverage. That means it would be a heterogeneous network, in which each network providing with different radio communication resources. If we would like to exploit the SAGN to achieve reliable support of communication, we have to solve the problems of the unified mapping of different radio communication resources. Besides, we should further design the exact scheduling scheme for the communication service of emergency logistics with global heterogeneous networks. Therefore, we propose a novel scheme of cross‐network radio resources scheduling in SAGN based on unified resources mapping and genetic algorithm. First, we build the system model for SAGN in the scenario of emergency logistics. Second, the unified resource mapping method is proposed, which achieves global cross‐network resources virtualization by the quality of service (QoS) bearer matching. Third, the multi‐population genetic algorithm is introduced to relate with each network resource to achieve available virtual global radio communication resource scheduling. The simulation results show that the resource efficiency of this proposed scheme has a better performance compared with the other resource scheduling method, which increased by 11.8 % compared with bottom‐left (BL) algorithm.