Abstract：To solve the problem of data congestion due to the limitation of node buffer space in the apron-aware opportunity network, a control strategy of apron opportunity network cache under cellular evolution rule (ACER) was proposed. A routing communication model was established based on node congestion degree. The node congestion was judged, and the data routing communication based on probability was carried out in the nodes with low congestion degree. For the nodes with high congestion degree, the message discarding strategy of cellular automata was used to effectively alleviate the network issues of low delivery rate caused by data congestion, so that the data transmission of node load was balanced. Based on the opportunity network environment (ONE) simulation platform, the map of Tianjin Binhai International Airport was used to conduct experiments to analyze the performance of the algorithm under different numbers of nodes and different cache spaces. The results show that in the apron network simulation environment, with different numbers of nodes and different cache capacities, compared to DY and DL cache management strategies, the ACER delivery rate is increased by 97% at most with the network overhead reduced by 70% at most, and the transmission delay has a certain degree of improvement.
CHEN W X, SU J F, MENG M H. WSN-ON access mechanism and protocol under apron awareness environment[J]. Journal of Jiangsu University (Natural Science Edition),2020,41(3):359-365. (in Chinese)
HUANG D L, QIU Z Q, PENG D Q. An opportunistic VANET routing in urban environment[J]. Journal of Chongqing University Posts and Telecommunications (Natural Science Edition),2018,30(4):484-491. (in Chinese)
ZHANG F. Node encounter interval based buffer ma-nagement strategy in opportunistic networks[J]. Compu-ter Science, 2019,46(5):57-61. (in Chinese)
［4］
EZIFE F, LI W, YANG S H. A survey of buffer ma-nagement strategies in delay tolerant networks[C]∥Proceedings of the 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems. New York：IEEE, 2017：599-603.
ZHANG F, WANG X M, ZHANG L C, et al. A cellular-learning-automata-based congestion control strategy in opportunistic networks[J]. Journal of Sichuan University（Engineering Science Edition）, 2016,48(1):158-165. (in Chinese)
［6］
WANG B, LIU L, LI F, et al. A congestion control strategy for opportunistic network[C]∥Proceedings of 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference. New York：IEEE,2018：1824-1828.
［7］
SILVA M D, NUNES I O, MINI R A F, et al. ST-Drop: a novel buffer management strategy for D2D opportunistic networks[C]∥Proceedings of the 2017 IEEE Symposium on Computers and Communications. New York：IEEE, 2017：1300-1305.
［8］
KRIFA A, BARAKAT C, SPYROPOULOS T. Optimal buffer management policies for delay tolerant networks[C]∥Proceedings of the 2008 5th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks. Piscataway：IEEE Computer Society, 2008:260-268.
［9］
SZABO C. Complex systems modeling and analysis[C]∥Proceedings of the 2019 Winter Simulation Conference. New York：IEEE, 2019：1495-1503.
［10］
AHANGARAN M, TAGHIZADEH N, BEIGY H. Associative cellular learning automata and its applications[J].Applied Soft Computing Journal, 2017, doi：10.1016/j.asoc.2016.12.006.
［11］
NAVID A H F, JAVADI H H S. ICLEAR: energy aware routing protocol for WSN using irregular cellular learning automata[C]∥Proceedings of the 2009 IEEE Symposium on Industrial Electronics and Applications. Piscataway：IEEE Computer Society, 2009:463-468.
［12］
CUI J Q, CAO S Q, CHANG Y N, et al. An adaptive spray and wait routing algorithm based on quality of node in delay tolerant network[J]. IEEE Access, 2019，7:35274-35286.
2022, Vol. 43 
