1. College of Information and Navigation, Air Force Engineering University, Xi’an 710077, China 2. Unit 95816 of People’s Liberation Army, Hubei 432700, China 3. Department of Computer Science, Northwestern Polytechnical University, Xi’an 710072, China 4. Department of Software Micro-electronics, Northwestern Polytechnical University, Xi’an 710072, China
The network repair problem after the nodes in the military communication network were hit was described, and the topology of the communication network was repaired by using the network edge-adding method. An edge addition repair model was established with maximizing network invulnerability as objective function, network connection cost and network connectivity as constraints. The network connection cost model considering redundant and necessary edges was defined. A model solving method based on the discrete artificial bee colony algorithm was proposed. Through specific cases of military communication network, simulation experiments were conducted under random and deliberate attacks, respectively. In the experiment, the proposed method was compared with other edge-adding methods, such as random addition, low degree first addition and low betweenness addition. Results showed that the proposed method can improve the survivability of network and the result was better than that of other three methods.
Guan-yu CHEN,Peng SUN,Jie-yong ZHANG,Jun-sheng WU. Repair strategy of military communication network. Journal of ZheJiang University (Engineering Science), 2019, 53(8): 1536-1545.
Tab.4Connection relationship between platform and communication entity
Fig.5Pre-destruction topology structure
Fig.6Algorithm performance under random attack
Fig.7Algorithm performance under deliberate attack
Fig.8Variation of experimental results with cost under random attack
Fig.9Variation of experimental results with cost under deliberate attack
Fig.10Algorithm performance comparison under random attack
Fig.13Variation of experimental results with cost upper under deliberate attack for different algorithms
Fig.11Variation of experimental results with cost upper under random attack for different algorithms
Fig.12Algorithm performance comparison under deliberate attack
Fig.14Algorithm performance comparison of different weight coefficients under random attack
Fig.15Algorithm performance comparison of different weight coefficients under deliberate attack
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