网络中高机密数据传输速率优化数学建模分析

Mathematical Modeling Analysis of High Confidential Data Transmission Rate Optimization in Network

针对传统模型无法为节点分配最佳的数据速率而导致吞吐量低、延时长等问题,提出一种基于空闲信道检测的高机密数据传输速率优化模型。对近邻时隙对的传输信道状态进行概率分析,计算出目标网络信道繁忙概率,使高机密数据主动躲让减少冲突。基于信道状态模型构造一种时空动态感知矩阵,降低采样频率。以最小传输数据量为优化目标,链路容量、功率、路由选取为约束条件,构建了数据传输速率优化模型。通过求解速率优化模型,获得最优的数据传输策略。实验结果表明,在传输数据所用时间上,所提模型相比基于最优停止理论的传输速率优化模型以及基于多信道分配决策的传输速率优化模型提高了15%以上,在提高吞吐量和减少延迟时间上也显示出了更好的效果。

This paper focuses on a model for optimizing high confidential data transmission rate based on idle channel detection. At first, we analyzed the probability of transmission channel state of neighboring time slot pair and calculated the busy probability of objective network channel, and then the high confidential data could actively take evasive action and reduce the conflict. In addition, we built the spatio-temporal dynamic sensing matrix based on channel state model to reduce the sampling frequency. Taking the minimum transmission data as the optimization goal, and taking the link capacity, link power and routing selection as constraints, we constructed the data transmission rate optimization model. By solving the model of rate optimization, we got the optimal data transmission strategy. Simulation results show that, compared with the transmission rate optimization model based on the optimal stopping theory and the transmission rate optimization model based on the multi-channel allocation decision, the data transmission time of the proposed model is increased by more than 15%. Meanwhile, this model shows a better effect in improving throughput and reducing time delay.