仿蛛网农田无线传感器网络抗毁性量化指标体系构建

为解决传统抗毁性量化指标无法准确描述网络组件失效的耦合关系和全局作用,难以有效归纳、继承蛛网抗毁性机制与规律的问题,该文提出了一套基于节点平均路径数和节点、链路平均使用次数的人工蛛网模型抗毁性量化指标体系,评测失效网络组件的全网影响度和权重等指标。仿真试验表明该指标体系可有效量化评价不同规模的人工蛛网模型的抗毁性,测评各网络组件的抗毁性权重占比,其中,节点、弦链、辐链分别占50%、39.44%、10.56%,同时与传统抗毁性量化指标相比,该文提出的指标具有独特的优势。田间试验结果表明节点遭受不同程度损坏时,仿蛛网部署仍可通过备用链路进行数据传输,相较非交叠分簇部署、栅格部署具有更优的抗毁性。人工蛛网模型抗毁性量化分析可为优化农田无线传感器网络部署,实现规模化可靠应用提供参考。

Construction of quantitative indicator system of invulnerability for bionic spider-web farmland wireless sensor network

Combining the unique advantages of spider web with communication technology of wireless sensor network, presents high research value and broad development prospects. Nevertheless, the traditional quantitative index of invulnerability can not accurately describe the coupling relationship and overall function of failed network components, which leads to the difficulty in effectively inheriting the invulnerability mechanism of the artificial spider web model. In this paper, a sort of quantitative index system of invulnerability was proposed based on average number of node paths and average usage number of nodes and links, as the indicators for evaluating the impact degree and weight assignment of failed network components. In order to investigate effectiveness and availability of the index system, 3 independent artificial spider web models were involved in simulation analysis. The simulation experiment showed that the average number of node paths, the average usage number of nodes, chord chains and spoke chains were in consistent with the approximate regulations for different scale artificial spider-web models. Among them, in the case of the failure of nodes, chord chains and spoke chains, the attenuation of average number of node paths had unidirectional diffusion, namely the failure only affected the outer layers of failure location. Meanwhile, the attenuation of average usage number of nodes, chord chains and spoke chains had bidirectional diffusivity, and the failure affected both inside and outside of the layer where it was located. It showed that there were obvious cross-coupling relations and inter-layer coupling correlation between nodes and links. At the same time, the failure of local components would affect the whole network, and the effect of the same layer and the adjacent layer was more significant, indicating that the failure process of artificial spider-web model had obvious cascade diffusion characteristics. Moreover, the number of node paths of any node was exponentially positively correlated with the scale of the model and the number of layers in which it was located. As the layer number increasing, the average usage times of nodes, chord chains and spoke chains gradually decreased, the inner layers decreased slightly, and the outer layers had significant downward trend. In conclusion, the index system could effectively quantify the invulnerability of artificial spider web model, and evaluate the weight proportion of each network component, and the nodes, chord and spoke chains account for 50%, 39.44% and 10.56% respectively. The weight ratio of the first layer node, chord chain and spoke chain reached 33.28%, and the outermost layer only accounted for 6.72%. It manifested that the importance of nodes and chord chains was much higher than that of spoke chains, and the components closer to the network center had had higher value. Compared with the traditional index, the index system proposed in this paper had unique advantages. Field experiment adopted 3 network deployment schemes consisting of one sink node and 12 common nodes respectively. Node energy consumption, packet loss rate, delay and hops were applied as the indicators. The results showed that spider web deployment had better invulnerability than non-overlapping clustering deployment and grid deployment. In addition, the failure of nodes would cause the increase of packet loss rate, delay time and hops of adjacent outer nodes, which was similar to the theoretical simulation results. Quantitative analysis of the invulnerability of artificial spider web model can provide useful guidance for optimizing the deployment of farmland wireless sensor network and achieving reliable applications.