基于自愈技术的无线传感器网络基站生存模型

Survivable Model for Base Station in Wireless Sensor Network with Rejuvenation Technology

传统无线传感器网络(WSN)的安全研究主要集中在提高系统的抗入侵能力上,却很少涉及系统被入侵或失效后如何继续对外提供服务的问题,为此引入自愈技术的思想,构建了一种WSN基站生存模型.通过监测系统性能来预测系统失效点,及时执行自愈操作,从而在攻击、失效发生后,使系统仍能继续提供服务.此外,使用半马尔科夫过程来描述模型,并通过分析模型稳定健康状态的概率,发现系统受损状态的检测率是提高模型生存性的关键参数.仿真结果显示,系统检测率与失效率之间呈反向变化关系,通过自愈技术提高检测率并及时进行自愈恢复,可显著降低系统失效率,提高系统的生存性.

The conventional security technology for wireless sensor network （WSN） mamty is focused on improving the anti-invasion ability, but not on providing external services after the invasion and failure, and hence, the survivability of WSN is poor. Based on the rejuvenation technology, a survivable model for base station in WSN is designed. The uninterrupted services can be provided by the model in face of attack or failure by monitoring system performance to predict the rejuvenation interval and timely implementing rejuvenation recovery. By analyzing the probability in steady health state of the model using semi-Markov process, it is found that the detect probability in the compromised state is a key point to improve the model survivability. According to the experimental results, the failure probability varies inversely with the detect probability. Therefore, the failure probability can be reduced significantly and hence the survivability of the system can be enhanced by increasing the detect probability and timely implementing rejuvenation recovcry.