基于自愈技术的无线传感器网络基站生存模型

何欣 1; 2; 桂小林 1

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基于自愈技术的无线传感器网络基站生存模型

专题研究 | 更新时间：2025-12-08

- 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
- 西安交通大学学报 2008年42卷第8期页码：950-953+1000
- 作者机构：
  
  1. 西安交通大学计算机科学与技术系,西安,710049
  2. 河南大学计算中心,河南,开封,475001
- 作者简介：
- 基金信息：
  
  : 2007-11-26. 作者简介: 何欣(1974-),男,博士生;桂小林(联系人),男,教授,博士生导师. 基金项目: 陕西省科技攻关资助项目(200704K05)
- DOI：
  中图分类号： TP393
- 网络首发：2008-08-10，
  
  纸质出版：2008
- 稿件说明：
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何欣 1, 2, 桂小林 1. 基于自愈技术的无线传感器网络基站生存模型[J]. 西安交通大学学报, 2008,42(8):950-953+1000.

何欣 1, 2, 桂小林 1. Survivable Model for Base Station in Wireless Sensor Network with Rejuvenation Technology[J]. 2008, 42(8): 950-953+1000.
何欣 1, 2, 桂小林 1. 基于自愈技术的无线传感器网络基站生存模型[J]. 西安交通大学学报, 2008,42(8):950-953+1000. DOI：

何欣 1, 2, 桂小林 1. Survivable Model for Base Station in Wireless Sensor Network with Rejuvenation Technology[J]. 2008, 42(8): 950-953+1000. DOI：

摘要

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.

Abstract

The conventional security technology for wireless sensor network(WSN)mainly 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 recovery.

关键词

Keywords

references

PERRIG A, STANKOVIC J, WAGNER D. Security in wireless sensor networks[J]. Communications of the ACM, 2004,47(6):53-57.

SHAIKH R A, LEE S, SONG Y, et al. Securing distributed wireless sensor networks: issues and guidelines [C]∥Proceedings of International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing. Los Alamitos, CA,USA: IEEE Computer Society,2006:226-231.

GARG S, PULIAFITO A,TELEK M,et al. Analysis of software rejuvenation using Markov rejuvenation stochastic Petri nets [C]∥Proceedings of the 6th International Symposium on Software Reliability Engineering. Los Alamitos, CA, USA: IEEE Computer Society, 1995:180-187.

GROTTKE M, LI L, VAIDYANATHAN K, et al. Analysis of software aging in a web server [J]. IEEE Transactions on Reliability, 2006,55(3):411-420.

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CIARDO G, MUPPALA J, TRIVEDI K S. SPNP:stochastic Petri net package [C]∥Proceedings of the 3rd International Workshop on Petri Nets and Performance Models. Los Alamitos, CA, USA: IEEE Computer Society, 1989:142-151.

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