Virus spreading in wireless sensor networks with a medium access control mechanism
- ISSN号:1674-1056
- 期刊名称:Chinese Physics B
- 时间:2013.4.1
- 页码:-
- 分类:TP212[自动化与计算机技术—控制科学与工程;自动化与计算机技术—检测技术与自动化装置] TP316.81[自动化与计算机技术—计算机软件与理论;自动化与计算机技术—计算机科学与技术]
- 作者机构:[1]Network and Information Security Key Laboratory of Armed Police Force, Department of Electronics Technology, Engineering University of the Chinese People's Armed Police Force, Xi' an 710086, China
- 相关基金:Project supported by the National Natural Science Foundation of China (Grant Nos. 61103231 and 61103230); the Natural Science Foundation of Jiangsu Province, China (Grant No. BK2012082); the Innovation Program of Graduate Scientific Research in Institution of Higher Education of Jiangsu Province,China (Grant No. CXZZ11 0401); the Natural Science Basic Research Plan in Shaanxi Province of China (Grant No. 2011JM8012); the Basic Research Foundation of Engineering University of the Chinese People’s Armed Police Force (Grant No. WJY201218)
- 相关项目:新型代理加密体制研究
关键词:
无线传感器网络, 访问控制机制, 病毒传播, 媒体接入控制, 节点通信, 网络节点, 数值模拟, 节点数, wireless sensor networks, medium access control, virus spreading, susceptible-infected model
中文摘要:
In this paper, an extended version of standard susceptible-infected (SI) model is proposed to consider the influence of a medium access control mechanism on virus spreading in wireless sensor networks. Theoretical analysis shows that the medium access control mechanism obviously reduces the density of infected nodes in the networks, which has been ignored in previous studies. It is also found that by increasing the network node density or node communication radius greatly increases the number of infected nodes. The theoretical results are confirmed by numerical simulations.
英文摘要:
In this paper, an extended version of standard susceptible-infected (SI) model is proposed to consider the influence of a medium access control mechanism on virus spreading in wireless sensor networks. Theoretical analysis shows that the medium access control mechanism obviously reduces the density of infected nodes in the networks, which has been ignored in previous studies. It is also found that by increasing the network node density or node communication radius greatly increases the number of infected nodes. The theoretical results are confirmed by numerical simulations.