首页> 外文会议>International Conference on Advanced Materials and Computer Science >Network Security Situation Analysis of Weighted Neural Network with Association Rules Mining
【24h】

Network Security Situation Analysis of Weighted Neural Network with Association Rules Mining

机译:与关联规则挖掘加权神经网络的网络安全状况分析

获取原文

摘要

In order to assess reliability of polymorphic wireless sensor networks, specific to characteristics of communication delays, imperfect cover (IPC) and common cause failure (CCF) which are different from general network, a reliability evaluation model of multistate WSN is constructed, which simultaneously considers processing delay of node data, IPC and CCF. Specific to the problem of "combinatorial explosion" produced by system state space of multimode WSN with the increasing of node number, in order to avoid solving the minimal path set, multistate and multiple-valued decision diagram (MMDD) is introduced to build WSN as required. By just constructing one MMDD, according to common cause set, reliability of WSN can be calculated under the effect of IPC and CCF, which effectively controls the space complexity of the algorithm. Experimental results show that the provided MMDD algorithm can complete reliability assessment task of polymorphic WSN constrained by IPC, CCF and time delay. The calculated reliability value is lower than the result of solution method for model of WSN ignoring the network congestion and the influence of CCF and IPC.
机译:为了评估多态无线传感器网络的可靠性,特定于通信延迟的特征,不完美的覆盖(IPC)和与通用网络不同的常见原因失败(CCF),构建了多态WSN的可靠性评估模型,同时考虑节点数据,IPC和CCF的处理延迟。特定于通过多模WSN的系统状态空间产生的“组合爆炸”的问题,随着节点数的增加,为了避免求解最小路径集,介绍多态和多值决策图(MMDD)以构建WSN为必需的。通过仅构建一个MMDD,根据常见的原因集,可以在IPC和CCF的效果下计算WSN的可靠性,从而有效地控制算法的空间复杂度。实验结果表明,提供的MMDD算法可以完成IPC,CCF和时间延迟约束的多态性WSN的可靠性评估任务。计算的可靠性值低于WSN模型忽略网络拥塞和CCF和IPC影响的解决方案方法的结果。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号