首页> 外文会议>International Conference on Sustainable Energy Information Technology >Localized Algorithm for Segregation of Critical/Non-critical Nodes in Mobile Ad Hoc and Sensor Networks
【24h】

Localized Algorithm for Segregation of Critical/Non-critical Nodes in Mobile Ad Hoc and Sensor Networks

机译:用于移动临时和传感器网络中临界/非关键节点的分离的本地化算法

获取原文

摘要

Timely segregation of connectivity-centric critical/non-critical nodes is extremely crucial in mobile ad hoc and sensor networks to assess network vulnerabilities against critical node failures and provide precautionary means for survivability. This paper presents a localized algorithm for segregation of critical/non-critical nodes (LASCNN) that opts to distinguish critical/non-critical nodes to the network connectivity based on limited topology information. Each node establishes and maintains a k-hop connection list and employ LASCNN to determine whether it is critical/non- critical. Based on the list, LASCNN marks a node as critical if its k-hop neighbor's become disconnected without the node, non-critical otherwise. Simulation experiments demonstrate the scalability of LASCNN and shows the performance is quite competitive compared to a scheme with global network information. The accuracy of LASCNN in determining critical nodes is 87% (1-hop) and 93% (2-hop) and non-critical nodes 91% (1-hop) and 93% (2-hop).
机译:连接性为中心的临界/非关键节点的及时分离在移动临时和传感器网络中非常重要,以评估对关键节点故障的网络漏洞,并提供用于生存能力的预防性手段。本文介绍了临界/非关键节点(Lascnn)的分离算法,该算法选择基于有限的拓扑信息来区分临界/非关键节点到网络连接。每个节点建立并维护K-Hop连接列表,并雇用Lascnn以确定它是否至关重要/非关键。基于列表,如果其K-Hop邻居未在没有节点的情况下断开连接,则Lascnn将节点标记为关键。仿真实验表明,与具有全球网络信息的方案相比,LASCNN的可扩展性并表明性能非常有竞争力。 Lascnn在确定关键节点时的准确性为87%(1跳)和93%(2跳)和非关键节点91%(1跳)和93%(2跳)。

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