Poster abstract: Light-weight network health monitoring

Yi-Hsuan Chiang, M. Keller, R. Lim, Polly Huang, J. Beutel
{"title":"Poster abstract: Light-weight network health monitoring","authors":"Yi-Hsuan Chiang, M. Keller, R. Lim, Polly Huang, J. Beutel","doi":"10.1145/2185677.2185701","DOIUrl":null,"url":null,"abstract":"As the application of WSNs for long-term monitoring purposes becomes real, the issue of WSN system health monitoring grows increasingly important. Manually understanding the root causes of an observed behavior is time-consuming and difficult, often knowledge of prior behavior is necessary for understanding the potential risk on the long-term system performance. The challenges lie in the balance between the amount of system data collected and the level of detail in which state can be inferred from this data. In this paper, we propose a lightweight runtime logging and corresponding network state inference mechanism that enables scalable WSN health monitoring. Concretely, we propose that nodes only report their internal state on the occurrence of important events. Having a very low computational complexity and message overhead within the sensor network, reported events are analyzed at a less constrained network sink.","PeriodicalId":231003,"journal":{"name":"2012 ACM/IEEE 11th International Conference on Information Processing in Sensor Networks (IPSN)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 ACM/IEEE 11th International Conference on Information Processing in Sensor Networks (IPSN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2185677.2185701","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

As the application of WSNs for long-term monitoring purposes becomes real, the issue of WSN system health monitoring grows increasingly important. Manually understanding the root causes of an observed behavior is time-consuming and difficult, often knowledge of prior behavior is necessary for understanding the potential risk on the long-term system performance. The challenges lie in the balance between the amount of system data collected and the level of detail in which state can be inferred from this data. In this paper, we propose a lightweight runtime logging and corresponding network state inference mechanism that enables scalable WSN health monitoring. Concretely, we propose that nodes only report their internal state on the occurrence of important events. Having a very low computational complexity and message overhead within the sensor network, reported events are analyzed at a less constrained network sink.
海报摘要:轻量级网络健康监测
随着无线传感器网络用于长期监测的应用成为现实,无线传感器网络系统的健康监测问题变得越来越重要。手动理解观察到的行为的根本原因是耗时和困难的,通常了解先前的行为对于理解长期系统性能的潜在风险是必要的。挑战在于收集的系统数据量和可以从这些数据推断状态的详细程度之间的平衡。在本文中,我们提出了一种轻量级的运行时日志记录和相应的网络状态推断机制,以实现可扩展的WSN健康监控。具体来说,我们建议节点仅在重要事件发生时报告其内部状态。由于传感器网络的计算复杂性和消息开销非常低,报告的事件在约束较少的网络接收器上进行分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信