2013 IEEE International Workshop on Measurements & Networking (M&N)最新文献_第4页

RESIMA: A new WSN based paradigm to assist weak people in indoor environment RESIMA:一种新的基于无线传感器网络的室内环境弱者辅助模式

2013 IEEE International Workshop on Measurements & Networking (M&N) Pub Date : 2013-11-14 DOI: 10.1109/IWMN.2013.6663804

B. Andò, S. Baglio, C. O. Lombardo, V. Marletta, E. Pergolizzi, A. Pistorio

引用次数: 12

Model-based throughput prediction in data center networks 数据中心网络中基于模型的吞吐量预测

2013 IEEE International Workshop on Measurements & Networking (M&N) Pub Date : 2013-11-14 DOI: 10.1109/IWMN.2013.6663797

Piotr Rygielski, Samuel Kounev, S. Zschaler

引用次数: 18

Evaluation and possible improvements of the ANT protocol for home heart monitoring applications 家庭心脏监测应用的ANT协议的评估和可能的改进

2013 IEEE International Workshop on Measurements & Networking (M&N) Pub Date : 2013-11-14 DOI: 10.1109/IWMN.2013.6663806

Samuele Gasparrini, E. Gambi, S. Spinsante

引用次数: 3

Characterization of the radio propagation channel aboard trains for optimal coverage at 2.45GHz 2.45GHz列车上无线电传播信道的特性研究

2013 IEEE International Workshop on Measurements & Networking (M&N) Pub Date : 2013-11-14 DOI: 10.1109/IWMN.2013.6663802

A. Mariscotti, A. Marrese, N. Pasquino, R. S. L. Moriello

引用次数: 14

Performance of PHY layer links of WSN: Criterions and ways of improvement 无线传感器网络物理层链路性能:改进标准与方法

2013 IEEE International Workshop on Measurements & Networking (M&N) Pub Date : 2013-11-14 DOI: 10.1109/IWMN.2013.6663776

A. Platonov, I. Zaitsev

引用次数: 4

Low-power communication protocol for low duty cycle data acquisition applications 用于低占空比数据采集应用的低功耗通信协议

2013 IEEE International Workshop on Measurements & Networking (M&N) Pub Date : 2013-11-14 DOI: 10.1109/IWMN.2013.6663777

G. Vakulya, G. Simon

引用次数: 3

Enabling induction and wireless power transmission technologies aimed at supplying remote equipment in critical logistic scenarios 启用感应和无线电力传输技术，旨在为关键后勤方案提供远程设备

2013 IEEE International Workshop on Measurements & Networking (M&N) Pub Date : 2013-11-14 DOI: 10.1109/IWMN.2013.6663800

L. Angrisani, Guido D'Alessandro, M. D'Apuzzo, M. D’Arco

引用次数: 8

Experimental analysis of the first order time difference of indicators used in the monitoring of complex systems 复杂系统监测中指标一阶时差的实验分析

2013 IEEE International Workshop on Measurements & Networking (M&N) Pub Date : 2013-11-14 DOI: 10.1109/IWMN.2013.6663792

A. Bondavalli, F. Brancati, A. Ceccarelli, Diego Santoro, M. Vadursi

{"title":"Experimental analysis of the first order time difference of indicators used in the monitoring of complex systems","authors":"A. Bondavalli, F. Brancati, A. Ceccarelli, Diego Santoro, M. Vadursi","doi":"10.1109/IWMN.2013.6663792","DOIUrl":"https://doi.org/10.1109/IWMN.2013.6663792","url":null,"abstract":"Complex and real time systems often operate under variable and non-stationary conditions, thus requiring efficient and extensive monitoring and error detection solutions. Amongst the many, we focus on anomaly detection techniques, which require measuring the evolution of the monitored indicators through time to identify anomalies i.e., deviations from the expected operational behavior. In this paper, we investigate the possibility to model the evolution of indicators through time using the random walk model. In particular, we focus on the detection of system anomalies at the application level (software errors), based on the monitoring of indicators at the Operating System level. The approach is based on the experimental evaluation of a large set of heterogeneous indicators, acquired under different operating conditions, both in terms of workload and fault load, on an air traffic management target system. The results of the analysis show that for a large number of cases, the histogram of the first order time differences well approximates a Gaussian distribution, independently of the nature of the indicator and its statistical distribution. Such outcomes suggest that the idea of adopting a Gaussian random walk model for several monitoring indicators has an experimental support and deserves be further investigated on a wider scale, in order to determine its range of applicability and representativeness.","PeriodicalId":218660,"journal":{"name":"2013 IEEE International Workshop on Measurements & Networking (M&N)","volume":"213 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121348280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Predicting time series of individual trends with resolution adaptive ARIMA 分辨率自适应ARIMA预测时间序列个体趋势

2013 IEEE International Workshop on Measurements & Networking (M&N) Pub Date : 2013-10-01 DOI: 10.1109/IWMN.2013.6663793

Hiroki Nakayama, S. Ata, I. Oka

{"title":"Predicting time series of individual trends with resolution adaptive ARIMA","authors":"Hiroki Nakayama, S. Ata, I. Oka","doi":"10.1109/IWMN.2013.6663793","DOIUrl":"https://doi.org/10.1109/IWMN.2013.6663793","url":null,"abstract":"It is important to analyze and predict the time series of traffic trends from the perspective of network operation and management, such as that in fine-grained traffic control, capacity dimensioning, and traffic engineering. However, it is difficult to accurately predict traffic trends because this strongly depends on the time, the type of content, and its popularity. We propose new methods of accurately predicting traffic trends in this paper. Our methods are based on a wavelet transform and the auto regressive integrated moving average (ARIMA) model. We first demonstrate that applying a wavelet transform can improve the accuracy of prediction compared to the original ARIMA model; however, it still has large error due to the fixed time granularity of each resolution. We therefore propose a resolution adaptive ARIMA (RA-ARIMA) model to improve accuracy by changing the time granularity according to the degree of resolution. We demonstrate that by applying it to the real monitored data in a major P2P file-sharing system the normalized mean squared error of RA-ARIMA can be reduced by more than 20% of that of Wavelet-ARIMA. Moreover, we also compared RA-ARIMA with other existing models to prove the accuracy of our proposed method.","PeriodicalId":218660,"journal":{"name":"2013 IEEE International Workshop on Measurements & Networking (M&N)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122035419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Impulse noise mitigation for MIMO-OFDM wireless networks with linear equalization 基于线性均衡的MIMO-OFDM无线网络脉冲噪声抑制

2013 IEEE International Workshop on Measurements & Networking (M&N) Pub Date : 2013-10-01 DOI: 10.1109/IWMN.2013.6663784

D. Darsena, G. Gelli, Fulvio Melito, F. Verde, Andrea Vitiello

引用次数: 9