Measuring Consistency Metric for Web Applications

被引:0
|
作者
Dane, Levent [1 ]
Gurkan, Deniz [1 ]
机构
[1] Univ Houston, Engn Technol, Houston, TX 77004 USA
来源
2022 IEEE 12TH ANNUAL COMPUTING AND COMMUNICATION WORKSHOP AND CONFERENCE (CCWC) | 2022年
关键词
Web services; Computer network reliability; Content distribution networks;
D O I
10.1109/CCWC54503.2022.9720827
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Web application performance analysis is critical in determination of content delivery time delay and user experience issues. Typical approaches focus on a nominal performance perspective where individual components of web application resource delivery is analyzed and optimized over a presumed minimum delay baseline such as the propagation delay for given distance traveled over the network. Each component of the system is bound to cross various administrative domains and technical demarcation points resulting in a tendency towards an over-provisioned solution set. On the other hand, the user experience has a subjective component where the consistency experiences may dictate a lesser performance as acceptable for an application. That is, if user experiences are taken as the nominal optimization constraint, the baseline measurement of the consistency experienced by the user may serve the analysis and the consecutive improvement measures both more useful and maybe more importantly, more cost-effective. In this respect, this paper presents a novel baseline measurement metric called a consistency metric to utilize as a baseline measurement parameter in making optimization improvements on the web application performance. We present our method of measurements and determination of the consistency metric using our highly distributed geographically-diverse data collection system, NetForager, using two popular applications CNN and YouTube.
引用
收藏
页码:531 / 537
页数:7
相关论文
共 50 条
  • [21] ON MEASURING STATUS CONSISTENCY
    VERMILYE, HA
    AMERICAN SOCIOLOGICAL REVIEW, 1963, 28 (03) : 455 - 456
  • [22] On the Consistency of Metric and Non-Metric K-medoids
    Arias-Castro, Ery
    Jiang, He
    24TH INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS (AISTATS), 2021, 130
  • [23] Scalable consistency maintenance for edge query caches - Exploiting templates in Web applications
    Amiri, K
    Sprenkle, S
    Tewari, R
    Padmanabhan, S
    WEB CONTENT CACHING AND DISTRIBUTION, 2004, : 79 - 90
  • [24] mBenchLab: Measuring QoE of Web Applications using mobile devices
    Cecchet, Emmanuel
    Sims, Robert
    He, Xin
    Shenoy, Prashant
    2013 IEEE/ACM 21ST INTERNATIONAL SYMPOSIUM ON QUALITY OF SERVICE (IWQOS), 2013, : 1 - 10
  • [25] UNIVERSAL BAYES CONSISTENCY IN METRIC SPACES
    Hanneke, Steve
    Kontorovich, Aryeh
    Sabato, Sivan
    Weiss, Roi
    2020 INFORMATION THEORY AND APPLICATIONS WORKSHOP (ITA), 2020,
  • [26] UNIVERSAL BAYES CONSISTENCY IN METRIC SPACES
    Hanneke, Steve
    Kontorovich, Aryeh
    Sabato, Sivan
    Weiss, Roi
    ANNALS OF STATISTICS, 2021, 49 (04): : 2129 - 2150
  • [27] Deep Metric Learning with Graph Consistency
    Chen, Binghui
    Li, Pengyu
    Yan, Zhaoyi
    Wang, Biao
    Zhang, Lei
    THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2021, 35 : 982 - 990
  • [28] Strong consistency of nonparametric Bayes density estimation on compact metric spaces with applications to specific manifolds
    Bhattacharya, Abhishek
    Dunson, David B.
    ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS, 2012, 64 (04) : 687 - 714
  • [29] Strong consistency of nonparametric Bayes density estimation on compact metric spaces with applications to specific manifolds
    Abhishek Bhattacharya
    David B. Dunson
    Annals of the Institute of Statistical Mathematics, 2012, 64 : 687 - 714
  • [30] MEASURING CONSISTENCY WITH THE GRID TEST
    CYR, JJ
    BRITISH JOURNAL OF CLINICAL PSYCHOLOGY, 1983, 22 (SEP) : 219 - 220