Multidimensional Cloud Latency Monitoring and Evaluation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F16%3A00305157" target="_blank" >RIV/68407700:21230/16:00305157 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.comnet.2016.06.011" target="_blank" >http://dx.doi.org/10.1016/j.comnet.2016.06.011</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.comnet.2016.06.011" target="_blank" >10.1016/j.comnet.2016.06.011</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Multidimensional Cloud Latency Monitoring and Evaluation

Popis výsledku v původním jazyce

Measuring or evaluating performance of a Cloud service is a non-trivial and highly ambiguous task. We focus on Cloud-service latency from the user’s point of view, and, to this end, utilize the multidimensional latency measurements obtained using an in-house designed active-probing platform, CLAudit, deployed across PlanetLab and Microsoft Azure datacenters. The multiple geographic Vantage Points, multiple protocol layers and multiple datacenter locations of CLAudit measurements allow us to pinpoint with great precision if, where and what kind of a particular latency-generating event has happened. We analyze and interpret measurements over two one-month time-intervals, one in 2013 and one in 2016. As these traces are large, an automated interpretation has been appended to the data-capture process. In summary, we demonstrate the utility of the multidimensional approach and document the differences in the measured Cloud-services latency over time. Our measurements data is publicly available and we encourage the research community to use it for verification and further studies.

Název v anglickém jazyce

Multidimensional Cloud Latency Monitoring and Evaluation

Popis výsledku anglicky

Measuring or evaluating performance of a Cloud service is a non-trivial and highly ambiguous task. We focus on Cloud-service latency from the user’s point of view, and, to this end, utilize the multidimensional latency measurements obtained using an in-house designed active-probing platform, CLAudit, deployed across PlanetLab and Microsoft Azure datacenters. The multiple geographic Vantage Points, multiple protocol layers and multiple datacenter locations of CLAudit measurements allow us to pinpoint with great precision if, where and what kind of a particular latency-generating event has happened. We analyze and interpret measurements over two one-month time-intervals, one in 2013 and one in 2016. As these traces are large, an automated interpretation has been appended to the data-capture process. In summary, we demonstrate the utility of the multidimensional approach and document the differences in the measured Cloud-services latency over time. Our measurements data is publicly available and we encourage the research community to use it for verification and further studies.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Computer Networks

ISSN

1389-1286

e-ISSN

—

Svazek periodika

107

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

17

Strana od-do

104-120

Kód UT WoS článku

000385328600009

EID výsledku v databázi Scopus

2-s2.0-84991800844