FMonE: A Flexible Monitoring Solution at the Edge

Monitoring has always been a key element on ensuring the performance of complex distributed systems, being a first step to control quality of service, detect anomalies, or make decisions about resource allocation and job scheduling, to name a few. Edge computing is a new type of distributed computin...

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Main Authors: Álvaro Brandón, María S. Pérez, Jesus Montes, Alberto Sanchez
Format: Article
Language:English
Published: Hindawi-Wiley 2018-01-01
Series:Wireless Communications and Mobile Computing
Online Access:http://dx.doi.org/10.1155/2018/2068278
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spelling doaj-2e6f71f5c9fb445c8f2a4276bb52b9c42020-11-25T01:12:20ZengHindawi-WileyWireless Communications and Mobile Computing1530-86691530-86772018-01-01201810.1155/2018/20682782068278FMonE: A Flexible Monitoring Solution at the EdgeÁlvaro Brandón0María S. Pérez1Jesus Montes2Alberto Sanchez3Universidad Politecnica de Madrid, Madrid, SpainUniversidad Politecnica de Madrid, Madrid, SpainUniversidad Politecnica de Madrid, Madrid, SpainUniversidad Rey Juan Carlos Madrid, SpainMonitoring has always been a key element on ensuring the performance of complex distributed systems, being a first step to control quality of service, detect anomalies, or make decisions about resource allocation and job scheduling, to name a few. Edge computing is a new type of distributed computing, where data processing is performed by a large number of heterogeneous devices close to the place where the data is generated. Some of the differences between this approach and more traditional architectures, like cloud or high performance computing, are that these devices have low computing power, have unstable connectivity, and are geo-distributed or even mobile. All of these aforementioned characteristics establish new requirements for monitoring tools, such as customized monitoring workflows or choosing different back-ends for the metrics, depending on the device hosting them. In this paper, we present a study of the requirements that an edge monitoring tool should meet, based on motivating scenarios drawn from literature. Additionally, we implement these requirements in a monitoring tool named FMonE. This framework allows deploying monitoring workflows that conform to the specific demands of edge computing systems. We evaluate FMonE by simulating a fog environment in the Grid’5000 testbed and we demonstrate that it fulfills the requirements we previously enumerated.http://dx.doi.org/10.1155/2018/2068278
collection DOAJ
language English
format Article
sources DOAJ
author Álvaro Brandón
María S. Pérez
Jesus Montes
Alberto Sanchez
spellingShingle Álvaro Brandón
María S. Pérez
Jesus Montes
Alberto Sanchez
FMonE: A Flexible Monitoring Solution at the Edge
Wireless Communications and Mobile Computing
author_facet Álvaro Brandón
María S. Pérez
Jesus Montes
Alberto Sanchez
author_sort Álvaro Brandón
title FMonE: A Flexible Monitoring Solution at the Edge
title_short FMonE: A Flexible Monitoring Solution at the Edge
title_full FMonE: A Flexible Monitoring Solution at the Edge
title_fullStr FMonE: A Flexible Monitoring Solution at the Edge
title_full_unstemmed FMonE: A Flexible Monitoring Solution at the Edge
title_sort fmone: a flexible monitoring solution at the edge
publisher Hindawi-Wiley
series Wireless Communications and Mobile Computing
issn 1530-8669
1530-8677
publishDate 2018-01-01
description Monitoring has always been a key element on ensuring the performance of complex distributed systems, being a first step to control quality of service, detect anomalies, or make decisions about resource allocation and job scheduling, to name a few. Edge computing is a new type of distributed computing, where data processing is performed by a large number of heterogeneous devices close to the place where the data is generated. Some of the differences between this approach and more traditional architectures, like cloud or high performance computing, are that these devices have low computing power, have unstable connectivity, and are geo-distributed or even mobile. All of these aforementioned characteristics establish new requirements for monitoring tools, such as customized monitoring workflows or choosing different back-ends for the metrics, depending on the device hosting them. In this paper, we present a study of the requirements that an edge monitoring tool should meet, based on motivating scenarios drawn from literature. Additionally, we implement these requirements in a monitoring tool named FMonE. This framework allows deploying monitoring workflows that conform to the specific demands of edge computing systems. We evaluate FMonE by simulating a fog environment in the Grid’5000 testbed and we demonstrate that it fulfills the requirements we previously enumerated.
url http://dx.doi.org/10.1155/2018/2068278
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