Stammdaten

Titel: M3AT: Monitoring Agents Assignment Model for Data-Intensive Applications
Untertitel:
Kurzfassung:

Nowadays, massive amounts of data are acquired, transferred, and analyzed nearly in real-time by utilizing a large number of computing and storage elements interconnected through high-speed communication networks. However, one issue that still requires research effort is to enable efficient monitoring of applications and infrastructures of such complex systems. In this paper, we introduce a Integer Linear Programming (ILP) model called M3AT for optimised assignment of monitoring agents and aggregators on large-scale computing systems. We identified a set of requirements from three representative data-intensive applications and exploited them to define the model’s input parameters. We evaluated the scalability of M3AT using the Constraint Integer Programing (SCIP) solver with default configuration based on synthetic data sets. Preliminary results show that the model provides optimal assignments for systems composed of up to 200 monitoring agents while keeping the number of aggregators constant and demonstrates variable sensitivity with respect to the scale of monitoring data aggregators and limitation policies imposed.

Schlagworte: Monitoring systems, high performance computing, aggregation, systems control, data-intensive systems, generalized assignment problem, SCIP optimization suite
Publikationstyp: Beitrag in Proceedings (Autorenschaft)
Erscheinungsdatum: 14.05.2020 (Online)
Erschienen in: PDP 2020 Proceedings of the 28th Euromicro International Conference on Parallel, Distributed and Network-Based Processing
PDP 2020 Proceedings of the 28th Euromicro International Conference on Parallel, Distributed and Network-Based Processing
zur Publikation
 ( IEEE; )
Titel der Serie: -
Bandnummer: -
Erstveröffentlichung: Ja
Version: -
Seite: S. 72 - 79

Versionen

Keine Version vorhanden
Erscheinungsdatum: 14.05.2020
ISBN (e-book):
  • 978-1-7281-6582-0
  • 978-1-7281-6583-7
eISSN: 2377-5750
DOI: http://dx.doi.org/10.1109/PDP50117.2020.00018
Homepage: https://ieeexplore.ieee.org/document/9092397
Open Access
  • Online verfügbar (nicht Open Access)

Zuordnung

Organisation Adresse
Fakultät für Technische Wissenschaften
 
Institut für Informationstechnologie
Universitaetsstr. 65-67
9020 Klagenfurt am Wörthersee
Österreich
   martina.steinbacher@aau.at
http://itec.aau.at/
zur Organisation
Universitaetsstr. 65-67
AT - 9020  Klagenfurt am Wörthersee

Kategorisierung

Sachgebiete
  • 1020 - Informatik
Forschungscluster Kein Forschungscluster ausgewählt
Peer Reviewed
  • Ja
Publikationsfokus
  • Science to Science (Qualitätsindikator: II)
Klassifikationsraster der zugeordneten Organisationseinheiten:
Arbeitsgruppen
  • Distributed Multimedia Systems

Kooperationen

Organisation Adresse
University of Calabria
Via Pietro Bucci
87036 Arcavacata di Rende
Italien - restliches Italien
Via Pietro Bucci
IT - 87036  Arcavacata di Rende
West-Universität Temeswar
Bulevardul Vasile Pârvan 4
300223 Timișoara
Rumänien
https://www.uvt.ro/en/
Bulevardul Vasile Pârvan 4
RO - 300223  Timișoara
Poznan Supercomputing and Networking Center
Polen
PL  
UNIVERSIDAD CARLOS III DE MADRID
Calle Madrid 126
28903 Getafe, Madrid
Spanien
Calle Madrid 126
ES - 28903  Getafe, Madrid

Beiträge der Publikation

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