Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Cluster Computing
Erschienen in: Cluster Computing 3/2017

28.11.2016

Real-time data replication strategy for data grids

verfasst von: Junsang Kim, Youngkyun Kim, Changho Jeon

Erschienen in: Cluster Computing | Ausgabe 3/2017

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Current replication strategies update replicas by analyzing the data access pattern for a certain period of time. Therefore, the access latency temporarily increases due to delayed responses to changing data access pattern during the interval of updating replicas. Thus, we propose a real-time data replication strategy that can update a replica by reflecting changes in the data access patterns in real time to solve this problem. The proposed replication strategy introduces a priority value (PV) as a criterion to generate and delete replicas in real time. The PV is calculated based on the previous data access patterns and is updated in real time. We perform simulations to evaluate the performance of the proposed replication strategy by comparing it with the popular file replicate first algorithm (PFRF). The simulation results show that the average job execution time of the proposed strategy is shorter than that of the PFRF by 34.0–38.0%.
Vorheriger Artikel Energy aware scheduling model and online heuristics for stencil codes on heterogeneous computing architectures
Nächster Artikel Connected components of big graphs in fixed MapReduce rounds

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Literatur
1.
Tos, U., Mokadem, R., Hameurlain, A., Ayav, T., Bora, S.: Dynamic replication strategies in data grid systems: a survey. J. Supercomput. 71(11), 4116–4140 (2015)CrossRef
2.
Mokadem, R., Hameurlain, A.: Data replication strategies with performance objective in data grid systems: a survey. Int. J. Grid Util. Comput. 6(1), 30–46 (2014)CrossRef
3.
Amjad, T., Sher, M., Daud, A.: A survey of dynamic replication strategies for improving data availability in data grids. Future Gener. Comput. Syst. 28(2), 337–349 (2012)CrossRef
4.
Mansouri, N., Dastghaibyfard, G.H.: Job scheduling and dynamic data replication in data grid environment. J. Supercomput. 64(1), 204–225 (2013)CrossRef
5.
Wang, L., von Laszewski, G., Tao, J., Kunze, M.: Virtual data system on distributed virtual machines in computational grids. IJAHUC 6(4), 194–204 (2010)CrossRef
6.
Chen, D., Wang, L., Wu, X., Chen, J., Khan, S.U., Kolodziej, J., Tian, M., Huang, F., Liu, W.: Hybrid modelling and simulation of huge crowd over a hierarchical Grid architecture. Future Gener. Comput. Syst. 29(5), 1309–1317 (2013)CrossRef
7.
Koodziej, J., Khan, S.U., Wang, L., Byrski, A., Min-Allah, N., Madani, S.A.: Hierarchical genetic-based grid scheduling with energy optimization. Clust. Comput. 16(3), 591–609 (2013)CrossRef
8.
Childers, L., T. Disz, R. Olson, M.E. Papka, R. Stevens and T. Udeshi: Access grid: immersive group-to-group collaborative visualization. In: Proceedings of 4th International Immersive Projection Technology Workshop (2000)
9.
Grace, R.K., Manimegalai, R.: Dynamic replica placement and selection strategies in data grids—a comprehensive survey. J. Parallel Distrib. Comput. 74(2), 2099–2108 (2014)CrossRef
10.
Dayyani, S., Khayyambashi, M.: A comparative study of replication techniques in grid computing systems. Int. J. Comput. Sci. Inf. Secur. 11(9), 64–73 (2013)
11.
Ma, J., Liu, W., Glatard, G.: A classification of file placement and replication methods on grids. Future Gener. Comput. Syst. 29(6), 1395–1406 (2013)CrossRef
12.
Lee, M.C., Leu, F.Y., Chen, Y.P.: PFRF: an adaptive data replication algorithm based on star-based data grids. Future Gener. Comput. Syst. 28(7), 1045–1057 (2012)CrossRef
13.
Chang, R.S., Chang, H.P.: A dynamic data replication strategy using access weights in data grids. J. Supercomput. 45(3), 277–295 (2008)MathSciNetCrossRef
14.
15.
Ranganathan, K., Foster, I.: Simulation studies of computation and data scheduling algorithms for data grids. J. Grid Comput. 1(1), 53–62 (2003)CrossRef
16.
Tang, M., Lee, B.S., Yeo, C.K., Tang, X.: Dynamic replication algorithms for the multi-tier data grid. Future Gener. Comput. Syst. 21(5), 775–790 (2005)CrossRef
17.
Khanli, L.M., Isazadeh, A., Shishavan, T.N.: PHFS: a dynamic replication method, to decrease access latency in the multi-tier data grid. Future Gener. Comput. Syst. 27(3), 233–244 (2011)CrossRef
18.
Bsoul, M., Alsarhan, A., Otoom, A., Hammad, M., Al-Khasawneh, A.: A dynamic replication strategy based on categorization for data grid. Multiagent Grid Syst. 10(2), 109–118 (2014)CrossRef
19.
Chang, R.S., Chang, J.S., Lin, S.Y.: Job scheduling and data replication on data grids. Future Gener. Comput. Syst. 23(7), 846–860 (2007)
20.
Park, S., Kim, J., Ko, Y., Yoon, W.: Dynamic data replication strategy based on internet hierarchy. In: Proceedings of 2nd International Workshop on Grid and Cooperative Computing (GCC03) (2003)
21.
Perez, J.M., Garcia-Carballeira, F., Carretero, J., Calderon, A., Fernandez, J.: Branch replication scheme: a new model for data replication in large scale data grids. Future Gener. Comput. Syst. 26(1), 12–20 (2010)CrossRef
22.
Sashi, K., Thanamani, A.S.: Dynamic replication in a data grid using a modified BHR region based algorithm. Future Gener. Comput. Syst. 27(2), 202–210 (2011)CrossRef
23.
Vashisht, P., Kumar, R., Sharma, A.: Efficient dynamic replication algorithm using agent for data grid. Sci. World J. Article ID 767016 (2014)
24.
Mansouri, N., Dastghaibyfard, G.H., Mansouri, E.: Combination of data replication and scheduling algorithm for improving data availability in data grids. J. Netw. Comput. Appl. 36(2), 711–722 (2013)CrossRef
25.
Mansouri, N., Dastghaibyfard, G.H.: Enhanced dynamic hierarchical replication and weighted scheduling strategy in data grid. J. Parallel Distrib. Comput. 73(4), 534–543 (2013)CrossRef
26.
Mansouri, N., Dastghaibyfard, G.H.: A dynamic replica management strategy in data grid. J. Netw. Comput. Appl 36(2), 1297–1303 (2012)CrossRef
27.
Metz, C.: Interconnecting ISP networks. IEEE Internet Comput. 5, 74–80 (2001)CrossRef
28.
Sulistio, A., Cibej, U., Venugopal, S., Robic, B., Buyya, R.: A toolkit for modelling and simulating data grids: an extension to GridSim. Pract. Exp. 20(13), 1591–1609 (2008)CrossRef
29.
30.
Metadaten
Titel
Real-time data replication strategy for data grids
verfasst von
Junsang Kim
Youngkyun Kim
Changho Jeon
Publikationsdatum
28.11.2016
Verlag
Springer US
Erschienen in
Cluster Computing / Ausgabe 3/2017
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-016-0697-z

Weitere Artikel der Ausgabe 3/2017

Cluster Computing 3/2017 Zur Ausgabe

OriginalPaper

Energy-efficient and QoS-aware model based resource consolidation in cloud data centers

OriginalPaper

PB-MII: replacing static RSUs with public buses-based mobile intermediary infrastructure in urban VANET-based clouds

OriginalPaper

A low-latency storage stack for fast storage devices

OriginalPaper

Enhanced speaker verification using an adaptive multiple low-rank representation based on the modified adaptive Gaussian mixture model framework

OriginalPaper

Predictive communication modeling for HPC applications

OriginalPaper

Spectral-spatial multi-feature classification of remote sensing big data based on a random forest classifier for land cover mapping

Premium Partner

    Bildnachweise