Awan: Locality-aware resource manager for geo-distributed data-intensive applications

Albert Jonathan, Abhishek Chandra, Jon Weissman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

Today, many organizations need to operate on datathat is distributed around the globe. This is inevitable due to thenature of data that is generated in different locations such as videofeeds from distributed cameras, log files from distributed servers, and many others. Although centralized cloud platforms havebeen widely used for data-intensive applications, such systemsare not suitable for processing geo-distributed data due to highdata transfer overheads. An alternative approach is to use anEdge Cloud which reduces the network cost of transferringdata by distributing its computations globally. While the EdgeCloud is attractive for geo-distributed data-intensive applications, extending existing cluster computing frameworks to a wide-areaenvironment must account for locality. We propose Awan: anew locality-aware resource manager for geo-distributed dataintensiveapplications. Awan allows resource sharing betweenmultiple computing frameworks while enabling high localityscheduling within each framework. Our experiments with theNebula Edge Cloud on PlanetLab show that Awan achieves up toa 28% increase in locality scheduling which reduces the averagejob turnaround time by approximately 18% compared to existingcluster management mechanisms.

Original languageEnglish (US)
Title of host publicationProceedings - 2016 IEEE International Conference on Cloud Engineering, IC2E 2016
Subtitle of host publicationCo-located with the 1st IEEE International Conference on Internet-of-Things Design and Implementation, IoTDI 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages32-41
Number of pages10
ISBN (Electronic)9781509019618
DOIs
StatePublished - Jun 1 2016
Event4th IEEE Annual International Conference on Cloud Engineering, IC2E 2016 - Berlin, Germany
Duration: Apr 4 2016Apr 8 2016

Publication series

NameProceedings - 2016 IEEE International Conference on Cloud Engineering, IC2E 2016: Co-located with the 1st IEEE International Conference on Internet-of-Things Design and Implementation, IoTDI 2016

Other

Other4th IEEE Annual International Conference on Cloud Engineering, IC2E 2016
Country/TerritoryGermany
CityBerlin
Period4/4/164/8/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

  • Cloud Computing
  • Data Intensive
  • Edge Cloud
  • Geo-distributed
  • Resource Management
  • Scheduling

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