MONARCH: Gaining command on geo-distributed graph analytics

Anand Padmanabha Iyer, Aurojit Panda, Mosharaf Chowdhury, Aditya Akella, Scott Shenker, Ion Stoica

Research output: Contribution to conferencePaperpeer-review

Abstract

A number of existing and emerging application scenarios generate graph-structured data in a geo-distributed fashion. Although there is a lot of interest in distributed graph processing systems, none of them support geo-distributed graph processing. Geo-distributed analytics, on the other hand, has not focused on iterative workloads such as distributed graph processing. In this paper, we look at the problem of efficient geo-distributed graph analytics. We find that optimizing the iterative processing style of graph-parallel systems is the key to achieving this goal rather than extending existing geo-distributed techniques to graph processing. Based on this, we discuss our proposal on building MONARCH, the first system to our knowledge that focuses on geo-distributed graph processing. Our preliminary evaluation of MONARCH shows encouraging results.

Original languageEnglish (US)
StatePublished - 2018
Event10th USENIX Workshop on Hot Topics in Cloud Computing, HotCloud 2018 - Boston, United States
Duration: Jul 9 2018 → …

Conference

Conference10th USENIX Workshop on Hot Topics in Cloud Computing, HotCloud 2018
CountryUnited States
CityBoston
Period7/9/18 → …

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software

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