publication . Other literature type . Conference object . 2017

Chrysaor: Fine-Grained, Fault-Tolerant Cloud-Of-Clouds Mapreduce

Costa, Pedro A. R. S.; Ramos, Fernando M. V.; Correia, Miguel;
Open Access
  • Published: 14 May 2017
  • Publisher: Zenodo
Abstract
MapReduce is a framework for processing large data sets much used in the context of cloud computing. MapReduce implementations like Hadoop can tolerate crashes and file corruptions, but not arbitrary faults. Unfortunately, there is evidence that arbitrary faults do occur and can affect the correctness of MapReduce job executions. Furthermore, many outages of major cloud offerings have been reported, raising concerns about the dependence on a single cloud. In this paper we propose a novel execution system that allows to scale out MapReduce computations to a cloud-of-clouds and tolerate arbitrary faults, malicious faults, and cloud outages. Our system, Chrysaor, i...
Funded by
EC| SUPERCLOUD
Project
SUPERCLOUD
USER-CENTRIC MANAGEMENT OF SECURITY AND DEPENDABILITY IN CLOUDS OF CLOUDS
  • Funder: European Commission (EC)
  • Project Code: 643964
  • Funding stream: H2020 | RIA
Download fromView all 3 versions
Zenodo
Other literature type . 2017
Provider: Datacite
Zenodo
Other literature type . 2017
Provider: Datacite
ZENODO
Conference object . 2017
Provider: ZENODO
Powered by OpenAIRE Research Graph
Any information missing or wrong?Report an Issue