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Nebula: Distributed Edge Cloud for Data Intensive Computing.

Authors :
Jonathan, Albert
Ryden, Mathew
Oh, Kwangsung
Chandra, Abhishek
Weissman, Jon
Source :
IEEE Transactions on Parallel & Distributed Systems. Nov2017, Vol. 28 Issue 11, p3229-3242. 14p.
Publication Year :
2017

Abstract

Centralized cloud infrastructures have become the popular platforms for data-intensive computing today. However, they suffer from inefficient data mobility due to the centralization of cloud resources, and hence, are highly unsuited for geo-distributed data-intensive applications where the data may be spread at multiple geographical locations. In this paper, we present Nebula: a dispersed edge cloud infrastructure that explores the use of voluntary resources for both computation and data storage. We describe the lightweight Nebula architecture that enables distributed data-intensive computing through a number of optimization techniques including location-aware data and computation placement, replication, and recovery. We evaluate Nebula performance on an emulated volunteer platform that spans over 50 PlanetLab nodes distributed across Europe, and show how a common data-intensive computing framework, MapReduce, can be easily deployed and run on Nebula. We show Nebula MapReduce is robust to a wide array of failures and substantially outperforms other wide-area versions based on emulated existing systems. [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISSN :
10459219
Volume :
28
Issue :
11
Database :
Academic Search Index
Journal :
IEEE Transactions on Parallel & Distributed Systems
Publication Type :
Academic Journal
Accession number :
125562517
Full Text :
https://doi.org/10.1109/TPDS.2017.2717883