Nebula: Distributed edge cloud for data-intensive computing

Mathew Ryden, Kwangsung Oh, Abhishek Chandra, Jon Weissman
2014 2014 International Conference on Collaboration Technologies and Systems (CTS)  
Centralized cloud infrastructures have become the de-facto platform 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 disperseddata-intensive applications, where the data may be spread at multiple geographical locations. In this paper, we present Nebula: a dispersed cloud infrastructure that uses voluntary edge resources for both computation and data storage. We describe the
more » ... htweight Nebula architecture that enables distributed dataintensive computing through a number of optimizations including location-aware data and computation placement, replication, and recovery. We evaluate Nebula's 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 a BOINC like model.
doi:10.1109/cts.2014.6867613 dblp:conf/cts/RydenOCW14 fatcat:aswwg5wi3nbdnpzhfkyujmfx7y