Abstract
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 dispersed-data-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 lightweight Nebula architecture that enables distributed data-intensive 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.
Original language | English (US) |
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Title of host publication | Proceedings - 2014 IEEE International Conference on Cloud Engineering, IC2E 2014 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 57-66 |
Number of pages | 10 |
ISBN (Electronic) | 9781479937660 |
DOIs | |
State | Published - Sep 18 2014 |
Event | 2nd IEEE International Conference on Cloud Engineering, IC2E 2014 - Boston, United States Duration: Mar 10 2014 → Mar 14 2014 |
Publication series
Name | Proceedings - 2014 IEEE International Conference on Cloud Engineering, IC2E 2014 |
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Other
Other | 2nd IEEE International Conference on Cloud Engineering, IC2E 2014 |
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Country/Territory | United States |
City | Boston |
Period | 3/10/14 → 3/14/14 |
Bibliographical note
Publisher Copyright:© 2014 IEEE.
Keywords
- Cloud programming models and tools
- Data Intensive
- Edge
- Geo-distributed
- MapReduce
- Voluntary