Volume 4, Issue 2, April 2016, Pages 116 - 126
IntegrityMR: Exploring Result Integrity Assurance Solutions for Big Data Computing Applications
Authors
Yongzhi Wang, Jinpeng Wei, Mudhakar Srivatsa, Yucong Duan, Wencai Du
Corresponding Author
Yongzhi Wang
Available Online 1 April 2016.
- DOI
- 10.2991/ijndc.2016.4.2.5How to use a DOI?
- Keywords
- Big Data; MapReduce; Integrity Assurance; Cloud Computing
- Abstract
Large-scale adoption of MapReduce applications on public clouds is hindered by the lack of trust on the participating virtual machines deployed on the public cloud. In this paper, we propose IntegrityMR, a multi-public clouds architecture-based solution, which performs the MapReduce-based result integrity check techniques at two alternative layers: the task layer and the application layer. Our experimental results show that solutions in both layers offer a high result integrity but non-negligible performance overheads.
- Copyright
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Yongzhi Wang AU - Jinpeng Wei AU - Mudhakar Srivatsa AU - Yucong Duan AU - Wencai Du PY - 2016 DA - 2016/04/01 TI - IntegrityMR: Exploring Result Integrity Assurance Solutions for Big Data Computing Applications JO - International Journal of Networked and Distributed Computing SP - 116 EP - 126 VL - 4 IS - 2 SN - 2211-7946 UR - https://doi.org/10.2991/ijndc.2016.4.2.5 DO - 10.2991/ijndc.2016.4.2.5 ID - Wang2016 ER -