Name
Abstract | ||
|---|---|---|
Large scale adoption of MapReduce computations on public clouds is hindered by the lack of trust on the participating virtual machines, because misbehaving worker nodes can compromise the integrity of the computation result. In this paper, we propose a novel MapReduce framework, Cross Cloud MapReduce (CCMR), which overlays the MapReduce computation on top of a hybrid cloud: the master that is in control of the entire computation and guarantees result integrity runs on a private and trusted cloud, while normal workers run on a public cloud. In order to achieve high accuracy, CCMR proposes a result integrity check scheme on both the map phase and the reduce phase, which combines random task replication, random task verification, and credit accumulation, and CCMR strives to reduce the overhead by reducing cross-cloud communication. We implement our approach based on Apache Hadoop MapReduce and evaluate our implementation on Amazon EC2. Both theoretical and experimental analysis show that our approach can guarantee high result integrity in a normal cloud environment while incurring non-negligible performance overhead (e.g., when 16.7% workers are malicious, CCMR can guarantee at least 99.52% of accuracy with 33.6% of overhead when replication probability is 0.3 and the credit threshold is 50). |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/CLOUD.2013.118 | IEEE CLOUD |
Keywords | Field | DocType |
computation result,trusted cloud,mapreduce,result integrity check,credit accumulation,random task verification,reduce phase,hybrid cloud,mapreduce computation,virtual machines,novel mapreduce framework,trusted computing,task replication,apache hadoop mapreduce,mapreduce computations,guarantees result integrity,integrity assurance,normal cloud environment,cross cloud mapreduce,hybrid clouds,ccmr,map phase,public clouds,result integrity check scheme,high result integrity,cloud computing,private cloud,public cloud,replication probability | Trusted Computing,Virtual machine,Computer science,Overlay,Operating system,Cloud computing,Distributed computing,Computation | Conference |
ISSN | ISBN | Citations |
2159-6182 | 978-0-7695-5028-2 | 8 |
PageRank | References | Authors |
0.48 | 8 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yongzhi Wang | 1 | 13 | 1.95 |
| Jinpeng Wei | 2 | 221 | 20.22 |
| Mudhakar Srivatsa | 3 | 1084 | 77.97 |