CLOUDLET: towards mapreduce implementation on virtual machines

Authors:
Shadi Ibrahim;Hai Jin;Bin Cheng;Haijun Cao;Song Wu;Li Qi
Affiliations:
Huazhong University of Science and Technology, Wuhan, China;Huazhong University of Science and Technology, Wuhan, China;Huazhong University of Science and Technology, Wuhan, China;Huazhong University of Science and Technology, Wuhan, China;Huazhong University of Science and Technology, Wuhan, China;China Development Bank, Beijing, China
Venue:
Proceedings of the 18th ACM international symposium on High performance distributed computing
Year:
2009

Citing 4
Cited 8

Diagnosing performance overheads in the xen virtual machine environment

Proceedings of the 1st ACM/USENIX international conference on Virtual execution environments
A case for high performance computing with virtual machines

Proceedings of the 20th annual international conference on Supercomputing
MapReduce: simplified data processing on large clusters

OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Improving MapReduce performance in heterogeneous environments

OSDI'08 Proceedings of the 8th USENIX conference on Operating systems design and implementation

Evaluating MapReduce on Virtual Machines: The Hadoop Case

CloudCom '09 Proceedings of the 1st International Conference on Cloud Computing
MR-scope: a real-time tracing tool for MapReduce

Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
Variable-sized map and locality-aware reduce on public-resource grids

Future Generation Computer Systems
A Load-Driven Task Scheduler with Adaptive DSC for MapReduce

GREENCOM '11 Proceedings of the 2011 IEEE/ACM International Conference on Green Computing and Communications
MARIANE: MApReduce Implementation Adapted for HPC Environments

GRID '11 Proceedings of the 2011 IEEE/ACM 12th International Conference on Grid Computing
Variable-Sized map and locality-aware reduce on public-resource grids

GPC'10 Proceedings of the 5th international conference on Advances in Grid and Pervasive Computing
Maestro: Replica-Aware Map Scheduling for MapReduce

CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
G-Hadoop: MapReduce across distributed data centers for data-intensive computing

Future Generation Computer Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

The existing MapReduce framework in virtualized environment suffers from poor performance, due to the heavy overhead of I/O virtualization, and management difficulty for storage and computation. To address the problems, we propose Cloudlet, a novel MapReduce framework on virtual machines. The aim of Cloudlet design is to overcome the overhead of VM while benefiting of the other features of VM (i.e. management and reliability issues).