DocumentCode
2691837
Title
A Modified MapReduce Framework for Cloud Computing
Author
Zeng, Lingying ; Lin, Hao Wen
Author_Institution
Shenzhen Grad. Sch., Harbin Inst. of Technol., Shenzhen, China
fYear
2012
fDate
7-9 July 2012
Firstpage
277
Lastpage
280
Abstract
Due to the heterogeneous, opaqueness and dynamic nature of Cloud Computing, existing MapReduce approach is not suitable for perform Parallel Computing on the cloud. In this paper, we propose a modified MapReduce framework which extracts the physical network topology information from the Virtual Machine Monitor (VMM) feature of VMs, in order to exploit dynamic resource allocations, and hence enable effective Parallel Computing within the cloud environment.
Keywords
cloud computing; parallel processing; resource allocation; virtual machines; MapReduce framework; VMM; cloud computing; dynamic resource allocations; parallel computing; physical network topology information extraction; virtual machine monitor; Cloud computing; Computers; Data mining; Delay; Heart beat; Network topology; Topology; Cloud Computing; MapReduce; Parallel Computing; Virtual Machine;
fLanguage
English
Publisher
ieee
Conference_Titel
Computing, Measurement, Control and Sensor Network (CMCSN), 2012 International Conference on
Conference_Location
Taiyuan
Print_ISBN
978-1-4673-2033-7
Type
conf
DOI
10.1109/CMCSN.2012.67
Filename
6245866
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