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
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;
Conference_Titel :
Computing, Measurement, Control and Sensor Network (CMCSN), 2012 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4673-2033-7
DOI :
10.1109/CMCSN.2012.67
