DocumentCode :
3360589
Title :
A scheduling mechanism for multiple MapReduce jobs in a workflow application (position paper)
Author :
Yoo, Dongjin ; Sim, Kwang Mong
Author_Institution :
Multi-Agent & Cloud Comput. Syst. Lab., Gwangju Inst. of Sci. & Technol. (GIST), Gwangju, South Korea
fYear :
2012
fDate :
11-13 Jan. 2012
Firstpage :
405
Lastpage :
410
Abstract :
MapReduce is currently an attractive model for data intensive application due to easy interface of programming, high scalability and fault tolerance capability. It is well suited for applications requiring processing large data with distributed processing resources such as web data analysis, bio informatics, and high performance computing area. There are many studies of job scheduling mechanism in shared cluster for MapReduce. However there is a need for scheduling workflow service composed of multiple MapReduce tasks with precedence dependency in multiple processing nodes. The contribution of this paper is proposing a scheduling mechanism for a workflow service containing multiple MapReduce jobs. The workflow application has precedence dependency constraints among multiple tasks, represented as directed acyclic graph (DAG). Also, for less data transfer cost in limited bisection bandwidth, data dependency criterion should be considered for scheduling multiple map-reduce jobs in a workflow. The proposed scheduling mechanism provides 1) scheduling MapReduce tasks regarding precedence constraints and 2) pre-data placement method considering data dependency constraints for saving data transfer cost over network.
Keywords :
directed graphs; distributed processing; scheduling; software fault tolerance; Web data analysis; bio informatics; data intensive application; data transfer cost; directed acyclic graph; fault tolerance capability; high performance computing; high scalability; multiple MapReduce jobs; scheduling mechanism; workflow application; workflow service scheduling; Cloud computing; Computational modeling; Distributed databases; Fault tolerance; Fault tolerant systems; Processor scheduling; Synchronization; Cloud Computing; Data Intensive Computing; MapReduce; Scheduling; Workflow Application;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing, Communications and Applications Conference (ComComAp), 2012
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4577-1717-8
Type :
conf
DOI :
10.1109/ComComAp.2012.6154882
Filename :
6154882
Link To Document :
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