A Constraint Programming-Based Resource Management Technique for Processing MapReduce Jobs with SLAs on Clouds

Clouds that are rapidly gaining in popularity require an effective resource manager that can harness the power of the underlying resource pool, and provide resources on demand to its users. This paper focuses on resource management on clouds for workflow requests characterized by Service Level Agree...

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Bibliographic Details
Published in2014 43rd International Conference on Parallel Processing pp. 411 - 421
Main Authors Lim, Norman, Majumdar, Shikharesh, Ashwood-Smith, Peter
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2014
Subjects
Cloud computing
Computational modeling
MapReduce with deadlines
MapReduce with SLAs
matchmaking and scheduling on clouds
Open systems
Optimization
Programming
Resource management
resource management on clouds
Schedules
SLAs on clouds
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Summary:Clouds that are rapidly gaining in popularity require an effective resource manager that can harness the power of the underlying resource pool, and provide resources on demand to its users. This paper focuses on resource management on clouds for workflow requests characterized by Service Level Agreements (SLAs). Specifically, we devise a novel MapReduce constraint programming based resource manager (MRCP-RM) that can effectively perform matchmaking and scheduling of MapReduce jobs, each characterized by an SLA comprising an earliest start time, execution time, and an end-to-end deadline. Using discrete event simulation a performance evaluation of MRCP-RM is conducted for an open system subjected to a stream of job arrivals. The simulation results demonstrate the effectiveness of the resource manager and provide insights into system behaviour and performance.
ISSN:0190-3918
2332-5690
DOI:10.1109/ICPP.2014.50