This paper focuses on devising a configurable resource management technique for use in clouds for processing batches of MapReduce jobs associated with Service Level Agreements (SLAs). The proposed technique permits cloud service providers to make resource management decisions which consider client quality of service requirements, system performance, and energy consumption which directly affects data center operation costs. This research models the resource management problem as an optimization problem using Constraint Programming (CP). A simulation-based performance analysis that demonstrates the effectiveness of the approach is provided.

Additional Metadata
Keywords Constraint Programming, Energy management, MapReduce with deadlines, Resource management on clouds
Persistent URL dx.doi.org/10.1109/CloudCom.2016.0041
Conference 8th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2016
Citation
Gregory, A. (Adam), & Majumdar, S. (2017). A configurable energy aware resource management technique for optimization of performance and energy consumption on clouds. In Proceedings of the International Conference on Cloud Computing Technology and Science, CloudCom (pp. 184–192). doi:10.1109/CloudCom.2016.0041