Systematic methodology for exploration of performance - Energy trade-offs in network applications using Dynamic Data Type refinement

Modern network applications require high performance and consume a lot of energy. Their inherent dynamic nature makes the dynamic memory subsystem a critical contributing factor to the overall energy consumption and to the execution time performance. This paper presents a novel, systematic methodology for generating performance-energy trade-offs by implementing optimal Dynamic Data Types, finely tuned and refined for network applications. Our systematic methodology is supported by a new, fully automated tool.We assess the effectiveness of the proposed approach in four representative, reallife case studies and provide significant energy savings and performance improvements compared to the original implementations. 2007 Elsevier B.V. All rights reserved.