Worst-Case Energy Consumption Analysis for Energy-Constrained Embedded Systems
暂无分享,去创建一个
Tobias Distler | Wolfgang Schröder-Preikschat | Rüdiger Kapitza | Timo Hönig | Heiko Janker | Peter Wägemann
[1] Giuseppe Lipari,et al. Speed modulation in energy-aware real-time systems , 2005, 17th Euromicro Conference on Real-Time Systems (ECRTS'05).
[2] Marcus Völp,et al. Has energy surpassed timeliness? Scheduling energy-constrained mixed-criticality systems , 2014, 2014 IEEE 19th Real-Time and Embedded Technology and Applications Symposium (RTAS).
[3] No License,et al. Intel ® 64 and IA-32 Architectures Software Developer ’ s Manual Volume 3 A : System Programming Guide , Part 1 , 2006 .
[4] James E. Baker,et al. Reducing Bias and Inefficienry in the Selection Algorithm , 1987, ICGA.
[5] Simon J. Hollis,et al. Identifying Compiler Options to Minimize Energy Consumption for Embedded Platforms , 2013, Comput. J..
[6] Paul S. Wang,et al. Chains of recurrences—a method to expedite the evaluation of closed-form functions , 1994, ISSAC '94.
[7] Dawson R. Engler,et al. KLEE: Unassisted and Automatic Generation of High-Coverage Tests for Complex Systems Programs , 2008, OSDI.
[8] Gernot Heiser,et al. Trickle: Automated infeasible path detection using all minimal unsatisfiable subsets , 2014, 2014 IEEE 19th Real-Time and Embedded Technology and Applications Symposium (RTAS).
[9] John H. Holland,et al. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .
[10] Peter P. Puschner,et al. Computing Maximum Task Execution Times — A Graph-Based Approach , 2004, Real-Time Systems.
[11] Vikram S. Adve,et al. LLVM: a compilation framework for lifelong program analysis & transformation , 2004, International Symposium on Code Generation and Optimization, 2004. CGO 2004..
[12] Jakob Engblom,et al. The worst-case execution-time problem—overview of methods and survey of tools , 2008, TECS.
[13] Raimund Kirner,et al. Obstacles in Worst-Case Execution Time Analysis , 2008, 2008 11th IEEE International Symposium on Object and Component-Oriented Real-Time Distributed Computing (ISORC).
[14] Rüdiger Kapitza,et al. Proactive Energy-Aware Programming with PEEK , 2014, TRIOS.
[15] Jan Gustafsson,et al. The Mälardalen WCET Benchmarks: Past, Present And Future , 2010, WCET.
[16] Kang G. Shin,et al. Real-time dynamic voltage scaling for low-power embedded operating systems , 2001, SOSP.
[17] Kalyanmoy Deb,et al. A Comparative Analysis of Selection Schemes Used in Genetic Algorithms , 1990, FOGA.
[18] Raimund Kirner,et al. Measurement-Based Timing Analysis , 2008, ISoLA.
[19] Xianfeng Li,et al. Estimating the Worst-Case Energy Consumption of Embedded Software , 2006, 12th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS'06).
[20] Gerard J. M. Smit,et al. A mathematical approach towards hardware design , 2010, Dynamically Reconfigurable Architectures.
[21] George Candea,et al. The S2E Platform: Design, Implementation, and Applications , 2012, TOCS.
[22] Benedikt Huber,et al. Combined WCET analysis of bitcode and machine code using control-flow relation graphs , 2013, LCTES.
[23] Wolfgang Schröder-Preikschat,et al. The RTSC: Leveraging the Migration from Event-Triggered to Time-Triggered Systems , 2010, 2010 13th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing.
[24] Torsten Braun,et al. On the Accuracy of Software-Based Energy Estimation Techniques , 2011, EWSN.
[25] Hermann Härtig,et al. Measuring energy consumption for short code paths using RAPL , 2012, PERV.
[26] Jens Knoop,et al. WCET squeezing: on-demand feasibility refinement for proven precise WCET-bounds , 2013, RTNS '13.