Abstract
Energy consumption is certainly a major determinant for the success and deployment of embedded systems (ES). Unlike traditional ES, recent ones are more complex, open and interact with dynamic and uncertain environment. In this context, we presented the theoretical results of our flexible scheduling scheme aimed at minimizing energy consumption by using the Dynamic Voltage Scaling (DVS) technique and reusing the time savings that express the difference between the worst case time and the real execution time on a multiprocessor embedded architecture with uncertain data. We performed simulations under Matlab in order to evaluate the behavior of our proposed algorithm. These simulations have in particular confirmed the very good behavior of our proposed algorithm in terms of energy consumption with regard to periodic independent tasks executing on multiprocessor architecture.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Wolf, W.: Computers and Components Principles of Embedded Computing System Design. Morgan Kaufman Publishers, Burlington (2000)
Choi, H., Koo, Y., Park, S.: Modeling the power consumption of function-level code relocation for low-power embedded systems. Appl. Sci. 9(11), 2354 (2019)
Malewski, M., Cowell, D.M.J., Freear, S.: Reviewof battery powered embedded systems design for mission-critical low-power applications. Int. J. Electron. 105(6), 893–909 (2017)
Anuradha, P., Rallapalli, H., Narsimha, G.: Energy efficient scheduling algorithm for the multicore heterogeneous embedded architectures. Des. Autom. Embed. Syst. 22(1–2), 1–12 (2018)
Rohárik Vîlcu, D.M.: Optimal scheduling of tasks for CPU power consumption. Ph.D. thesis, Université Paris XII – Val de Marne (2004)
Mehalaine, R., Boutekkouk, F.: Fuzzy energy aware real time scheduling targeting mono-processor embedded architectures. In: CSOC 2016: 5th Computer Science On-line Conference 2016. Springer Series: Advances in Intelligent Systems and Computing - ISSN 2194, vol. 5357. pp. 81–91 (2016)
Smith, J.S.: Application Specific Integrated Circuits. Addision Wesley, Boston (1997)
Yao, F., Demers, A., Shenker, S.: A scheduling model for reduced CPU energy. In: Proceedings of the 36th Annual Symposium on Foundations of Computer Science, FOCS, Washington, DC, USA, pp. 374–382 (1995)
Kacem, F.: Algorithmes Exacts et Approchés pour des problèmes d’Ordonnancement et de Placement. Ph.D. thesis (2012)
Buttazzo, G.C., Lipari, G., Abeni, L., Caccamo, M.: Soft RealTime Systems: Predictability vs. Efficiency. Springer, Heidelberg (2005)
Pedram, M., Nazarian, S.: Thermal modeling, analysis and management in VLSI cicuits: principles and methods. Proc. IEEE 94(8), 1487–1501 (2006)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Mehalaine, R., Boutekkouk, F. (2020). Energy Consumption Reduction in Real Time Multiprocessor Embedded Systems with Uncertain Data. In: Silhavy, R. (eds) Artificial Intelligence and Bioinspired Computational Methods. CSOC 2020. Advances in Intelligent Systems and Computing, vol 1225. Springer, Cham. https://doi.org/10.1007/978-3-030-51971-1_4
Download citation
DOI: https://doi.org/10.1007/978-3-030-51971-1_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-51970-4
Online ISBN: 978-3-030-51971-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)