Energy-Efficient Algorithm for Mixed-Criticality Systems in E-Learning Environment

Document Type : Original Article

Author

Department of Information and Communication Technology, Payame Noor University, Tehran, Iran. Email: sadeghzadeh1@gmail.com

10.5812/ijvlms.89300

Abstract

Background: Low-energy consumption is a vital concern in E-learning due to high-volume processing and the fact that mobile technologies are usually battery-operated devices. Methods: The method is simulated by developing a discrete-event simulation in C#. The validation of the proposed method is performed on generated task sets as used in similar work. The characteristic of randomly produced tasks is similar to the well-known techniques of task generation in mixed-criticality (MC) systems. Results: The simulation results show that energy consumption can be improved up to 23% in comparison to similar approaches. The most important factor for this satisfaction was the reservation times of critical tasks to further reduce the processor frequency. Conclusions: The internet of thing (IoT) is poised to be one of the most disruptive technologies in E-learning environment. The IoT is a kind of MC system that integrates multiple things with different criticalities into the same platform. Mobile technologies provide education to people through mobile devices. These devices are usually battery-operated and owing to high-volume processing, Low energy consumption becomes a vital concern in E-learning. Therefore, this paper was discussed about the MC system in general. Finally, the paper was proposed a scheduling technique to minimize the energy consumption of E-learning devices that use the IoT.

Keywords


Xu H, Li R, Zeng L, Li K, Pan C. Energy-efficient scheduling with reliability guarantee in embedded real-time systems. Sustain Comput Infor Syst. 2018;18:137–48. doi: 10.1016/j.suscom.2018.01.005.
Kopetz H. Real-time systems: design principles for distributed embedded applications. Springer Science & Business Media; 2011.
Baruah SK, Cucu-Grosjean L, Davis RI, Maiza C. Mixed criticality on multicore/manycore platforms (dagstuhl seminar 15121). Dagstuhl Seminar 15121. Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik; 2015.
Baruah SK, Bonifaci V, D’Angelo G, Li H, Marchetti-Spaccamela A, Megow N, et al. Scheduling real-time mixed-criticality jobs. IEEE Tran Comput. 2012;61(8):1140–52. doi: 10.1109/tc.2011.142.
Santy F, George L, Thierry P, Goossens J. Relaxing mixed-criticality scheduling strictness for task sets scheduled with FP. Real-Time Systems (ECRTS), 24th Euromicro Conference on 2012 Jul 11. IEEE; 2012. p. 155–65.
Baruah S, Bonifaci V, Dangelo G, Li H, Marchetti-Spaccamela A, van der Ster S, et al. The preemptive uniprocessor scheduling of mixedcriticality implicit-deadline sporadic task systems. Real-Time Systems (ECRTS), 24th Euromicro Conference on 2012 Jul 11. IEEE; 2012. p. 145–54.
Park T, Kim S. Dynamic scheduling algorithm and its schedulability analysis for certifiable dual-criticality systems. Embedded Software (EMSOFT), Proceedings of the International Conference on 2011 Oct 9. IEEE; 2011. 253 p.
Baruah S, Li H, Stougie L. Towards the design of certifiable mixedcriticality systems. Real-Time and Embedded Technology and Applications Symposium (RTAS), 16th IEEE 2010 Apr 12. IEEE; 2010. p. 13–22.
Niz D, Lakshmanan K, Rajkumar R. On the scheduling of mixedcriticality real-time task sets. Real-Time Systems Symposium, RTSS. 30th IEEE 2009 Dec 1. IEEE; 2009. p. 291–300.
Baruah S, Vestal S. Schedulability analysis of sporadic tasks with multiple criticality specifications. Real-Time Systems. ECRTS’08. Euromicro Conference on 2008 Jul 2. IEEE; 2008. p. 147–55.
Su H, Zhu D, Brandt S. An elastic mixed-criticality task model and early-release EDF scheduling algorithms. ACM Trans Desig Autom Electron Syst. 2016;22(2):1–25. doi: 10.1145/2984633.
Su H, Zhu D. An elastic mixed-criticality task model and its scheduling algorithm. Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE; 2013. p. 147–52.
Huang P, Yang H, Thiele L. On the scheduling of fault-tolerant mixed-criticality systems. Design Automation Conference (DAC), 51st ACM/EDAC/IEEE. IEEE; 2014. p. 1–6.
Ekberg P, Yi W. Bounding and shaping the demand of generalized mixed-criticality sporadic task systems. Real-Time Syst. 2013;50(1):48–86. doi: 10.1007/s11241-013-9187-z.
Su H, Guan N, Zhu D. Service guarantee exploration for mixedcriticality systems. 2014 IEEE 20th International Conference on Embedded and Real-Time Computing Systems and Applications. IEEE; 2014. p. 1–10.
Schreiner S, Gruttner K, Rosinger S, Rettberg A. Autonomous flight control meets custom payload processing: A mixed-critical avionics architecture approach for civilian UAVs. Object/Component/Service-Oriented Real-Time Distributed Computing (ISORC), IEEE 17th International Symposium on 2014 Jun 10. 2014. p. 348–57.
Vestal S. Preemptive Scheduling of Multi-criticality Systems with Varying Degrees of Execution Time Assurance. Real-Time Systems Symposium. RTSS 2007. 28th IEEE International 2007 Dec 3. IEEE; 2007. p. 239–43.
Legout V, Jan M, Pautet L. Scheduling algorithms to reduce the static energy consumption of real-time systems. Real-Time Syst. 2015;51(2):153–91. doi: 10.1007/s11241-014-9207-7.
Marwedel P. Embedded system design. 1. New York: Springer; 2006.
Cheng D, Zhou X, Lama P, Ji M, Jiang C. Energy Efficiency Aware Task Assignment with DVFS in Heterogeneous Hadoop Clusters. IEEE Trans Parallel Distrib Systems. 2018;29(1):70–82. doi: 10.1109/tpds.2017.2745571.
Weste NH, Eshraghian K. Principles of CMOS VLSI design: A systems perspective. California: Addision-Wesley Publishing; 1994.
Bambagini M, Marinoni M, Aydin H, Buttazzo G. Energy-Aware Scheduling for Real-Time Systems. ACM Tran Embed Comput Syst. 2016;15(1):1–34. doi: 10.1145/2808231.
Xie G, Zeng G, Xiao X, Li R, Li K. Energy-efficient scheduling algorithms for real-time parallel applications on heterogeneous distributed embedded systems. IEEE Trans Parallel Distrib Systems. 2017;28(12):3426–42. doi: 10.1109/tpds.2017.2730876.
Huang P, Kumar P, Giannopoulou G, Thiele L. Energy efficient DVFS scheduling for mixed-criticality systems. Proceedings of the 14th International Conference on Embedded Software. ACM; 2014. p. 1–10.
Volp M, Hahnel M, Lackorzynski A. Has energy surpassed timeliness? Scheduling energy-constrained mixed-criticality systems. Real-Time and Embedded Technology and Applications Symposium (RTAS), IEEE 20th. IEEE; 2014. p. 275–84.
Taherin A, Salehi M, Ejlali A. Reliability-aware energy management in mixed-criticality systems. IEEE Tran Sustainable Comput. 2018;3(3):195–208. doi: 10.1109/tsusc.2018.2801123.
Legout V, Jan M, Pautet L. Mixed-criticality multiprocessor real-time systems: Energy consumption vs deadline misses. First Workshop on Real-Time Mixed Criticality Systems (ReTiMiCS). 2013. p. 1–6.
Narayana S, Huang P, Giannopoulou G, Thiele L, Prasad RV. Exploring energy saving for mixed-criticality systems on multi-cores. IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS). IEEE; 2016. p. 1–12.
Han JJ, Tao X, Zhu D, Aydin H, Shao Z, Yang LT. Multicore mixed criticality systems: Partitioned scheduling and utilization bound. IEEE Tran Comput Aided Des Integr Circ Syst. 2018;37(1):21–34. doi: 10.1109/tcad.2017.2697955.
Li Z, Guo C, Hua X, Ren S. Reliability guaranteed energy minimization on mixed-criticality systems. J Syst Softw. 2016;112:1–10. doi: 10.1016/j.jss.2015.10.029.
Moghaddas V, Fazeli M, Patooghy A. Reliability-oriented scheduling for static-priority real-time tasks in standby-sparing systems. Microprocess Microsy. 2016;45:208–15. doi: 10.1016/j.micpro.2016.05.005.
Baruah S, Chattopadhyay B, Li H, Shin I. Mixed-criticality scheduling on multiprocessors. Real-Time Syst. 2013;50(1):142–77. doi: 10.1007/s11241-013-9184-2.
Gu C, Guan N, Deng Q, Yi W. Partitioned mixed-criticality scheduling on multiprocessor platforms. Proceedings of the conference on Design, Automation & Test in Europe. European Design and Automation Association; 2014. 292 p.
Bini E, Buttazzo GC. Biasing effects in schedulability measures. 16th Euromicro Conference on Real-Time Systems,. 2004. p. 196–203.