Real-Time Fault Tolerance Task Scheduling Algorithm with Minimum Energy Consumption

  • Arvind Kumar
  • Bashir Alam
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 380)


In this paper, we propose a fault tolerance real-time task scheduling algorithm with energy minimization. A fault in a system can be recovered at runtime without participation of external agent. It maintains enough time redundancy so that task can be re-executed in presence of fault. It can be achieved by checkpointing policy which gives reliability in a system. For reliable fault tolerance in a system, optimal number of checkpoints is applied and save the system from complete re-execution. Energy minimization can be achieved by dynamic voltage scaling (DVS). In this paper, existing real-time scheduling algorithm has been modified for fault tolerance and energy minimization. To minimize energy consumption voltage level is adjusted with respect to deadline of the system and check the schedulability of test on each task. The worst-case execution time is associated with voltage level for each task. The result shows that energy consumption is reduced with maximum task scheduling in a system.


Real-time system Fault tolerance DVS Scheduling 


  1. 1.
    Dima, C., Girault, A., Lavarenne, C., Sorel, Y.: Off-line real-time fault-tolerant scheduling. In Euromicro Workshop on Parallel and Distributed Processing, Mantova, Italy, February 2001Google Scholar
  2. 2.
    Alam, B., Kumar, A.: A real time scheduling algorithm for tolerating single transient fault. Inf. Syst. Comput. Netw. (ISCON). In: 2014 International Conference on, pp. 11–14, 1–2 March 2014Google Scholar
  3. 3.
    Pradhan, D.K.: Fault Tolerance Computing: Theory and Techniques. Prentice Hall (1986)Google Scholar
  4. 4.
    Huang, K., Santinelli, L., Chen, J., Thiele, L., Buttazzo, G.: Adaptive dynamic power management for hard real-time systems. In: Proceedings of the IEEE Real-Time Systems Symposium (2009)Google Scholar
  5. 5.
    Zhang, Y., Chakrabarty, K.: Energy-aware adaptive checkpointing in embedded real-time systems. In: Proceedings of the DATE (2003)Google Scholar
  6. 6.
    Pillai, P., Shin, K.: Real-time dynamic voltage scaling for low-power embedded operating systems. In: Proceedings of the ACM Symposium on Operating Systems Principle (2001)Google Scholar
  7. 7.
    Liu, Y., Liang, H., Wu, K.: Scheduling for Energy Efficiency and Fault Tolerance in Hard Real Time Systems. 978-3-9810801-6-2/DATE10 © 2010 EDAA, pp. 1444–1449Google Scholar
  8. 8.
    Kumar, A., Alam, B.: Real time scheduling algorithm for fault tolerant and energy minimization. Issues Challenges Intell. Comput. Tech. (ICICT). In: 2014 International Conference on, pp. 356–360, 7–8 Feb 2014Google Scholar
  9. 9.
    Kumar, A., Yadav, R.S., Ranvijay, A.J.: Fault tolerance in real time distributed system. Int. J. Comput. Sci. Eng. (IJCSE) 3(2), 933–939 (2011)Google Scholar
  10. 10.
    Izosimov, V., Pop, P., Eles, P., Peng, Z.: Scheduling of fault-tolerant embedded systems with soft and hard timing constraints. In: Proceedings of the DATE (2008)Google Scholar
  11. 11.
    Woonseok, K., Dongkun, S., Han-Saem, Y., Jihong, K., Sang, M.L.: Performance comparison of dynamic voltage scaling algorithms for hard real-time systems. In: Proceedings of the Eighth IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS’02), pp. 219–228 (2002)Google Scholar
  12. 12.
    Melhem, R., Mosse, D., Elnozahy, E.: The interplay of power management and fault recovery in real-time systems. IEEE Trans. Comput. 53(2), 217–231 (2004)CrossRefGoogle Scholar

Copyright information

© Springer India 2016

Authors and Affiliations

  1. 1.Department of Computer Engineering, Faculty of Engineering and TechnologyJamia Millia IslamiaNew DelhiIndia

Personalised recommendations