Deriving a Fault Resilience Metric for Real-Time Systems

• Flávia Maristela Nascimento IFBA
• George Lima UFBA
• Verônica Cadena Lima UFBA

DOI: https://doi.org/10.5753/wtf.2009.23139

Resumo

Most real-time systems are required to comply with strict time and logical requirements even in the presence of faults. Although scheduling policies and schedulability analyses have been extended to deal with fault tolerance, not much attention has been given to measuring the fault resilience of such systems. Usually, worst-case error patterns are artificially assumed and system correctness is checked. However, such patterns do not represent the capacity of the system to tolerate faults, nor consider the overall system behavior in the presence of faults. In this paper we define a fault resilience metric and present a simulation-based analysis. Then we show how simulation results can be statistically analyzed.

Referências

Avizienis, A., Laprie, J.-C., Landwehr, C., and Randell, B. (2004). Basic concepts and taxonomy of dependable and secure computing. IEEE Transactions on Dependable and Secure Computing, 1(1):11–33.

Aydin, H. (2007). Exact fault-sensitive feasibility analysis of real-time tasks. IEEE Transactions on Computers, 56(10):1372 – 1386.

Broster, I. and Burns, A. (2004). Random Arrivals in Fixed Priority Analysis. In Proc. of the 1st International Workshop on Probabilistic Analysis Techniques for Real-time and Embedded Systems.

Burns, A., Bernat, G., and Broster, I. (2003). A Probabilistic Framework for Schedulability Analysis. In Proc. of the Third International Conference on Embedded Software, pages 1 – 15.

Burns, A., Davis, R., and Punnekkat, S. (1996). Feasibility Analysis of Fault-Tolerant Real-Time Task Sets. In Proc. of the 8th Euromicro Conference on Real-Time Systems, pages 29 – 33.

Burns, A., Punnekkat, S., Strigini, L., and Wright, D. R. (1999). Probabilistic Scheduling Guarantees for Fault-Tolerant Real-Time Systems. In Proc. of the International Working Conference on Dependable Computing for Critical Applications, pages 361 – 378.

Burns, A. and Wellings, A. J. (2001). Real-Time Systems and Programming Languages. Addison-Wesley, 3rd edition.

Ghosh, S., Melhem, R., and Mossé, D. (1995). Enhancing Real-Time Schedules to Tolerate Transient Faults. In Proc. of the 16th IEEE Real-time Systems Symposium, pages 120–129.

Ghosh, S., Melhem, R., Mossé, D., and Sarma, J. S. (1998). Fault-tolerant rate monotonic scheduling. Real-Time Systems, 15(2):149–181.

Han, C., Shin, K., and Wu, J. (2003). A fault-tolerant scheduling algorithm for real-time periodic tasks with possible software faults. IEEE Transactions on Computers, 52(3):362–372.

Huselius, J., Kraft, J., Hansson, H., and Punnekkat, S. (2007). Evaluating the Quality of Models Extracted from Embedded Real-Time Software. In Proc. of the 14th Annual IEEE International Conference and Workshops on the Engineering of Computer-Based Systems, pages 577–585.

Liberato, F., Melhem, R., and Mossé, D. (2000). Tolerance to multiple transient faults for aperiodic tasks in hard real-time systems. IEEE Transactions on Computers, 49(9):906–914.

Lima, G. and Burns, A. (2003). An optimal fixed-priority assignment algorithm for supporting fault-tolerant hard real-time systems. IEEE Transactions on Computers, 52(10):1332–1346.

Lima, G. and Burns, A. (2005). Scheduling Fixed-Priority Hard Real-Time Tasks in the Presence of Faults. In Proc. of the 2nd Latin-American Symposium on Dependable Computing, volume LNCS 3747, pages 154–173. Springer-Verlag.

Lima, G. and Nascimento, F. (2009). Simulation Scenarios: a Means of Deriving Fault Resilience for Real-Time Systems. In Proc. of the 11th Workshop on Real-Time and Embedded Systems.

Liu, C. L. and Layland, J. W. (1973). Scheduling algorithms for multiprogramming in a hard-real-time environment. Journal of the ACM, 20(1):46–61.

Liu, J. W. S. W. (2000). Real-Time Systems. Prentice Hall PTR, Upper Saddle River, NJ, USA.

Pandya, M. and Malek, M. (1998). Minimum achievable utilization for fault-tolerant processing of periodic tasks. IEEE Transactions on Computers, 47(10):1102–1112.

Pereira, N., Tovar, E., Batista, B., Pinho, L. M., and Broster, I. (2004). A few what-ifs on using statistical analysis of stochastic simulation runs to extract timeliness properties. In 1st International Workshop on Probabilistic Analysis Techniques for Real-time and Embedded Systems (PARTES ’2004), Pisa, Italy.

Triola, M. F. (2008). Elementary Statistics. Pearson.

Wall, A., Andersson, J., and Norstrom, C. (2003). Probabilistic simulation-based analysis of complex real-time systems. In Proc. of the Sixth IEEE International Symposium on Object-Oriented Real-Time Distributed Computing, pages 257–266.