ProMARTES: Performance Analysis Method and Toolkit for Real-Time Systems

  • Konstantinos TriantafyllidisEmail author
  • Egor Bondarev
  • Peter H. N. de With
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 311)


In this chapter, we present a cycle-accurate performance analysis method for real-time systems that incorporates the following phases: 1. profiling SW components at high accuracy, 2. modeling the obtained performance measurements in MARTE-compatible models, 3. generation, scheduling analysis and simulation of a system model, 4. analysis of the obtained performance metrics, and 5. a subsequent architecture improvement. The method has been applied to a new autonomous navigation system for robots with advanced sensing capabilities, enabling validation of multiple performance analysis aspects, such as SW/HW mapping, real-time requirements and synchronization on multiprocessor schemes. The case-study has proved that the method is able to use the profiled low-level performance metrics throughout all the phases, resulting in high prediction accuracy. We have found a range of inefficient design directions leading to RT requirements failure, and recommended to robot owners a design decision set to reach an optimal solution.


Profiling Modeling Component-based Simulation Schedulability analysis Performance analysis  Evaluation Prediction Assessment Optimization  Real-time system Modeling and Analysis of Real-Time and Embedded systems (MARTE) 


  1. 1.
    AUTOSAR (2003) AUTOSAR: AUtomotive Open System Architecture. AUTOSAR Consortium,
  2. 2.
    Becker S, Koziolek H, Reussner R (2007) Model-based performance prediction with the palladio component model. In: Proceedings of the 6th international workshop on software and performance (WOSP) 2007, ACM, pp 54–65. doi: 10.1145/1216993.1217006
  3. 3.
    Bertolino A, Mirandola R (2004) CB-SPE tool: putting component-based performance engineering into practice. In: Crnkovic I, Stafford JA, Schmidt HW, Wallnau K (eds) Component-based software engineering, vol 3054, Springer, Berlin and Heidelberg, Germany, pp 233–248. doi: 10.1007/978-3-540-24774-6_21
  4. 4.
    Bondarev E, Chaudron M, de With P (2006) A process for resolving performance trade-offs in component-based architectures. In: Gorton I, Heineman GT, Crnković I, Schmidt HW, Stafford JA, Szyperski C, Wallnau K (eds) Component-based software engineering—9th international symposium, CBSE 2006, Västerås, Sweden, Lect Notes Comput Sci, vol 4063, Springer, Berlin, Germany, pp 254–269. doi: 10.1007/11783565_18
  5. 5.
    Bondarev E, Chaudron M, de With P (2007) CARAT: a toolkit for design and performance analysis of component-based embedded systems. In: Proceedings of the design, automation test in Europe conference exhibition (DATE) 2007, pp 1–6. doi: 10.1109/DATE.2007.364428
  6. 6.
    Cortellessa V, Pierini P, Rossi D (2007) Integrating software models and platform models for performance analysis. IEEE Trans Softw Eng 33(6):385–401. doi: 10.1109/TSE.2007.1014 CrossRefGoogle Scholar
  7. 7.
    Cuesta C (2010) JsimMAST: The performance analysis simulator for real-time.
  8. 8.
    Eker J, Janneck JW, Lee EA, Liu J, Liu X, Ludvig J, Neuendorffer S, Sachs S, Xiong Y (2003) Taming heterogeneity—the Ptolemy approach. Proc IEEE 91(1):127–144. doi: 10.1109/JPROC.2002.805829 CrossRefGoogle Scholar
  9. 9.
    Garage W (2007) ROS: the robot operating system. Open Source Robotics Foundation.
  10. 10.
    Gonzalez Harbour M, Gutierrez Garcia J, Palencia Gutierrez J, Drake Moyano J (2001) MAST: modeling and analysis suite for real time applications. In: Proceedings of the 13th Euromicro conference on real-time systems 2001, pp 125–134. doi: 10.1109/EMRTS.2001.934015
  11. 11.
    Graf S, Ober I, Ober I (2006) A real-time profile for UML. Int J Softw Tools Technol Transf 8(2):113–127. doi: 10.1007/s10009-005-0213-x CrossRefGoogle Scholar
  12. 12.
    Grassi V, Mirandola R, Sabetta A (2005) From design to analysis models: a kernel language for performance and reliability analysis of component-based systems. In: Proceedings of the 5th international workshop on software and performance (WOSP) 2005, ACM, New York, NY, USA, pp 25–36.doi: 10.1145/1071021.1071024
  13. 13.
    Hissam S, Moreno G, Stafford J, Wallnau K (2003) Enabling predictable assembly. J Syst Softw 65(3):185–198. doi: 10.1016/S0164-1212(02)00038-9 component-Based Software EngineeringCrossRefGoogle Scholar
  14. 14.
    IBM (2003) Rationale rose: a modeling environment. IBM.
  15. 15.
    ITEA (2000) ROBOCOP: robust open component based software architecture for configurable devices project. ITEA.
  16. 16.
    Klobedanz K, Kuznik C, Thuy A, Mueller W (2010) Timing modeling and analysis for AUTOSAR-based software development—a case study. In: Proceedings of design, automation test in Europe conference exhibition (DATE) 2010, pp 642–645. doi: 10.1109/DATE.2010.5457125
  17. 17.
    Liu Y, Fekete A, Gorton I (2005) Design-level performance prediction of component-based applications. IEEE Trans Softw Eng 31(11):928–941. doi: 10.1109/TSE.2005.127 CrossRefGoogle Scholar
  18. 18.
    Medina JL, Cuesta AG (2011) MAST: modeling and analysis suite for real-time applications.
  19. 19.
    Medina JL, Garcia Cuesta A (2011) Model-based analysis and design of real-time distributed systems with Ada and the UML profile for MARTE. In: Reliable software technologies—Ada-Europe 2011, Lect Notes Comput Sci, vol 6652, Springer, Berlin and Heidelberg, Germany, pp 89–102.doi: 10.1007/978-3-642-21338-0_7
  20. 20.
    Mos A, Murphy J (2002) A framework for performance monitoring, modelling and prediction of component oriented distributed systems. In: Proceedings of the 3rd international workshop on software and performance (WOSP) 2002, ACM, New York, NY, USA, pp 235–36. doi: 10.1145/584369.584403
  21. 21.
    Määttä S, Indrusiak LS, Ost L, Möller L, Glesner M, Moraes FG, Nurmi J (2010) Model based approach for heterogeneous application modelling for real time embedded systems. In: Proceedings of the third international workshop on model based architecting and construction of embedded systems (ACES-MB 2010), held as part of the 2010 international conference on model driven engineering languages and systems (MoDELS’10), Oslo, Norway.
  22. 22.
    OMG (2007) SysML: systems modeling language. OMG.
  23. 23.
    OMG (2009) MARTE: modeling and analysis of real time and embedded systems. OMG.
  24. 24.
    SAE (2000) Architecture analysis and design language. SAE.
  25. 25.
    Silvano C, Fornaciari W, Palermo G, Zaccaria V, Castro F, Martinez M, Bocchio S, Zafalon R, Avasare P, Vanmeerbeeck G, Ykman-Couvreur C, Wouters M, Kavka C, Onesti L, Turco A, Bondik U, Marianik G, Posadas H, Villar E, Wu C, Dongrui F, Hao Z, Shibin T (2010) MULTICUBE: multi-objective design space exploration of multi-core architectures. In: Proceedings of the 2010 IEEE Annu Symp VLSI (ISVLSI), IEEE Comput Soc, Washington, DC, USA, pp 488–493. doi: 10.1109/ISVLSI.2010.67
  26. 26.
    Thompson M, Polstra S, Erbas C, Pimentel AD (2008) Calibration of abstract performance models for system-level design space exploration. J Signal Proc Syst 50(2):99–114. doi: 10.1007/s11265-007-0085-2 CrossRefGoogle Scholar
  27. 27.
    Triantafyllidis K (2013) ProMARTES: profiling, modeling, analysis of real-time embedded systems.
  28. 28.
    Triantafyllidis K, Bondarev E, de With P (2012) Low-level profiling and MARTE-compatible modeling of software components for real-time systems. In: Proceedings of the 38th EUROMICRO conference on software engineering and advanced applications (SEAA) 2012, pp 216–223.doi: 10.1109/SEAA.2012.25
  29. 29.
    Wandeler E, Thiele L, Verhoef M, Lieverse P (2006) System architecture evaluation using modular performance analysis: a case study. Int J Softw Tools Technol Transfer 8(6):649–667. doi: 10.1007/s10009-006-0019-5 CrossRefGoogle Scholar
  30. 30.
    Wu X, Woodside M (2004) Performance modeling from software components. In: Proceedings of the 4th international workshop on software and performance (WOSP) 2004, ACM, New York, NY, USA, pp 290–301. doi: 10.1145/974044.974089

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Konstantinos Triantafyllidis
    • 1
    Email author
  • Egor Bondarev
    • 1
  • Peter H. N. de With
    • 1
  1. 1.Eindhoven University of TechnologyEindhovenThe Netherlands

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