Ouvrages édités à titre de seul éditeur ou en collaboration (4)
  1. 1. Goossens, J. (2016). Special issue on the Real-Time and Network Systems (RTNS 2014) conference.
  2. 2. Goossens, J., & Maiza, C. (2014). Proceedings of the 22nd International Conference on Real-Time Networks and Systems. Association for Computing Machinery.
  3. 3. Goossens, J., & Baruah, S. (2006). Multiprocessor Real-time Scheduling.
  4. 4. Goossens, J. (2004). Proceedings of the 12th RTS Embedded Systems.
    5.   Parties d'ouvrages collectifs (5)
  5. 1. Goossens, J., & Richard, P. (2017). Multiprocessor Real-Time Scheduling. In Cyber-Physical Systems: A Reference. doi:10.1007/978-3-642-54477-4_2-1
  6. 2. Goossens, J., & Richard, P. (2014). Multiprocessor Architecture Solutions. In Real-Time Systems Scheduling 1: Fundamentals (pp. 105-147). wiley. doi:10.1002/9781118984413.ch3
  7. 3. Goossens, J., & Richard, P. (2014). Solutions pour les architectures multiprocesseurs. In M. Silly-Chetto (Ed.), Ordonnancement dans les systèmes temps réel (1 ed., p. 398). ISTE Editions.
  8. 4. Goossens, J. (2006). Ordonnancement temps réel multiprocesseur. In N. Navet (Ed.), Systèmes temps réel, Vol. 2. Ordonnancement, réseaux et qualité de service. Paris: Hermès.(Informatique et systèmes d'information).
  9. 5. Baruah, S., & Goossens, J. (2004). Scheduling real-time tasks: algorithms and complexity. In J. Leung (Ed.), Handbook of Scheduling: Algorithms, Models, and Performance Analysis (pp. 1-26). Boca Raton: Chapman Hall/CRC Press.
    10.   Articles dans des revues avec comité de lecture (75)
  10. 1. Goossens, J., & Masson, D. (2022). Simulation intervals for uniprocessor real-time schedulers with preemption delay. Proceedings of Real-Time and Network Systems, RTNS 2022, 36-45.
  11. 2. Bertout, A., Goossens, J., Jamil, R., & Poczekajlo, X. (2022). Workload assignment for global real-time scheduling on unrelated clustered platforms. Real-time systems, 58, 4-35.
  12. 3. Schuh, M., Maiza, C., Goossens, J., Raymond, P., & Dupont de Dinechin, B. (2020). A study of predictable execution models implementation for industrial data-flow applications on a multi-core platform with shared banked memory. Proceedings - Real-Time Systems Symposium. doi:https://doi.org/10.1109/RTSS49844.2020.00034
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