Abstract
One approach to handle the ever-increasing complexity of embedded systems is the Artificial Hormone System (AHS). The AHS is a middleware based on Organic Computing principles capable of assigning tasks to a distributed system’s processing elements (PEs). It is completely decentralized and has no single point of failure. In case a PE fails, the affected tasks are automatically re-assigned to healthy PEs, thus self-healing the system. Furthermore, the AHS is suited for real-time systems since hard time bounds can be proven for the duration of its self-configuration and self-healing capabilities.
A recently proposed extension of the AHS supports defining assignment priorities for tasks. These allow to enforce a specific order of task assignment, thus allowing to e.g. start the most important tasks first during the system’s initial self-configuration and to make sure these tasks are re-assigned as quickly as possible in self-healing scenarios.
Although this priority-based AHS extension’s time bounds have previously been studied, its behavior has not yet been thoroughly evaluated. In this paper, we thus present evaluations of this extension, confirming and refining the known time bounds.
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References
Brinkschulte, U., Fastnacht, F.: Applying the concept of artificial DNA and hormone system to a low-performance automotive environment. In: Schoeberl, M., Hochberger, C., Uhrig, S., Brehm, J., Pionteck, T. (eds.) ARCS 2019. LNCS, vol. 11479, pp. 87–99. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-18656-2_7
Brinkschulte, U., Pacher, M.: An agressive strategy for an artificial hormone system to minimize the task allocation time. In: 2012 IEEE 15th International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops. pp. 188–195. IEEE, Shenzhen, April 2012. https://doi.org/10.1109/ISORCW.2012.40
Brinkschulte, U., Pacher, M., von Renteln, A.: Towards an artificial hormone system for self-organizing real-time task allocation. In: Obermaisser, R., Nah, Y., Puschner, P., Rammig, F.J. (eds.) SEUS 2007. LNCS, vol. 4761, pp. 339–347. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-75664-4_34
Brinkschulte, U., Pacher, M., von Renteln, A., Betting, B.: Organic real-time middleware. In: Higuera-Toledano, M.T., Brinkschulte, U., Rettberg, A. (eds.) Self-Organization in Embedded Real-Time Systems, pp. 179–208. Springer, New York (2013). https://doi.org/10.1007/978-1-4614-1969-3_9
Chen, L., Xue-song, Q., Yang, Y., Gao, Z., Qu, Z.: The contract net based task allocation algorithm for wireless sensor network. In: 2012 IEEE Symposium on Computers and Communications (ISCC), pp. 600–604, July 2012. https://doi.org/10.1109/ISCC.2012.6249362
Fohler, G., Gala, G., Pérez, Daniel, G., Claire, Pagetti: evaluation of DREAMS resource management solutions on a mixed-critical demonstrator. In: ERTS 2018. 9th European Congress on Embedded Real Time Software and Systems (ERTS 2018), Toulouse, France, January 2018
Guan, N., Stigge, M., Yi, W., Yu, G.: Fixed-priority multiprocessor scheduling with Liu and Layland’s utilization bound. In: 2010 16th IEEE Real-Time and Embedded Technology and Applications Symposium, pp. 165–174. IEEE, Stockholm, April 2010. https://doi.org/10.1109/RTAS.2010.39
Hutter, E., Brinkschulte, U.: Towards a priority-based task distribution strategy for an artificial hormone system. In: Brinkmann, A., Karl, W., Lankes, S., Tomforde, S., Pionteck, T., Trinitis, C. (eds.) ARCS 2020. LNCS, vol. 12155, pp. 69–81. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-52794-5_6
Müller-Schloer, C., Tomforde, S.: Organic Computing – Technical Systems for Survival in the Real World. AS, Springer, Cham (2017). https://doi.org/10.1007/978-3-319-68477-2
Orlov, S., Korte, M., Oszwald, F., Vollmer, P.: Automatically reconfigurable actuator control for reliable autonomous driving functions (AutoKonf). In: 10th International Munich Chassis Symposium 2019. Tech Plus, Chassis (2019). https://doi.org/10.1007/978-3-658-26435-2_26
Schmeck, H.: Organic computing - A new vision for distributed embedded systems. In: Eighth IEEE International Symposium on Object-Oriented Real-Time Distributed Computing (ISORC 2005), pp. 201–203 (2005). https://doi.org/10.1109/ISORC.2005.42
Smith, R.G.: The contract net protocol: high-level communication and control in a distributed problem solver. IEEE Trans. Comput. C-29(12), 1104–1113 (1980). https://doi.org/10.1109/TC.1980.1675516
Sun, Y., Lipari, G., Guan, N., Yi, W.: Improving the response time analysis of global fixed-priority multiprocessor scheduling. In: 2014 IEEE 20th International Conference on Embedded and Real-Time Computing Systems and Applications, pp. 1–9, August 2014. https://doi.org/10.1109/RTCSA.2014.6910543
von Renteln, A., Brinkschulte, U., Pacher, M.: The artificial hormone system—An organic middleware for self-organising real-time task allocation. In: Müller-Schloer, C., Schmeck, H., Ungerer, T. (eds.) Organic Computing — A Paradigm Shift for Complex Systems. ASYS, vol. 1, pp. 369–384. Springer, Basel (2011). https://doi.org/10.1007/978-3-0348-0130-0_24
Yin, X., Dai, W., Li, B., Chang, L., Li, C.: Cooperative task allocation in heterogeneous wireless sensor networks. Int. J. Distrib. Sensor Networks 13(10), 15501447 (2017). https://doi.org/10.1177/1550147717735747
Zhang, J., Wang, G., Song, Y.: Task assignment of the improved contract net protocol under a multi-agent system. Algorithms 12(4), 70 (2019). https://doi.org/10.3390/a12040070
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Hutter, E., Brinkschulte, U. (2021). Evaluating a Priority-Based Task Distribution Strategy for an Artificial Hormone System. In: Hochberger, C., Bauer, L., Pionteck, T. (eds) Architecture of Computing Systems. ARCS 2021. Lecture Notes in Computer Science(), vol 12800. Springer, Cham. https://doi.org/10.1007/978-3-030-81682-7_10
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