Abstract
The Artificial DNA (ADNA) and Artificial Hormone System (AHS) together form a middleware that uses Organic Computing techniques to improve the robustness and adaptability of distributed embedded systems. These systems then have the properties of self-organization, self-healing, self-configuration and self-improvement. However, the adaptability of the system is limited by the rigidity of the ADNA, since it cannot be modified at runtime. Recent research approaches already assume the existence of a modifiable ADNA in their applications without actually implementing it or evaluating its behavior. In this paper, we present two crucial steps to extend the ADNA with the ability to allow run-time modifications. First, we describe the possible modifications that can be made at runtime, and how they can be implemented without making significant changes to the ADNA implementation. Second, we provide an experimental evaluation of this new feature and contextualize its behavior within the framework of traditional ADNA.
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Notes
- 1.
Strictly speaking, the task function reads the Destinationlink information each time it sends messages to the destinations. Updating the Destinationlinks in the DNA array would suffice without requiring a restart. However, this approach has not been implemented yet due to the potential for inconsistencies in the sending procedure.
- 2.
It is implicitly assumed that each task function is implemented with a proper shut down procedure, i.e. no removal may stall the modification indefinitely.
- 3.
In order to allow reproducabilty of the results, the modification requests are also stored with the results.
- 4.
In the light weight implementation, this is the allocated time for the decision phase.
- 5.
Other tests with slightly altered wait times in the test environment show that the behavior falls in line with the other cycle lengths.
- 6.
In the cases close to the multiples, this circumstance must happen twice.
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Koschowoj, A., Brinkschulte, U. (2024). Modifiable Artificial DNA - Change Your System’s ADNA at Any Time. In: Fey, D., Stabernack, B., Lankes, S., Pacher, M., Pionteck, T. (eds) Architecture of Computing Systems. ARCS 2024. Lecture Notes in Computer Science, vol 14842. Springer, Cham. https://doi.org/10.1007/978-3-031-66146-4_5
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