Kuksa : self-adaptive microservices in automotive systems

Banijamali, Ahmad; Kuvaja, Pasi; Oivo, Markku; Jamshidi, Pooyan (2020-11-21)
 
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https://doi.org/10.1007/978-3-030-64148-1_23

Banijamali, Ahmad
Kuvaja, Pasi
Oivo, Markku
Jamshidi, Pooyan
Springer Nature
21.11.2020

Banijamali A., Kuvaja P., Oivo M., Jamshidi P. (2020) Kuksa∗: Self-adaptive Microservices in Automotive Systems. In: Morisio M., Torchiano M., Jedlitschka A. (eds) Product-Focused Software Process Improvement. PROFES 2020. Lecture Notes in Computer Science, vol 12562. Springer, Cham. https://doi.org/10.1007/978-3-030-64148-1_23

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© Springer Nature Switzerland AG 2020.This is a post-peer-review, pre-copyedit version of an article published in Product-Focused Software Process Improvement : 21st International Conference, PROFES 2020, Turin, Italy, November 25–27, 2020, Proceedings. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-64148-1_23.
https://rightsstatements.org/vocab/InC/1.0/
doi:https://doi.org/10.1007/978-3-030-64148-1_23
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https://urn.fi/URN:NBN:fi-fe2020120399302
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Abstract

In pervasive dynamic environments, vehicles connect to other objects to send operational data and receive updates so that vehicular applications can provide services to users on demand. Automotive systems should be self-adaptive, thereby they can make real-time decisions based on changing operating conditions. Emerging modern solutions, such as microservices could improve self-adaptation capabilities and ensure higher levels of quality performance in many domains. We employed a real-world automotive platform called Eclipse Kuksa to propose a framework based on microservices architecture to enhance the self-adaptation capabilities of automotive systems for runtime data analysis. To evaluate the designed solution, we conducted an experiment in an automotive laboratory setting where our solution was implemented as a microservice-based adaptation engine and integrated with other Eclipse Kuksa components. The results of our study indicate the importance of design trade-offs for quality requirements’ satisfaction levels of each microservices and the whole system for the optimal performance of an adaptive system at runtime.

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