Self-configuration in humanized Cyber-Physical Systems
- 300 Downloads
Most works on Cyber-Physical Systems (CPS) are based on classic hardware infrastructures made of sensors, actuators and processing devices. Usual self-configuration technologies, then, do not allow humans to be integrated in CPS as service providers. Therefore, in this work we propose a new self-configuration technology for humanized CPS. The proposed technology uses simple binary and mathematical operations in order to reduce the convergence time, improve the scalability and address the dynamism introduced by humans into CPS. Besides, a human-oriented quality-of-service algorithm based on the Maslow pyramid is also introduced. Moreover, an experimental validation is conducted in order to validate the proposed solution as a useful and scalable self-configuration technology for humanized Cyber-Physical Systems.
KeywordsCyber-Physical Systems HCI Humanized computing Self-configuration Humanized CPS Maslow pyramid
The research leading to these results has received funding from the Ministry of Economy and Competitiveness through SEMOLA project (TEC2015-68284-R) and from the Autonomous Region of Madrid through MOSI-AGIL-CM project (grant P2013/ICE-3019, co-funded by EU Structural Funds FSE and FEDER).
Compliance with ethical standards
Conflicts of interest
The authors declare that there is no conflict of interest regarding the publication of this paper.
- Bitalino (2014). Project Bitalino [online]. http://www.bitalino.com/. Accessed 26 March 2016
- Bordel B, Alcarria R, Pérez-Jiménez M, Robles T, Martín D, de Rivera DS (2015) Building smart adaptable Cyber-Physical Systems: definitions, classification and elements. In: ubiquitous computing and ambient intelligence. Sensing, processing, and using environmental information, Springer International Publishing, Berlin, pp 144–149Google Scholar
- Cardenas AA, Amin S, Sastry S (2008) Secure control: towards survivable cyber-physical systems. In: the 28th International Conference on Distributed Computing Systems Workshops (pp 495–500) IEEEGoogle Scholar
- De Lemos R, Giese H, Müller HA, Shaw M, Andersson J, Litoiu M, Weyns D (2013) Software engineering for self-adaptive systems: a second research roadmap. Springer, Berlin Heidelberg, pp 1–32Google Scholar
- Dillon T, Potdar V, Singh J, Talevski A (2011) Cyber-Physical Systems: providing quality of service (QoS) in a heterogeneous systems-of-systems environment. In: digital ecosystems and technologies Conference (DEST), 2011.In: Proceedings of the 5th IEEE International Conference on (pp. 330–335). IEEEGoogle Scholar
- Domingues J, Damaso A, Nascimento R, Rosa N (2011) An energy-aware middleware for integrating wireless sensor networks and the internet. Int J Distrib Sens Netw 2011:672313. doi: 10.1155/2011/672313
- European commission (2005). Proyect Hydra. [online]. http://www.hydramiddleware.eu/articles.php?article_id=68. Accessed 26 March 2016
- Hoang DD, Paik HY, Kim CK (2012) Service-oriented middleware architectures for cyber-physical systems. Int J Comput Sci Netw Secur 12(1):79–87Google Scholar
- JaSkowski P, Rybarczyk K, Jaroszyk F, Lemanski D (1995) The effect of stimulus intensity on force output in simple reaction time task in humans. Acta Neurobiol Exp 55:57Google Scholar
- Keddis N, Kainz G, Buckl C, Knoll A (2013) Towards adaptable manufacturing systems. In: Industrial Technology (ICIT), 2013 IEEE International Conference on (pp 1410–1415). IEEEGoogle Scholar
- Lee EA (2006) Cyber-physical systems-are computing foundations adequate. In position paper for NSF workshop On Cyber-Physical Systems: research motivation, techniques and roadmap (vol 2)Google Scholar
- Park J, Lee S, Yoon T (2015) Designing goal model for autonomic control point of Cyber-Physical Systems (CPS). Indian J Sci Technol 8(19). doi: 10.17485/ijst/2015/v8i19/76692
- Wang T, Niu C, Cheng L (2014) A two-phase context-sensitive service composition method with the workflow model in cyber-physical systems. In: Computational Science and Engineering (CSE), 2014 IEEE 17th International Conference on (pp 1475–1482). IEEEGoogle Scholar