Hasan Esen
ABSTRACT
The Internet of Things (IoT) is the interconnection of embedded devices and offers the possibility of exploiting cloud-based services to improve control functions. But how much cloud control is possible when facing real-time challenges in a safety-critical environment? This paper provides first insights and data into cloud-based control by means of a feasibility study in the automotive domain. We present the Control as a Service (CaaS) concept, which investigates cloud-based control scheme for a model car with WLAN / CAN gateway. CaaS delivers successfully an architectural design and a proof-of-concept implementation for a simple cloud-based throttle limitation scenario, in which the throttle values requested by driver (remote control user) is dynamically regulated by a controller implemented as a virtual ECU (Electronic Control Unit) in the cloud. We found that the correct handling of time-varying network delay is one of the most relevant challenges. Therefore we started a simulation study in parallel to design controllers that are capable of coping with network imperfections. Preliminary simulation results indicate the potential of model predictive control.
- D. Bernardini and A. Bemporad. Stabilizing model predictive control of stochastic constrained linear systems. IEEE Trans. Automatic Control, 57(6):1468--1480, 2012.Google Scholar
Cross Ref
- M. Bichi, G. Ripaccioli, S. Di Cairano, D. Bernardini, A. Bemporad, and I. Kolmanovsky. Stochastic model predictive control with driver behavior learning for improved powertrain control. In Proc. 49th IEEE Conf. on Decision and Control, pages 6077--6082, Atlanta, GA, 2010.Google ScholarCross Ref
- A. Cervin, D. Henriksson, B. Lincoln, J. Eker, and K. Årzn. How does control timing affect performance? analysis and simulation of timing using Jitterbug and TrueTime. IEEE Control Systems Magazine, 23(3):16--30, 2003.Google ScholarCross Ref
- M. Donkers, W. Heemels, D. Bernardini, A. Bemporad, and V. Shneer. Stability analysis of stochastic networked control systems. Automatica, 48:917--925, 2012. Google ScholarDigital Library
- T. Keuler, J. Knodel, and M. Naab. Fraunhofer aces: Architecture-centric engineering solutions. Technical Report 079.11/E, Fraunhofer IESE, Fraunhofer IESE, 2011.Google Scholar
- P. O. M. Scokaert and D. Q. Mayne. Min-max feedback model predictive control for constrained linear systems. IEEE Trans. Automatic Control, 43:1136--1142, 1998.Google ScholarCross Ref
- P. Seiler and R. Sengupta. An h∞ approach to networked control. IEEE Transactions on Automatic Control, 5(3):356--364, 2005.Google ScholarCross Ref
- Y. Shi and B. Yu. Output feedback stabilization of networked control systems with random delays modeled by Markov chains. IEEE Trans. Automatic Control, 54(7):1668--1674, 2009.Google ScholarCross Ref
- R. N. Taylor, N. Medvidovic, and E. M. Dashofy. Software Architecture: Foundations, Theory, and Practice. John Wiley and Sons, Hoboken, 2010. Google ScholarDigital Library
- X. Yu, J. Modestino, and X. Tian. The accuracy of Gilbert models in predicting packet-loss statistics for a single-multiplexer network model. In INFOCOM. 24th Annual Joint Conference of the IEEE Computer and Communications Societies, volume 4, pages 2602--2612, 2005.Google Scholar
Recommendations
Cloud service engineering
ICSE '10: Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 2Building on compute and storage virtualization, Cloud Computing provides scalable, network-centric, abstracted IT infrastructure, platforms, and applications as on-demand services that are billed by consumption. Cloud Service Engineering is the ...
A Pattern for Fog Computing
VikingPLoP '16: Proceedings of the 10th Travelling Conference on Pattern Languages of ProgramsFog Computing is a new variety of the cloud computing paradigm that brings virtualized cloud services to the edge of the network to control the devices in the IoT. We present a pattern for fog computing which describes its architecture, including its ...
Pricing as a Service: Personalized Pricing Strategy in Cloud Computing
CIT '12: Proceedings of the 2012 IEEE 12th International Conference on Computer and Information TechnologyCloud computing is emerging as a model in support of "everything-as-a-service". Virtualized physical resources, virtualized infrastructure, as well as virtualized middleware platforms and business applications are being provided and consumed as services ...
Comments