Abstract
Deploying remote laboratories at a very large scale is one of the upcoming challenges in remote experimentation. It is referred to as Massive Open Online Labs (MOOLs). Being able to sustain a massive number of users accessing a specific resource concurrently is a complex task. The challenge is to maximize the use of the shared resource (the online lab) while minimizing or even canceling the waiting time to access the online lab such that the user feels it is dedicated to him/her. Tackling this problem requires revisiting both the pedagogical and the technical methodologies of online lab implementation, sharing, and deployment. In this chapter, we use indifferently online labs or remote labs to refer to physical labs accessible at distance through the Internet. A remote lab can also be considered as a cyber-physical system (CPS) as a combination of sensors, actuators, and embedded intelligence to fulfill given operational objectives.
Remote experimentation is becoming a mature technology, and it is usual to see institutions or platforms offering a significant number of remote labs. The model often chosen to enable online access to these labs is Laboratory as a Service (LaaS), where the lab is seen as a set of resources that the user can select on demand. The Smart Device model follows to the LaaS scheme and tries to describe the physical lab equipment and its digital components and interfaces as a unique entity. The Smart Device is seen through a set of services that the user can connect to. There is an ongoing effort to standardize the relationship between all the components (software, hardware, and learning environments). The aim of this standard is to ease the design, the implementation, and the usage of pedagogically oriented online laboratories as smart learning objects and their integration in learning environments and learning object repositories. The initial Smart Device model has been enriched to provide remote application developers a set of noteworthy configurations since not all combinations of sensors, actuators, and services are meaningful.
The Smart Device and other LaaS models are the cornerstone for deploying Massive Open Online Labs (MOOLs), but alone, they just provide a one-to-one (1:1) access: one user accesses one real equipment at a time. Various solutions such as efficient time-sharing and resource duplication are proposed to increase the numbers of concurrent users, and a ratio of 5–10:1 is possible. The next step is to be able to handle the massive access, in the range of 50–100:1. Accommodating such a large number of concurrent users to access a real critical resource is a challenge that can be addressed by first giving priority to some users, for example, using gamification mechanisms. The analysis of the online usage pattern also permits a real-time adaptation of the various session parameters and session ordering. Lastly providing usage awareness is a key to help users select the best experimentation time.
This paper first provides some historical perspective and rationale to introduce the Smart Device model and its recent modifications toward completeness. Then, it proposes the required modifications in both the pedagogical and technical aspects to “traditional” remote lab in order to support the massive aspect of MOOCs. The MOOC and MOOL infrastructures are then described, especially how a Smart Device client application is integrated in a MOOC as an LTI module and how this application is able to interact with other applications or tools such as simulations.
This paper focuses on technical aspects, currently deployed, to implement such a remote lab within a MOOC infrastructure. It first covers the Smart Device specifications and its latest extensions. Then, the technical aspects such as the Smart Device implementation (server side) and the HTML5 client application are described. The components used for the deployment such as the LTI interface, the user storage, and other interactive tools are presented. The load balancer and the methods used to control the access are then depicted.
This paper provides a learning scenario for a MOOC session using the above elements, and an example is given with the control system lab deployed in edX, where more than 200 students access concurrently a farm of 30 electrical drives.
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Notes
- 1.
Web Services Description Language (WSDL) 1.1, http://www.w3.org/TR/wsdl
- 2.
Web Services Description Language – Wikipedia, http://en.wikipedia.org/wiki/Web Services Description Language.
- 3.
RESTful Service Description Language (RSDL), http://en.wikipedia.org/wiki/RSDL
- 4.
RESTful API Modeling Language (RAML), http://raml.org/
- 5.
JSON Schema specification – JSON Schema: core definitions and terminology json-schema-core, http://json-schema.org/latest/json-schema-core.html
- 6.
Swagger website: http://swagger.wordnik.com/
- 7.
- 8.
Metadata specification examples for Smart Devices are available at GitHub: https://github.com/Go-Lab/smart-device-metadata
- 9.
The full Smart Device specification is available at https://github.com/go-lab/smart-device-metadata/raw/master/smart-device-specification/SmartDevice specification.pdf.
- 10.
JSON Schema specification – JSON Schema: core definitions and terminology json-schema-core, http://json-schema.org/latest/json-schema-core.html
- 11.
SI derived units – Wikipedia, http://en.wikipedia.org/wiki/SI derived unit
- 12.
The Activity Streams specification is available at http://activitystrea.ms/specs/json/1.0/
- 13.
Virtual Reality Modeling Language (VRML), http://gun.teipir.gr/VRML-amgem/spec/index.html
- 14.
- 15.
MathML, \http://www.w3.org/Math/
- 16.
Demilitarized zone (DMZ), http://en.wikipedia.org/wiki/DMZ (computing)
- 17.
- 18.
- 19.
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Acknowledgments
The authors acknowledge the support provided by EPFL for the development of the control system MOOC described in this paper. The Smart Device specifications were partially developed in the context of Go-Lab (grant no. 317601) project under the ICT theme of the Seventh Framework Programme for R&D (FP7). We would like to thank Anjo Anjewierden, Lars Bollen, August’ın Caminero, Manuel Castro, German Carro, Gabriel D’ıaz, Danilo Garbi Zutin, Miguel Latorre, Irene Lequerica Zorrozua, Pablo Ordun˜a, Yves Piguet, Antonio Robles, Miguel Rodriguez-Artacho, Hamadou Saliah-Hassane, Elio San Cr’ıstobal, and Simon Schwantzer (in alphabetical order) for their input during the numerous discussions leading to the presented specifications.
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Salzmann, C., Halimi, W., Gillet, D., Govaerts, S. (2018). Deploying Large-Scale Online Labs with Smart Devices. In: Auer, M., Azad, A., Edwards, A., de Jong, T. (eds) Cyber-Physical Laboratories in Engineering and Science Education. Springer, Cham. https://doi.org/10.1007/978-3-319-76935-6_3
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