A framework for analyzing and evaluating architectures and control strategies in distributed remote laboratories

Maiti, Ananda and Zutin, Danilo G. and Wuttke, Heinz-Dietrich and Henke, Karsten and Maxwell, Andrew D. and Kist, Alexander A. (2017) A framework for analyzing and evaluating architectures and control strategies in distributed remote laboratories. IEEE Transactions on Learning Technologies. ISSN 1939-1382

Abstract

Remote Access Laboratories (RALs) have been used to develop experimental knowledge about practical engineering topics for a while. Distributed remote laboratories aim to share experiment among institutions and individuals through a distributed architecture. Experiments from diverse areas are combined as part of a larger system. Multiple control strategies are used to integrate experiments in Remote Laboratory Management Systems (RLMSs). This work defines two main categories to analyze the various implementations, white box and black box approaches. Experiments can be on a spectrum between these two extremes, sharing properties of both. When integrating an existing experiment into a new distributed RAL system, it is useful to evaluate the experiment with respect to its host or new RLMS for determining the best strategies to assimilate it. This paper provides a framework for such evaluation based on a number of properties of experiments. The proposed framework is called SHASS (Software, Hardware, Assessment, Support, and Share-ability) based on several factors such as the hardware used, the software to create the program, methods of sharing, user’s support, and assessment of user’s performance. It can be used to evaluate quality and identify options for improvements within an experiment's existing RLMS as well. Using this framework, a black box and white box approach are compared using two examples - federated and Peer-to-Peer RAL. The evaluation focuses on technical capabilities and development possibilities. A set of four experiments are also analysed to illustrate the utility of the framework in creating and improving experiments with respect to their RLMS.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: First Online 28 Dec 2017. Permanent restricted access to ArticleFirst version in accordance with the copyright policy of the publisher.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Mechanical and Electrical Engineering
Date Deposited: 06 Jun 2018 04:00
Last Modified: 25 Jun 2018 03:43
Uncontrolled Keywords: remote laboratories; e-learning; networked control systems; educational technology
Fields of Research : 13 Education > 1301 Education Systems > 130199 Education systems not elsewhere classified
08 Information and Computing Sciences > 0899 Other Information and Computing Sciences > 089999 Information and Computing Sciences not elsewhere classified
Socio-Economic Objective: C Society > 93 Education and Training > 9301 Learner and Learning > 930102 Learner and Learning Processes
Identification Number or DOI: 10.1109/TLT.2017.2787758
URI: http://eprints.usq.edu.au/id/eprint/34231

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