A Framework for Analyzing and Evaluating Architectures and Control Strategies in Distributed Remote Laboratories

Autor: Danilo Garbi Zutin, Ananda Maiti, Heinz-Dietrich Wuttke, Karsten Henke, Alexander A. Kist, Andrew D. Maxwell
Rok vydání: 2018
Předmět:
Zdroj: IEEE Transactions on Learning Technologies. 11:441-455
ISSN: 2372-0050
Popis: 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 bo x 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.
Databáze: OpenAIRE