Abstract
Online laboratories are a broad field that includes virtual laboratories, remote laboratories and hybrid configurations. The assessment of the reliability for these systems requires the identification of the laboratory components or human actions that can lead to a possible failure in the online laboratory normal operation. Having now bigger online laboratories implementations that provide access to hundreds or even thousands of users, the identification and evaluation of failures, causes and developing countermeasures, such as recovery mechanisms or alerts, is becoming increasingly important in order to provide more reliable systems. The paper presents a model for the assessment of failures, causes and countermeasures (actions, alerts or practices) that mitigate or eliminate failures. The model was created based on common failures reported by online laboratories users and based on the testing of a remote laboratory prototype implemented specifically for this purpose. The model for the assessment of the reliability of the online laboratory systems can be used to support reliability in implementations that are based on software components, such as virtual laboratories; and also in implementations that combine hardware and software components such as remote and hybrid laboratories. The model proposes a classification of the failures and its causes in a scale of low, medium and high frequency of occurrence. A definition of a rule based system based on the laboratories constrains is presented. Finally a definition of the integration of the model with the Remote Laboratory Management System (RLMS) is presented.
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Gravier, C., Fayolle, J., Bayard, B., Ates, M., Lardon, J.: State of the art about remote laboratories paradigms foundations of ongoing mutations. Int. J. Online Eng. 4, 1–9 (2008)
Nickerson, J.V., Corter, J.E., Esche, S.K., Chassapis, C.: A model for evaluating the effectiveness of remote engineering laboratories and simulations in education. Comput. Educ. 49, 708–725 (2007)
Ramakrishnan, T., Pecht, M.: Electronic hardware reliability. In: Avionics Handbook, pp. 22.1–22.21. CRC, Boca Raton (2000)
Smith, D.J.: Reliability, Maintainability and Risk, 9th edn. Butterworth-Heinemann, Amsterdam (2017). ISBN 9780081020104
Randell, B., Lee, P., Treleaven, P.C.: Reliability issues in computing system design. ACM Comput. Surv. 10(2) (1978). https://doi.org/10.1145/356725.356729
Shooman, M.L.: Probabilistic Reliability: An Engineering Approach. Mc-Graw-Hill Inc., New York (1968)
ISO/IEC 25010 - Systems and software engineering - Systems and software Quality Requirements and Evaluation (SQuaRE) - System and software quality models. ISO/IEC (2010)
Cristian, F.: Understanding Fault-Tolerant Distributed Systems. Thesis in Computer Science and Engineering, University of California, San Diego (1993)
Yu, T.L.: Lecture notes: operating systems concepts and theory. California State University (2010). http://cse.csusb.edu/tongyu/courses/cs660/notes/recovery.php
Newell, A., Simon, H.: A Human Problem Solving. Prentice Hall, Englewood Cliffs (1972)
Qin, B., Xia, Y., Prabhakar, S.: A rule-based classification algorithm for uncertain data. In: IEEE 25th International Conference on Data Engineering, ICDE 2009 (2009)
Marco, C., Prattichizzo, D., Vicino, A.: Operating remote laboratories through a bootable device. IEEE Trans. Ind. Electron. 54(6), 3134–3140 (2007)
Wu, C., Hwang, J., Chladek, J.: Fault-tolerant joint development for the space shuttle remote manipulator system: analysis and experiment. IEEE Trans. Robot. Autom. 9(5), 675–684 (1993)
Guimaraes, G., et al.: Design and implementation issues for modern remote laboratories. IEEE Trans. Learn. Technol. 4(2), 149–161 (2011)
Jess, The Java Expert System Shell. http://www.jessrules.com/docs/45/
Zapata-Rivera, L.F., Larrondo Petrie, M.M.: Implementation of cloud-based smart adaptive remote laboratories for education. In: Frontiers in Education (2017)
Zapata-Rivera, L.F., Larrondo Petrie, M.M.: Models of collaborative remote laboratories and integration with learning environments. Int. J. Online Eng. 12(9), 14–21 (2016)
Acknowledgements
This work has been supported by The Latin America and Caribbean Consortium of Engineering Institutions LACCEI, which is providing resources to make advances in this field. With the goal in the near future to have a great impact with online laboratories in the communities of the Latin America and the Caribbean region that has been affected by natural disasters such as Haiti, Puerto Rico, among others.
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Zapata-Rivera, L.F., Larrondo-Petrie, M.M. (2019). A Reliability Assessment Model for Online Laboratories Systems. In: Auer, M., Langmann, R. (eds) Smart Industry & Smart Education. REV 2018. Lecture Notes in Networks and Systems, vol 47. Springer, Cham. https://doi.org/10.1007/978-3-319-95678-7_28
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DOI: https://doi.org/10.1007/978-3-319-95678-7_28
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