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Bonus computing: towards free-of-charge metacomputing in the public cloud

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Abstract

Free-of-charge metacomputing aims at integrating surplus computing resources and utilizing their inter-connected computing power to fulfil computational demands at virtually no cost. The existing efforts on free-of-charge metacomputing can be observed in grid computing, parasitic computing and volunteer computing. As extensively discussed in the literature, these three metacomputing forms all have their respective challenges and shortcomings, ranging from sophisticated enabling technologies to possible frequent interruptions, not to mention the potential ethical and legal issues in parasitic computing. Based on our observation on the growing marketing strategy of offering cloud service samples (free quotas), we argue that it is also possible to follow a metacomputing approach to take advantage of free resources in the public cloud market. By applying this idea to our educational work, we gradually developed an implementation framework to facilitate exploiting free quotas of cloud user accounts. The relatively unique features and characteristics of cloud resource exploitation eventually turn our effort into a distinctive metacomputing form, and we name it bonus computing. Guided by the implementation framework, we initially verified bonus computing’s effectiveness and efficiency by implementing a proof-of-concept (PoC) system over multiple cloud vendors. Then, we justified bonus computing’s applicability by extending the PoC system to a Monte Carlo solution to a real-world problem in Astronomy. Based on our existing practices and the recent SLURM cluster experiments, we have tried to comprehensively analyze bonus computing’s advantages and disadvantages against the other comparable metacomputing forms, which in turn strengthens our confidence in this work’s contribution especially to the educational community.

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Notes

  1. Our later work further identified AWS Educate (https://aws.amazon.com/education/awseducate/) and Azure for Students (https://azure.microsoft.com/en-us/free/students/) for bonus computing.

  2. https://cloud.google.com/appengine/.

  3. https://www.ibm.com/cloud/lite-account/.

  4. https://run.pivotal.io/.

  5. https://nectar.org.au/cloudpage/.

  6. https://www.mersenne.org/.

  7. A demo of the submitted APIs is share at https://bit.ly/3xYjWrT.

  8. One of the contributor prototypes on GAE for this experiment is https://vocal-plateau-201001.appspot.com/hello/, which directly returns the number of points that fall inside the circle from the 100 million random-point generations.

  9. NGC 2808 is one of the most massive clusters in our home galaxy, containing more than one million stars.

  10. To facilitate readers’ review, we particularly demonstrate a single-tree generation task at https://appgae-219421.appspot.com.

  11. “Only the value of the E population seems to be statistically different from the metallicity of the primordial and intermediate components” [6].

  12. A broker implementation report: http://bit.ly/2X31U6l.

  13. A comparison study report: http://bit.ly/2Q0eS31.

  14. https://slurm.schedmd.com/overview.html.

  15. We maintain a live experimental doc: http://bit.ly/2X7pKxH.

  16. An example deployment cheatsheet: http://bit.ly/2K98fYn.

  17. Dropbox API: https://www.dropbox.com/developers/reference/getting-started.

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Authors and Affiliations

  1. University of Concepción, Concepción, Chile

    Zheng Li, Pedro Pinacho-Davidson, Monserrat Martínez-Marin, Guillermo Cabrera-Vives & María Andrea Rodríguez

  2. University of Melbourne, Parkville, Australia

    Yiqun Chen

  3. The University of Sydney, Camperdown, Australia

    Albert Y. Zomaya

  4. Newcastle University, Newcastle upon Tyne, UK

    Rajiv Ranjan

Authors
  1. Zheng Li
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  2. Pedro Pinacho-Davidson
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  3. Monserrat Martínez-Marin
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  4. Guillermo Cabrera-Vives
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  5. Yiqun Chen
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  6. María Andrea Rodríguez
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  7. Albert Y. Zomaya
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  8. Rajiv Ranjan
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This work was supported in part by Chilean National Research and Development Agency (ANID, Chile) under Grant FONDECYT Iniciación 11180905, and in part by the University of Concepción under Grant Teaching Innovation INICIA I19-027.

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Li, Z., Pinacho-Davidson, P., Martínez-Marin, M. et al. Bonus computing: towards free-of-charge metacomputing in the public cloud. Computing 104, 123–147 (2022). https://doi.org/10.1007/s00607-021-01036-3

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