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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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.
A demo of the submitted APIs is share at https://bit.ly/3xYjWrT.
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.
NGC 2808 is one of the most massive clusters in our home galaxy, containing more than one million stars.
To facilitate readers’ review, we particularly demonstrate a single-tree generation task at https://appgae-219421.appspot.com.
“Only the value of the E population seems to be statistically different from the metallicity of the primordial and intermediate components” [6].
A broker implementation report: http://bit.ly/2X31U6l.
A comparison study report: http://bit.ly/2Q0eS31.
We maintain a live experimental doc: http://bit.ly/2X7pKxH.
An example deployment cheatsheet: http://bit.ly/2K98fYn.
References
Baker M, Foxz G (1999) Metacomputing: harnessing informal supercomputers. In: Buyya R (ed) High performance cluster computing: architectures and Systems. Prentice-Hall, Englewood Cliffs, NJ, pp 1–42
Barabási AL, Freeh VW, Jeong H, Brockman JB (2001) Parasitic computing. Nature 412:984–897
Beberg AL, Ensign DL, Jayachandran G, Khaliq S, Pande VS (2009) Folding@home: lessons from eight years of volunteer distributed computing. In: Proceedings on 23rd international symposium on parallel & distributed processing (IPDPS 2009). IEEE Press, Rome, Italy, pp 1–8
Betz E (2010) Donated computer time discovers new star. https://www.insidescience.org/news/donated-computer-time-discovers-new-star
Blower JD (2010) GIS in the cloud: implementing a web map service on Google App Engine. In: Proceeding on 1st international conference on computing for geospatial research & application (COM.Geo 2010). ACM Press, Washington, D.C., USA, Article No. 34
Carretta E (2015) Five groups of red giants with distinct chemical composition in the globular cluster NGC 2808. Astrophys J 810(2):148
Carretta E, Bragaglia A, Gratton R, Lucatello S, Catanzaro G, Leone F, Bellazzini M, Claudi R, D’Orazi V, Momany Y, Ortolani S, Pancino E, Piotto G, Recio-Blanco A, Sabbi E (2009) Na-O anticorrelation and HB. VII. The chemical composition of first and second-generation stars in 15 globular clusters from GIRAFFE spectra. Astron Astrophys 505(1):117–138
CSIRO (2020) Obtaining astronomical spectra—spectrographs. http://www.atnf.csiro.au/outreach/education/senior/astrophysics/spectrographs.html
Cunsolo VD, Distefano S, Puliafito A, Scarpa M (2009) Volunteer computing and desktop cloud: the cloud@Home paradigm. In: Proceeding on 8th IEEE international symposium on network computing and applications (NCA 2009). IEEE Computer Society, Cambridge, MA, USA, pp 134–139
Durrani MN, Shamsi JA (2014) Volunteer computing: requirements, challenges, and solutions. J Netw Comput Appl 39:369–380
Elite Group (2018) Who owns the internet? https://www.elitegroup.com/news-and-insights/who-owns-the-internet/
Foster I (2003) The grid: a new infrastructure for 21st century science. In: Berman F, Fox G, Hey T (eds) Grid computing: making the global infrastructure a reality. Wiley, Chichester, pp 51–63
Foster I, Kesselman C, Tuecke S (2001) The anatomy of the grid: enabling scalable virtual organizations. Int J High Perform Comput Appl 15(3):200–222
Foster I, Zhao Y, Raicu I, Lu S (2008) Cloud computing and grid computing 360-degree compared. In: Proceeding on 2008 grid computing environments workshop (GCE 2008). IEEE Press, Austin, TX, USA, pp 1–10
GIMPS (2020) Great internet mersenne prime search. https://www.mersenne.org/
Jacob WJ, Gokbel V (2018) Global higher education learning outcomes and financial trends: comparative and innovative approaches. Int J Educ Dev 58:5–17
Kos B (2020) Disadvantages of grid computing described. https://www.brighthub.com/environment/green-computing/articles/107038.aspx
Li Z (2020) Using public and free Platform-as-a-Service (PaaS) based lightweight projects for software architecture education. In: Proceedings of the 42nd IEEE/ACM international conference on software engineering: software engineering education and training (ICSE-SEET 2020). ACM Press, Seoul, Republic of Korea, pp 1–11
Li Z, Guo X (2019) Do Google app engine’s runtimes perform homogeneously? An empirical investigation for bonus computing. IEEE Access 7:4698–4708
Li Z, O’Brien L, Ranjan R (2016) Cloud service evaluation. In: Murugesan S, Bojanova I (eds) Encyclopedia of cloud computing. Wiley-IEEE, Chichester, pp 349–360
Li Z, Chen Y, Rodríguez MA, Deng L (2018) Bonus computing: an evolution from and a supplement to volunteer computing. In: Proceedings of the 27th international conference on information systems development (ISD 2018). Association for Information Systems, Lund, Sweden, Article No. ISDevelopment/3
Malawski M, Kuźniar M, Wójcik P, Bubak M (2013) How to use Google App Engine for free computing. IEEE Internet Comput 17(1):50–59
Richmond M (2020) Emission and absorption lines. http://spiff.rit.edu/classes/phys301/lectures/spec_lines/spec_lines.html
Sarmenta LF, Hirano S (1999) Bayanihan: building and studying web-based volunteer computing systems using Java. Futur Gener Comput Syst 15(5–6):675–686
Sultan N (2010) Cloud computing for education: a new dawn? Int J Inf Manage 30(2):109–116
Typou TG, Margaritis KG (2003) Metacomputing: technology and applications. In: Bekakos MP (ed) Highly parallel computations: algorithms and applications. WIT Press, Ashurst, pp 69–108
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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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DOI: https://doi.org/10.1007/s00607-021-01036-3