![](bg8.png)
REFERENCES
Amazon Web Services Inc. (2020). AWS Cost Explorer
- Amazon Web Services. https://aws.amazon.com/
aws-cost-management/aws-cost-explorer/. Accessed:
2020-08-27.
Anderson, B. (2020). Quickstart - Explore Azure
costs with cost analysis. https://docs.microsoft.
com/en-us/azure/cost-management-billing/costs/
quick-acm-cost-analysis. Accessed: 2020-08-27.
Arcentry Inc. (2020). Arcentry: Create Interactive Cloud
Diagrams. https://arcentry.com/. Accessed: 2020-08-
27.
Averbukh, V., Bakhterev, M., Baydalin, A., Ismagilov, D.,
and Trushenkova, P. (2007). Interface and visualiza-
tion metaphors. In Proc. 12th Intl. Conf. on Human-
Computer Interaction, pages 13–22, Beijing, China.
Springer.
Beloglazov, A., Abawajy, J., and Buyya, R. (2012). Energy-
aware resource allocation heuristics for efficient man-
agement of data centers for cloud computing. Future
generation computer systems, 28(5):755–768.
Beloglazov, A. and Buyya, R. (2010). Energy efficient al-
location of virtual machines in cloud data centers. In
Proc. 10th IEEE/ACM Intl. Conf. on Cluster, Cloud
and Grid Computing, pages 577–578.
Berl, A., Gelenbe, E., Di Girolamo, M., Giuliani, G.,
De Meer, H., Dang, M. Q., and Pentikousis, K. (2010).
Energy-efficient cloud computing. The Computer
Journal, 53(7):1045–1051.
Bladh, T., Carr, D. A., and Scholl, J. (2004). Extending tree-
maps to three dimensions: A comparative study. In
Proc. Asia-Pacific Conf. on Computer Human Interac-
tion, pages 50–59, Rotorua, New Zealand. Springer.
Caldiera, V. R. B. G. and Rombach, H. D. (1994). The goal
question metric approach. Encyclopedia of software
engineering, pages 528–532. Wiley-Interscience.
Cloudcraft Inc. (2020). Cloudcraft - Draw AWS diagrams.
https://www.cloudcraft.co. Accessed: 2020-08-27.
Cloudviz Solutions SIA (2020). Cloudviz – Automated
AWS Architecture Diagrams & Documentation. https:
//cloudviz.io/. Accessed: 2020-08-27.
Duit, R. (1991). On the role of analogies and metaphors in
learning science. Science education, 75(6):649–672.
Fang, W., Liang, X., Li, S., Chiaraviglio, L., and Xiong,
N. (2013). VMPlanner: Optimizing virtual machine
placement and traffic flow routing to reduce network
power costs in cloud data centers. Computer Net-
works, 57(1):179–196.
Fittkau, F., Waller, J., Wulf, C., and Hasselbring, W. (2013).
Live trace visualization for comprehending large soft-
ware landscapes: The ExplorViz approach. In Proc.
IEEE Working Conf. on Softw. Vis., pages 1–4, Eind-
hoven, The Netherlands.
Google Inc. (2020). Visualize spend over time with Google
Data Studio - Cloud Billing. https://cloud.google.
com/billing/docs/how-to/visualize-data. Accessed:
2020-08-27.
Hogr
¨
afer, M., Heitzler, M., and Schulz, H.-J. (2020). The
state of the art in map-like visualization. Computer
Graphics Forum, 39(3):647–674.
Kondo, D., Javadi, B., Malecot, P., Cappello, F., and An-
derson, D. P. (2009). Cost-benefit analysis of cloud
computing versus desktop grids. In Proc. IEEE Intl.
Symp. on Parallel & Distributed Processing, pages 1–
12, Rome, Italy.
Li, J., Shuang, K., Su, S., Huang, Q., Xu, P., Cheng, X.,
and Wang, J. (2012). Reducing operational costs
through consolidation with resource prediction in the
cloud. In Proc. 12th IEEE/ACM Intl. Symp. on Cluster,
Cloud and Grid Computing, pages 793–798, Ottawa,
Canada.
Long, L. K., Hui, L. C., Fook, G. Y., and Zainon, W. M.
N. W. (2017). A study on the effectiveness of tree-
maps as tree visualization techniques. Procedia Com-
puter Science, 124:108–115.
Lucid Software Inc. (2020). Visualize Your Cloud
Infrastructure. https://www.lucidchart.com/blog/
why-visualize-your-cloud-infrastructure. Accessed:
2020-08-27.
Martens, B., Walterbusch, M., and Teuteberg, F. (2012).
Costing of cloud computing services: A total cost of
ownership approach. In Proc. 45th Hawaii Intl. Conf.
on System Sciences, pages 1563–1572, Maui, HI.
Nanath, K. and Pillai, R. (2013). A model for cost-benefit
analysis of cloud computing. International Technol-
ogy and Information Management, 22(3):93–117.
Schulz, H.-J., Hadlak, S., and Schumann, H. (2010). The
design space of implicit hierarchy visualization: A
survey. IEEE transactions on visualization and com-
puter graphics, 17(4):393–411.
Shastri, S. and Irwin, D. (2018). Cloud index tracking:
Enabling predictable costs in cloud spot markets. In
Proc. ACM Symp. on Cloud Computing, pages 451–
463, Carlsbad, CA.
Steinbr
¨
uckner, F. and Lewerentz, C. (2010). Representing
Development History in Software Cities. In Proc. 5th
Intl. Symp. on Softw. Vis., pages 193–202, Salt Lake
City, UT.
Teyseyre, A. and Campo, M. (2008). An Overview of 3D
Software Visualization. IEEE Trans. Visual. Comput.
Graphics, 15(1):87–105.
UMAknow Solutions Inc. (2020). Cloudockit – Generate
your cloud documentation. https://www.cloudockit.
com/. Accessed: 2020-08-27.
Vieira, C. C., Bittencourt, L. F., and Madeira, E. R. (2014).
Reducing costs in cloud application execution using
redundancy-based scheduling. In Proc. IEEE/ACM
7th Intl. Conf. on Utility and Cloud Computing, pages
117–126, Washington, DC.
Wettel, R. and Lanza, M. (2007). Visualizing software sys-
tems as cities. In Proc. 4th IEEE Intl. Workshop on
Vis. Softw. Understanding Anal., pages 92–99, Banff,
Canada.
Zohar, E., Cidon, I., and Mokryn, O. (2011). The power
of prediction: Cloud bandwidth and cost reduction.
ACM SIGCOMM Computer Communication Review,
41(4):86–97.
IVAPP 2021 - 12th International Conference on Information Visualization Theory and Applications
180