education services with the newest technology.
However, due to the economic crises experienced by
the countries especially with COVID19 pandemic,
the financial support for higher education institutions
has decreased. Thus, education continues to keep
pace with technology by available resources and
exploit them with the rapid development of
technology.
Accordingly, HEIs are quickly taking the
adoption of cloud technology to reduce the service
cost, to deliver more productivity in learning and
management process, and to offer higher responsive
for data retriever, to assist in decision-making. This
paper proposed CCC system solution that is defined
as the holistic adoption plan for cloud computing that
includes nine stages. In addition, this paper built a
questionnaire focused on the usage rate of using IT
among the academic and university staff. The
obtained result shows that more than 68% of
university staff are precipitate to use internet family
applications in their work. Nevertheless, they do not
have enough knowledge about the term cloud
computing.
Moreover, this study concludes that performance,
agility usage, and cost are basic parameters that
motivate the use of campus cloud technology in HEIs.
Therefore, CCC helps to provide an abundance in
cost, HR, time, and help the university staff to achieve
their tasks at anytime, anywhere. Our attempt enjoys
certain advantages when compared with the others,
especially concerning the adoption of the strategic
plan. It can be considered as the first campus cloud
environment that defines in detail the working
mechanism for each stage in the adoption plan.
Finally, this study opens the door for universities,
authors, and students to obtain the developing plan.
Also, authors going to develop a practical
environment of CCC using Hyper-V and
implementing it at the University of Fallujah.
REFERENCES
Njenga, K., Garg, L., Bhardwaj, A. K., Prakash, V., &
Bawa, S. (2019). The cloud computing adoption in
higher learning institutions in Kenya: Hindering factors
and recommendations for the way forward. Telematics
and Informatics, 38, 225-246.
Gao, F., & Sunyaev, A. (2019). Context matters: A review
of the determinant factors in the decision to adopt cloud
computing in healthcare. International Journal of
Information Management, 48, 120-138.
Kozák, Š. (2012, May). Advanced control engineering
methods in modern technological applications. In
Proceedings of the 13th International Carpathian
Control Conference (ICCC) (pp. 392-397). IEEE.
Restivo, M. T., Mendes, J., Lopes, A. M., Silva, C. M., &
Chouzal, F. (2009). A remote laboratory in engineering
measurement. IEEE transactions on industrial
electronics, 56(12), 4836-4843.
Sohaib, O., Naderpour, M., Hussain, W., & Martinez, L.
(2019). Cloud computing model selection for e-
commerce enterprises using a new 2-tuple fuzzy
linguistic decision-making method. Computers &
Industrial Engineering, 132, 47-58.
El-Haddadeh, R. (2020). Digital innovation dynamics
influence on organisational adoption: the case of cloud
computing services. Information Systems Frontiers,
22(4), 985-999.
Pardeshi, V. H. (2014). Cloud computing for higher
education institutes: architecture, strategy and
recommendations for effective adaptation. Procedia
Economics and Finance, 11, 589-599.
Okai, S., Uddin, M., Arshad, A., Alsaqour, R., & Shah, A.
(2014). Cloud computing adoption model for
universities to increase ICT proficiency. SAGE Open,
4(3), 2158244014546461.
Massadeh, S. A., & Mesleh, M. A. (2013). Cloud
Computing in Higher Education in Jordan. World of
Computer Science & Information Technology Journal,
3(2).
Attaran, M., Attaran, S., & Celik, B. G. (2017). Promises
and challenges of cloud computing in higher education:
a practical guide for implementation. Journal of Higher
Education Theory and Practice, 17(6), 20-38.
Guo, Q. Y. (2013). The Design of Universities Resource-
Sharing Network Teaching System Based on Cloud
Computing. In Applied Mechanics and Materials (Vol.
397, pp. 2430-2434). Trans Tech Publications Ltd.
Bildosola, I., Río-Belver, R., Cilleruelo, E., & Garechana,
G. (2015). Design and implementation of a cloud
computing adoption decision tool: Generating a cloud
road. PloS one, 10(7), e0134563.
Ali, O., Shrestha, A., Osmanaj, V., & Muhammed, S.
(2020). Cloud computing technology adoption: an
evaluation of key factors in local governments.
Information Technology & People.
Mohammad, O. K. J. (2018, June). Recent Trends of Cloud
Computing Applications and Services in Medical,
Educational, Financial, Library and Agricultural
Disciplines. In Proceedings of the 4th International
Conference on Frontiers of Educational Technologies
(pp. 132-141).
Kogias, D. G., Xevgenis, M. G., & Patrikakis, C. Z. (2016).
Cloud federation and the evolution of cloud computing.
Computer, 49(11), 96-99.
Dong, T., Ma, Y., & Liu, L. (2012). The application of
cloud computing in universities’ education information
resources management. In Information Engineering and
Applications (pp. 938-945). Springer, London.
Chakravarthi, K. K., & Vijayakumar, V. (2018). Workflow
scheduling techniques and algorithms in IaaS cloud: a
survey. International Journal of Electrical and
Computer Engineering, 8(2), 853.