Scalability analysis comparisons of cloud-based software services
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Scalability analysis comparisons of cloud-based software services
LITERATURE REVIEW 2
Benchmark -Literature Review
Joshua Odusola-Stephen COM-355: Communication Research Methods Grand Canyon University September 9, 2021
Literature Review
Scalability analysis comparisons of cloud-based software services
The coronavirus pandemic has had numerous economic, political, and social impacts. The result has been a surge in demand for internet connections at various workplaces attempt to adapt to the new social norms.
Though numerous companies have demonstrated their potential in sustaining economic activities, the education sector negatively affected student academic performance. It is noteworthy that many learning
institutions suspended activities due to the state mandate to limit the spread of the disease. Thus, numerous hypotheses were proposed with the limited information available on the social impact of the disease.
Regardless, to better understand the role of cloud computing in the education sector, the research will employ a mixed-method approach. In other words, it will implement both qualitative and quantitative strategies.
The purpose is to have a detailed appreciation of the problem, making it more straightforward to devise effective solutions. The information will also include the scope of the problem, thus allowing for better
prioritization. Therefore, to achieve effective data collection, statistical assessments and surveys will be employed.
The study will implement a cross-sectional survey involving assessing data from a population-based on variables critical to the task. The methodology will be divided into three sections, namely:
- Survey development, which will focus on the procedure responsible for developing the survey questions. For example, some questions from previous studies may be used to preserve historical data. Moreover, the survey questions will target academic performance appraisal, among other attributed critical in appreciating the scope and details of the problem.
- Survey application: addresses the approach through which the survey questions will be distributed to collect enough and reliable data. Moreover, it will also focus on the target population for the survey.
- Data statistical Analysis: the phase will address the proper processing tools needed to understand the data. Depending on the number of variables targeted, numerous statistical techniques may be required. Thus, it will determine if the study is multivariate or univariate.
Nevertheless, though the primary approach of the study will provide the needed data for the effective execution of the research, it will also exploit data from other researchers. Some data include a 2017 statistical
evaluation of the cloud computing market assessing its overall growth (Alsmadi & Prybutok, 2018). The data identified that the technology was slowly assimilated in various industries, with healthcare portraying the
greatest demand. However, Tuli et al. (2020) state that with the onset of the pandemic, the demand for cloud services rose by over 40%. It has been attributed to the rise in demand for big data and data analytics
which are essential for organizational or industrial changes through decision-making. It was mostly exploited by the retail sector, which was among the few industries with the positive financial outcomes of the
pandemic (Al-Said Ahmad & Andras, 2019). Nevertheless, supported by the low implementation requirements and high-cost effectiveness, Stergiou et al. (2018) stated the technology will continue being sought after in various sectors.
According to (), cloud computing has significantly evolved in the past decade, and its availability has been able to meet the demand. With over 30% of companies and institutions in various industries dependent on
cloud computing, the trend is expected to continue growing, offering opportunities for other industries (Wang, 2021). It is noteworthy that though the research will rely on primary data to better understand the
pandemic on students, secondary data will also be implemented. The objective is to appreciate both primary and secondary data in developing solutions for students. According to Varghese and Buyya (2018), cloud
computing is a global trend that significantly changes the business landscape with on-demand computing services.
Some services offered include application, storage, and processing power. They are provided over the internet with pay-as-you-go services. Cloud computing operates by offering consumers computing and database
infrastructure for clients to rent as they access the storage and applications provided by cloud services (Qasem et al., 2019). Such services benefit companies because they avoid initial costs and complexities
associated with owning and maintaining IT infrastructures. In turn, cloud service providers benefit from economies of scale, thus offering services at lower prices thus attracting numerous consumers.
The argument is supported by data from various researchers such as Qasem et al. (2019), identifying that cloud computing has numerous applications in all industries. In addition, the argument is founded on the rise
in demand for cloud computing services in various sectors, including public education. The author states that the technology has been progressively developing to meet demands in the current IT environment. However, the pandemic augmented the demand for cloud services as more people became reliant on the internet for work due to movement and interaction restrictions (Alashhab et al., 2021).
Zhang et al. (2019) support the notion by identifying the healthcare sector, government agencies, manufacturing sector, and the retail industry as having the greatest demand for cloud computing services. Though the
data does not directly address public education, the researcher states that the diverse applicability of cloud computing services can augment development and performance (Zhang et al., 2019). By exploiting the
available tools, proactive data analysis can allow for the effective exploitation of available resources. An example provided is how the agricultural sector can help farmers better understand their environment by
providing data on crop production and harvest, resulting in the exploitation of IoTs in increasing yield (van Eyk et al., 2018). In other words, from a qualitative perspective, the implementation of cloud computing is
essential in the development of the education sector. By taking advantage of the communication channels provided by technology, students will access information and resources essential for their performance.
References
Alashhab, Z. R., Anbar, M., Singh, M. M., Leau, Y., Al-Sai, Z. A., & Abu Alhayja’a, S. (2021). Impact of coronavirus pandemic crisis on technologies and cloud computing applications. Journal of Electronic Science and Technology, 19(1), 100059. doi: 10.1016/j.jnlest.2020.100059
Al-Said Ahmad, A., & Andras, P. (2019). Scalability analysis comparisons of cloud-based software services. Journal of Cloud Computing: Advances, Systems and Applications, 8(1), 1-17. doi:10.1186/s13677-019-0134-y
Alsmadi, D., & Prybutok, V. (2018). Sharing and storage behavior via cloud computing: Security and privacy in research and practice. Computers in Human Behavior, 85, 218-226. doi: 10.1016/j.chb.2018.04.003
Qasem, Y. A. M., Abdullah, R., Jusoh, Y. Y., Atan, R., & Asadi, S. (2019). Cloud computing adoption in higher education institutions: A systematic review. IEEE Access, 7, 63722-63744. doi:10.1109/ACCESS.2019.2916234
Stergiou, C., Psannis, K. E., Gupta, B. B., & Ishibashi, Y. (2018). Security, privacy & efficiency of sustainable cloud computing for big data & IoT. Sustainable Computing Informatics and Systems, 19, 174-184. doi: 10.1016/j.suscom.2018.06.003
Tuli, S., Tuli, S., Tuli, R., & Gill, S. S. (2020). Predicting the growth and trend of COVID-19 pandemic using machine learning and cloud computing. Internet of Things, 11, 100222. doi: 10.1016/j.iot.2020.100222
Van Eyk, E., Toader, L., Talluri, S., Versluis, L., Uta, A., & Iosup, A. (2018). Serverless is more: From PaaS to present cloud computing. doi:10.1109/MIC.2018.053681358
Varghese, B., & Buyya, R. (2018). Next generation cloud computing: new trends and research directions. Future Generation Computer Systems, 79, 849-861. doi: 10.1016/j.future.2017.09.020
Wang, X. (Jun 28, 2021). Introducing cloud data technology into economic statistics. Paper presented at the 865-869. doi:10.1109/IWCMC51323.2021.9498770 Retrieved from https://ieeexplore.ieee.org/document/9498770
Zhang, S., Byrnes, A. P., Jankovic, J., & Neilly, J. (2019, Mar). Management, analysis, and simulation of micrographs with cloud computing. Microscopy Today, 27, 26-33. doi:10.1017/S1551929519000026 Retrieved from https://dx.doi.org/10.1017/S1551929519000026
RUBRIC
Excellent Quality
95-100%
Introduction 45-41 points
The background and significance of the problem and a clear statement of the research purpose is provided. The search history is mentioned.
Literature Support
91-84 points
The background and significance of the problem and a clear statement of the research purpose is provided. The search history is mentioned.
Methodology
58-53 points
Content is well-organized with headings for each slide and bulleted lists to group related material as needed. Use of font, color, graphics, effects, etc. to enhance readability and presentation content is excellent. Length requirements of 10 slides/pages or less is met.
Average Score
50-85%
40-38 points
More depth/detail for the background and significance is needed, or the research detail is not clear. No search history information is provided.
83-76 points
Review of relevant theoretical literature is evident, but there is little integration of studies into concepts related to problem. Review is partially focused and organized. Supporting and opposing research are included. Summary of information presented is included. Conclusion may not contain a biblical integration.
52-49 points
Content is somewhat organized, but no structure is apparent. The use of font, color, graphics, effects, etc. is occasionally detracting to the presentation content. Length requirements may not be met.
Poor Quality
0-45%
37-1 points
The background and/or significance are missing. No search history information is provided.
75-1 points
Review of relevant theoretical literature is evident, but there is no integration of studies into concepts related to problem. Review is partially focused and organized. Supporting and opposing research are not included in the summary of information presented. Conclusion does not contain a biblical integration.
48-1 points
There is no clear or logical organizational structure. No logical sequence is apparent. The use of font, color, graphics, effects etc. is often detracting to the presentation content. Length requirements may not be met
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