Evaluating User Expectations and Quality of Service: A Novel Approach to Understanding Cloud Services
Jolly Upadhyaya1, Neelu Jyothi Ahuja2, Kapil Dev Sharma3
1Jolly Upadhyaya, Ph.D. Scholar, Department of Computer Science, UPES, Dehradun (Uttarakhand), India.
2Dr. Neelu Jyothi Ahuja, Professor, School of Computer Science, UPES, Dehradun (Uttarakhand), India.
3Kapil Dev Sharma, Assistant Professor, JIMSEMTC, Greater Noida (Uttar Pradesh), India.
Manuscript received on 08 February 2019 | Revised Manuscript received on 21 February 2019 | Manuscript Published on 04 March 2019 | PP: 381-385 | Volume-7 Issue-5S2 January 2019 | Retrieval Number: ES2069017519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Cloud Computing technology has revolutionized over the past decade as one of the fastest growing and adopted paradigm especially in the higher education sector. Its impact and popularity as a support system for learning is primarily based on the fact that it provides fast access to educational services and resources with high performance and support. At the same time, lack of institutional budgets, concerns for cyber security, and cost of technical and computer support continue to impact educational administration decision while adopting this enriched service. There is consensus that not enough consideration is given to the quality of cloud services experienced at the users’ end while pursuing such methods to fulfil the academic requirements. Currently, unavailability of a reliable standard model that effectively defines the “Quality of Experience,” QoE parameters from the users’ point of view impacts the recommendation of use for the cloud service across various educational institutions. Hence, it has become increasingly necessary to monitor, track, and quantify the variables influencing QoE for cloud computing-based e-learning applications and develop a new QoE Metrics Model. The current study was performed implementing quantitative method to collect and analyze the data received from various levels of educational institutions. The participants surveyed for study in the current work include students, librarians and faculties that were aware of cloud computing applications and services for higher education. Our study emphasized on variables like accessibility, demographics, age, income, educational status etc. and were statistically analyzed. The results of our study identified a correlation between the research questions and inferred hypotheses from them, leading to create an instrument that could be helpful in future as a diagnostic tool for the customer of cloud services, in academia. The implication of this study is to further help improve the qualitative process needed to identify the gap between user expectations and the experience of real quality of service (QoS)leading to build a reliable conceptual model for service evaluation in cloud computing.
Keywords: Cloud Computing; Higher Education; Metrics, Quality of Service (QoS), Quality of Experience (QoE).
Scope of the Article: Innovative Sensing Cloud and Systems