Mapping cloud computing in university e-governance system

Abstract

Purpose

The purpose of this paper is to propose a model to map the on-premise computing system of the university with cloud computing for achieving an effective and reliable university e-governance (e-gov) system.

Design/methodology/approach

The proposed model incorporates the university’s internal e-gov system with cloud computing in order to achieve better reliability, accessibility and availability of e-gov services while keeping the recurring expenditure low. This model has been implemented (and tested on a university e-gov system) in the University of Kashmir (UOK); case study of this implementation has been chosen as the research methodology to discuss and demonstrate the proposed model.

Findings

According to the results based on practical implementation, the proposed model is ideal for e-governed systems as it provided adequate cost savings and high availability (HA) with operational ease, apart from continuing to have the necessary security in place to maintain confidential information such as student details, grades, etc.

Practical implications

The implication of this study is to achieve HA and to reduce the cost from using external clouds, mapping internal IT servers of the university with the external cloud computing services.

Originality/value

Because no established mapping model for universities has been provided for effective, low-cost, highly available university e-gov system, the proposed mapping model through this paper closes this gap and provides guidelines to implement a hybrid-mapped e-gov model for universities while keeping the recurring expenditure on cloud computing minimal. The paper provides the perceptions of its adoption at UOK for achieving high reliability, accessibility and uptime of its e-gov applications while keeping the recurring expenditure on cloud computing minimal.

Citation

Qadri, M.N. and Quadri, S.M.K. (2018), "Mapping cloud computing in university e-governance system", International Journal of Intelligent Computing and Cybernetics, Vol. 11 No. 1, pp. 141-162. https://doi.org/10.1108/IJICC-11-2016-0048