Sustainable Green SLA (GSLA) Validation using Bayesian Network Model

Abstract

Currently, most of the IT (Information Technology) and ICT (Information and Communication Technology) industries/companies provides their various services/product at a different level of customers/users through newly developed sustainable GSLA (Green Service Level Agreement). In addition, all these industries also designed new green services at their scope by using global sustainable GSLA informational model. The recent development of sustainable GSLA under 3Es (Ecology, Economy and Ethics) are assisting these IT and ICT based industries to practice sustainability by providing green services to their customers/users and thus respecting green computing paradigm. However, the evaluation of newly developed sustainable GSLA model is not validating yet. This research attempts to evaluate and validate the sustainable GSLA model by using Bayesian Network Model (BNM). The validation of using BNM is done with the feedback of 44 different IT and ICT based companies from Japan, India and Bangladesh. The average accuracy of using BNM for validating sustainable GSLA model is 68% while considering all sample data sets. Moreover, while the proposed BNM have higher confidence with entropy calculation, then the accuracy is almost 100% for most of the companies’ feedback. The proposed idea of using BNM for evaluating and validating sustainable GSLA model would definitely help the ICT engineer to design and develop future green services in their industries. Additionally, the evaluation also validates the proposed information sustainable GSLA model from previous research.

Authors and Affiliations

Iqbal Ahmed, Hiroshi Okumura, Kohei Arai, Osamu Fukuda

Keywords

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  • EP ID EP258762
  • DOI 10.14569/IJACSA.2017.080526
  • Views 110
  • Downloads 0

How To Cite

Iqbal Ahmed, Hiroshi Okumura, Kohei Arai, Osamu Fukuda (2017). Sustainable Green SLA (GSLA) Validation using Bayesian Network Model. International Journal of Advanced Computer Science & Applications, 8(5), 208-215. https://europub.co.uk/articles/-A-258762