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Minimizing E-Waste Through Improved Virtualization

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Intelligent Computing & Optimization (ICO 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 569))

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Abstract

Consumption of electronics has increased in recent decades and become increasingly important. Consumer demand and ongoing technical advancement cause a serious problem as a consequence of this need and consumption. One of the issues now plaguing the world that is growing the quickest is E-waste. This article looks at how virtualization may abate the amount of e-waste produced and save resources. A comparison of E-waste management strategies and the optimal choice taking into account green computing has been shown. The model, which uses annual product sales data as well as historical and projected sales data as inputs, is a material flow analysis model. Future sales data are predicted using polynomial regression analysis for goods with increasing yearly sales and the sales rate for products with declining annual sales. Software that enables a single computer to perform several identical executions, each of which runs an operating system, is known as a hypervisor, or virtual machine monitor. By using those resources and the information from the models, the overall discussion on virtualization’s potential to reduce e-waste may be evaluated. As fewer portable computers and desktop computers are used, less electrical equipment is needed, which reduces the amount of power required. The hypervisor may also be set up to show how much less electronic waste results from virtualization. Therefore, even if virtualization won’t completely eradicate e-waste, it will significantly reduce it while having no negative effects on the environment.

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Correspondence to Ahmed Wasif Reza or Mohammad Shamsul Arefin .

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Liza, M.A., Suny, A., Shahjahan, R.M.B., Reza, A.W., Arefin, M.S. (2023). Minimizing E-Waste Through Improved Virtualization. In: Vasant, P., Weber, GW., Marmolejo-Saucedo, J.A., Munapo, E., Thomas, J.J. (eds) Intelligent Computing & Optimization. ICO 2022. Lecture Notes in Networks and Systems, vol 569. Springer, Cham. https://doi.org/10.1007/978-3-031-19958-5_97

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