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Estimating the Energy Consumption of Applications in the Computing Continuum with iFogSim

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High Performance Computing (ISC High Performance 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13999))

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Abstract

Digital services - applications that often span the entire computing continuum - have become an essential part of our daily lives, but they can have a significant energy cost, raising sustainability concerns. The computing continuum features multiple distributed layers (edge, fog, and cloud) with specific computing infrastructure and scheduling decisions at each layer, which impact the overall quality of service and energy consumption of digital services. Measuring the energy consumption of such applications is challenging due to the distributed nature of the system and the application. As such, simulation techniques are promising solutions to estimate energy consumption, and several simulators are available for modeling the cloud and fog computing environment.

In this paper, we investigate iFogSim’s effectiveness in analyzing the end-to-end energy consumption of applications in the computing continuum through two case studies. We design different scenarios for each case study to map application modules to devices along the continuum, including the Edge-Cloud collaboration architecture, and compare them with the two placement policies native to iFogSim: Cloud-only and Edge-ward policies. We observe iFogSim’s limitations in reporting energy consumption, and improve its ability to report energy consumption from an application’s perspective; this enables additional insight into an application’s energy consumption, thus enhancing the usability of iFogSim in evaluating the end-to-end energy consumption of digital services.

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Correspondence to Saeedeh Baneshi .

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Baneshi, S., Varbanescu, AL., Pathania, A., Akesson, B., Pimentel, A. (2023). Estimating the Energy Consumption of Applications in the Computing Continuum with iFogSim. In: Bienz, A., Weiland, M., Baboulin, M., Kruse, C. (eds) High Performance Computing. ISC High Performance 2023. Lecture Notes in Computer Science, vol 13999. Springer, Cham. https://doi.org/10.1007/978-3-031-40843-4_18

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  • DOI: https://doi.org/10.1007/978-3-031-40843-4_18

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