This paper explores an extended applications’ cost function to model the willingness of Edge data centres to accommodate additional users in decentralized edge computing environments. By enhancing the Marginal Computing Cost per User (MCU) concept, we introduce a dynamic cost factor influenced by the number of users currently served. Through extensive simulations conducted on the PureEdgeSim platform, we evaluate the impact of this variable MCU on system performance across various configurations. The results reveal a critical trade-off between cost sensitivity (i.e., collaboration willingness) of Edge data centres and optimization potential. This work offers insights into user allocation strategies in heterogeneous edge systems and sets the stage for future research into non-linear MCU configurations and diverse application workloads.
Marginal cost of computation as a collaborative strategy for resource management at the edge
Carlini E.;Mordacchini M.
2025
Abstract
This paper explores an extended applications’ cost function to model the willingness of Edge data centres to accommodate additional users in decentralized edge computing environments. By enhancing the Marginal Computing Cost per User (MCU) concept, we introduce a dynamic cost factor influenced by the number of users currently served. Through extensive simulations conducted on the PureEdgeSim platform, we evaluate the impact of this variable MCU on system performance across various configurations. The results reveal a critical trade-off between cost sensitivity (i.e., collaboration willingness) of Edge data centres and optimization potential. This work offers insights into user allocation strategies in heterogeneous edge systems and sets the stage for future research into non-linear MCU configurations and diverse application workloads.File | Dimensione | Formato | |
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Marginal_Cost_of_Computation.pdf
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Descrizione: This is the Submitted version (preprint) of the following paper: Carlini E. et al. “Marginal Cost of Computation as a Collaborative Strategy for Resource Management at the Edge”, 2025, submitted to 20th International Conference on the Economics of Grids, Clouds, Systems, and Services. The final published version is available on the publisher’s website https://link.springer.com/chapter/10.1007/978-3-031-81226-2_3.
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