Reference : Mobility-Driven and Energy-Efficient Deployment of Edge Data Centers in Urban Environments
Scientific journals : Article
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/46403
Mobility-Driven and Energy-Efficient Deployment of Edge Data Centers in Urban Environments
English
Vitello, Piergiorgio mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE) >]
Capponi, Andrea mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS) >]
Fiandrino, Claudio [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Cantelmo, Guido [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
Kliazovich, Dzmitry [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Feb-2021
IEEE Transactions on Sustainable Computing
Yes
International
[en] Multi-access Edge computing ; urban computing ; energy efficiency
[en] Multi-access Edge Computing (MEC) brings storage and computational capabilities at the edge of the network into so-called Edge Data Centers (EDCs) to better support low-latency applications. In this paper, we tackle the problem of EDC deployment in urban environments. Previous research on mobile phone data has exposed a strong correlation between the demand for mobile communications and the urban tissue. For example, joint analysis of mobile data and vehicle traffic can be extrapolated to estimate demand for transportation and human activities, thereby inferring the land use of the area where such activities take place. Our work takes into account the mobility of citizens and their spatial patterns to estimate the optimal placement of MEC EDCs in urban environments, in order to minimize outages while guaranteeing energy-efficiency. This is achieved by modeling both the energy consumption attributed to network components (e.g., base stations) and computing components (e.g., servers). We propose and compare three heuristics and show that mobility-aware deployments achieve superior performance. The results are obtained with a custom-designed simulator able to operate over large-scale realistic urban environments.
http://hdl.handle.net/10993/46403
10.1109/TSUSC.2021.3056621
https://www.computer.org/csdl/journal/su/5555/01/09346057/1qV2M42tjB6

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