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Title	Mobility-Driven And Energy-Efficient Deployment Of Edge Data Centers In Urban Environments
ID_Doc	37384
Authors	Vitello P.; Capponi A.; Fiandrino C.; Cantelmo G.; Kliazovich D.
Year	2022
Published	IEEE Transactions on Sustainable Computing, 7, 4
DOI	http://dx.doi.org/10.1109/TSUSC.2021.3056621
Abstract	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. © 2016 IEEE.
Author Keywords	energy efficiency; Multi-access Edge computing; urban computing

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