The current trend of the modern smart cities applications towards a continuous increase in the volume of produced data and the concurrent need for low and predictable latency in the response time has motivated the shift from a cloud to a fog computing approach. A fog computing architecture is likely to represent a preferable solution to reduce the application latency and the risk of network congestion by decreasing the volume of data transferred to cloud data centers. However, the design of a fog infrastructure opens new issues concerning not only how to allocate the data flow coming from sensors to fog nodes and from there to cloud data centers, but also the choice of the number and the location of the fog nodes to be activated among a list of potential candidates. We model this facility location issue through a multi-objective optimization problem. We propose a heuristic based on the variable neighborhood search, where neighborhood structures are based on swap and move operations. The proposed method is tested in a wide range of scenarios, considering a smart city application’s realistic setup with geographically distributed sensors. The experimental evaluation shows that our method can achieve stable and better performance concerning other literature approaches, supporting the given application.

A Variable Neighborhood Heuristic for Facility Locations in Fog Computing / Alves de Queiroz, T.; Canali, C.; Iori, M.; Lancellotti, R.. - 12559:(2021), pp. 28-42. ((Intervento presentato al convegno 8th International Conference on Variable Neighborhood Search, ICVNS 2021 tenutosi a are nel 2021 [10.1007/978-3-030-69625-2_3].

A Variable Neighborhood Heuristic for Facility Locations in Fog Computing

Canali C.;Iori M.;Lancellotti R.
2021

Abstract

The current trend of the modern smart cities applications towards a continuous increase in the volume of produced data and the concurrent need for low and predictable latency in the response time has motivated the shift from a cloud to a fog computing approach. A fog computing architecture is likely to represent a preferable solution to reduce the application latency and the risk of network congestion by decreasing the volume of data transferred to cloud data centers. However, the design of a fog infrastructure opens new issues concerning not only how to allocate the data flow coming from sensors to fog nodes and from there to cloud data centers, but also the choice of the number and the location of the fog nodes to be activated among a list of potential candidates. We model this facility location issue through a multi-objective optimization problem. We propose a heuristic based on the variable neighborhood search, where neighborhood structures are based on swap and move operations. The proposed method is tested in a wide range of scenarios, considering a smart city application’s realistic setup with geographically distributed sensors. The experimental evaluation shows that our method can achieve stable and better performance concerning other literature approaches, supporting the given application.
8th International Conference on Variable Neighborhood Search, ICVNS 2021
are
2021
12559
28
42
Alves de Queiroz, T.; Canali, C.; Iori, M.; Lancellotti, R.
A Variable Neighborhood Heuristic for Facility Locations in Fog Computing / Alves de Queiroz, T.; Canali, C.; Iori, M.; Lancellotti, R.. - 12559:(2021), pp. 28-42. ((Intervento presentato al convegno 8th International Conference on Variable Neighborhood Search, ICVNS 2021 tenutosi a are nel 2021 [10.1007/978-3-030-69625-2_3].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1241578
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