A Location-allocation Model for Fog Computing Infrastructures

Thiago Alves de Queiroz, Claudia Canali, Manuel Iori, Riccardo Lancellotti

2020

Abstract

The trend of an ever-increasing number of geographically distributed sensors producing data for a plethora of applications, from environmental monitoring to smart cities and autonomous driving, is shifting the computing paradigm from cloud to fog. The increase in the volume of produced data makes the processing and the aggregation of information at a single remote data center unfeasible or too expensive, while latency-critical applications cannot cope with the high network delays of a remote data center. Fog computing is a preferred solution as latency-sensitive tasks can be moved closer to the sensors. Furthermore, the same fog nodes can perform data aggregation and filtering to reduce the volume of data that is forwarded to the cloud data centers, reducing the risk of network overload. In this paper, we focus on the problem of designing a fog infrastructure considering both the location of how many fog nodes are required, which nodes should be considered (from a list of potential candidates), and how to allocate data flows from sensors to fog nodes and from there to cloud data centers. To this aim, we propose and evaluate a formal model based on a multi-objective optimization problem. We thoroughly test our proposal for a wide range of parameters and exploiting a reference scenario setup taken from a realistic smart city application. We compare the performance of our proposal with other approaches to the problem available in literature, taking into account two objective functions. Our experiments demonstrate that the proposed model is viable for the design of fog infrastructure and can outperform the alternative models, with results that in several cases are close to an ideal solution.

Paper Citation

in Harvard Style

Alves de Queiroz T., Canali C., Iori M. and Lancellotti R. (2020). A Location-allocation Model for Fog Computing Infrastructures.In Proceedings of the 10th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, ISBN 978-989-758-424-4, pages 253-260. DOI: 10.5220/0009324702530260

in Bibtex Style

@conference{closer20,
author={Thiago Alves de Queiroz and Claudia Canali and Manuel Iori and Riccardo Lancellotti},
title={A Location-allocation Model for Fog Computing Infrastructures},
booktitle={Proceedings of the 10th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,},
year={2020},
pages={253-260},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009324702530260},
isbn={978-989-758-424-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,
TI - A Location-allocation Model for Fog Computing Infrastructures
SN - 978-989-758-424-4
AU - Alves de Queiroz T.
AU - Canali C.
AU - Iori M.
AU - Lancellotti R.
PY - 2020
SP - 253
EP - 260
DO - 10.5220/0009324702530260