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Agile optimization for a real‐time facility location problem in Internet of Vehicles networks
Author(s) -
Martins Leandro do C.,
Tarchi Daniele,
Juan Angel A.,
Fusco Alessandro
Publication year - 2022
Publication title -
networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.977
H-Index - 64
eISSN - 1097-0037
pISSN - 0028-3045
DOI - 10.1002/net.22067
Subject(s) - computer science , agile software development , benchmark (surveying) , process (computing) , quality of service , the internet , optimization problem , operations research , distributed computing , mathematical optimization , real time computing , computer network , engineering , algorithm , software engineering , world wide web , mathematics , geodesy , geography , operating system
The uncapacitated facility location problem (UFLP) is a popular NP‐hard optimization problem that has been traditionally applied to logistics and supply networks, where decisions are difficult to reverse. However, over the years, many new application domains have emerged, in which real‐time optimization is needed, such as Internet of Vehicles (IoV), virtual network functions placement, and network controller placement. IoV scenarios take into account the presence of multiple roadside units (RSUs) that should be frequently assigned to operating vehicles. To ensure the desired quality of service level, the allocation process needs to be carried out frequently and efficiently, as vehicles' demands change. In this dynamic environment, the mapping of vehicles to RSUs needs to be reoptimized periodically over time. Thus, this article proposes an agile optimization algorithm, which is tested using existing benchmark instances. The experiments show that it can efficiently generate high‐quality and real‐time results in dynamic IoV scenarios.