Agile optimization for a real‐time facility location problem in Internet of Vehicles networks. Issue 4 (11th June 2021)

• Record Type: Journal Article
• Authors: Martins, Leandro do C.; Tarchi, Daniele; Juan, Angel A.; Fusco, Alessandro
• Is Part Of: Networks. Volume 79:Issue 4(2022)
• Page Start: 501
• Page End: 514
• Publication Date: 2021-06-11
• Subjects: agile optimization -- biased‐randomized heuristics -- Internet of Vehicles -- real‐time optimization -- smart cities -- uncapacitated facility location problem; Network analysis (Planning) -- Periodicals; 658.4032
• DOI: 10.1002/net.22067
• Languages: English
• ISSNs: 0028-3045

Abstract

Abstract: 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.