Revenue maximization of Internet of things provider using variable neighbourhood search (Q2022217)

Internet of things covers various aspects of collecting and exchanging data between diverse entities. One of the most significant issues is how to set the price that maximizes its revenue while meeting users' requirements. The authors focus on revenue maximization of the service provider by applying pay per use pricing within the combinatorial sealed-bid auction. Pay per use pricing option implies that each user is charged per unit of consumption according to the actual usage. They assume that a user pays a threshold price for a unit of consumption, which is determined based on the auction. The auction is conducted with bidding prices set up in advance within service level agreement. They use variable neighbourhood search in order to derive the optimal threshold price that maximizes the provider's revenue, and users' satisfaction. In addition, the optimization within the auction mechanism is conducted using different metaheuristics, which are compared with two types of algorithms.