Revenue maximization of Internet of things provider using variable neighbourhood search
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Revenue maximization of Internet of things provider using variable neighbourhood search Vesna Radonji´c ¯Dogatovi´c1 Nenad Mladenovi´c2
· Marko ¯Dogatovi´c1 · Milorad Stanojevi´c1 ·
Received: 31 March 2019 / Accepted: 18 February 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Internet of things (IoT) covers various aspects of collecting and exchanging data between diverse entities. From IoT provider’s perspective, one of the most significant issues is how to set the price that maximizes its revenue while meeting users’ requirements. In this paper, we focus on revenue maximization of the IoT 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. We 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 (SLA). We use variable neighbourhood search (VNS) in order to derive the optimal threshold price that maximizes IoT 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 VNS algorithms. Keywords Variable neighbourhood search · Metaheuristics · Auction · Revenue · Internet of things
1 Introduction Internet of things (IoT) is defined as a global infrastructure for the information society, enabling advanced services by interconnecting physical and virtual things based on existing and evolving interoperable information and communication technologies [17]. IoT ecosystems are complex environments encompassing many heterogeneous components. The huge amount of data generated by sensor-instrumented objects of the real world in an IoT ecosystem will impose a great demand for processing and storage resources to be transformed
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Vesna Radonji´c ¯Dogatovi´c [email protected]
1
Faculty of Traffic and Transport Engineering, University of Belgrade, Vojvode Stepe 305, Belgrade 11000, Serbia
2
Department of Industrial and Systems Engineering, Research Center on Digital Supply Chain and Operations Management, Khalifa University, Abu Dhabi, UAE
123
Journal of Global Optimization
into useful information or services. Some applications are latency sensitive, whereas other applications require complex processing including historical data and time series analyses. One of the major challenges of an IoT service provider is efficiently managing resources, and set prices in order to maximize its revenue/profit while meeting users’ requirements. When IoT provider starts a business, maximizing revenue is the preferable option instead of profit maximization in order to build a reputation in the market. Pursuing revenue maximization can also be a wise way to increase long-term profitability by gaining a larger market share. Resource allocation implies that a provider
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