Scheduling services on an IoT device under time-weighted pricing

The emerging vision of smart cities necessitates the use of Internet of Things (IoT) network devices to implement sustainable solutions that will improve the operations of urban areas. A massive amount of smart cities services may demand allocation of computational resources, such as processing power or storage, that IoT devices offer. Within this context, we present an IoT network device comprising interfaces with one specific computational resource available. The efficient utilization of available IoT resources would improve the Quality of Service (QoS) of the IoT network that serves the smart city. All resource allocations must be completed within a given scheduling window and every service is parametrized by a pricing weight function to indicate its tolerance to be served at the beginning of the scheduling window. We propose a mathematical optimization formulation to minimize the total cost of allocating all demands within the scheduling window considering the tolerance level of each service at the same time. Moreover, we prove that the problem is computationally hard and we provide numerical results to gain insight into the impact of different pricing weight functions on the allocations' distribution within the scheduling window.