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In this paper, we study the problem of resource allocation as well as pricingin the context of Internet of things (IoT) networks. We provide a novel pricingmodel for IoT services where all the parties involved in the communicationscenario as well as their revenue and cost are determined. We formulate theresource allocation in the considered model as a multi-objective optimizationproblem where in addition to the resource allocation variables, the pricevalues are also optimization variables. To solve the proposed multi-objectiveoptimization problem, we use the scalarization method which gives differentPareto optimal solutions. We solve the resulting problems using the alternatingapproach based on the successive convex approximation (SCA) method whichconverges to a local solution with few iterations. We also consider aconventional approach where each entity tries to maximize its own revenueindependently. Simulation results indicate that by applying the proposed jointframework, we can increase the total revenue compared to the conventional casewhile providing an almost complete fairness among the players. This is whilethe conventional approach fails to provide such a fairness.

Joint Dynamic Pricing and Radio Resource Allocation Framework for IoT Services