  In this paper, we study the problem of resource allocation as well as pricing
in the context of Internet of things (IoT) networks. We provide a novel pricing
model for IoT services where all the parties involved in the communication
scenario as well as their revenue and cost are determined. We formulate the
resource allocation in the considered model as a multi-objective optimization
problem where in addition to the resource allocation variables, the price
values are also optimization variables. To solve the proposed multi-objective
optimization problem, we use the scalarization method which gives different
Pareto optimal solutions. We solve the resulting problems using the alternating
approach based on the successive convex approximation (SCA) method which
converges to a local solution with few iterations. We also consider a
conventional approach where each entity tries to maximize its own revenue
independently. Simulation results indicate that by applying the proposed joint
framework, we can increase the total revenue compared to the conventional case
while providing an almost complete fairness among the players. This is while
the conventional approach fails to provide such a fairness.
