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Dynamic Pricing of Edge Cooperative Offloading Using a Simple Heuristic

In this paper, we study a dynamic pricing of edge cooperative offloading scenario in a multi-periods system that maximizes the total expected discounted profit of requesting MEC server over a finite horizon. Keeping track of the pricing decisions in each of the resource scheduling waiting time gives rise to the curse of dimensionality. In order to deal with the curse-of-dimensionality problem, we apply a simple heuristic algorithm. The idea of the heuristic stems from analytical findings which suggest that the shape of the myopic price is close to that of the optimal pricing policy. We firstly introduce the myopic price as the heuristic resource pricing policy, which is a function of the expected resource request quantity. For further simplified calculation, we then construct a linear approximation to the myopic expected resource request, which is a function of the initial computing resource of requesting MEC server. Finally, we illustrate the heuristic resource pricing and data offloading policy in detail. The proposed algorithm can transform a recurrence summation optimization problem into a single-period optimization, and efficiently make a decision of resource pricing and data offloading policy in collaborative computation offloading scenario. Simulation results show that the proposed algorithm is near-optimal.