  Mobile edge computing (MEC) has emerged as one of the key technical aspects
of the fifth-generation (5G) networks. The integration of MEC with
resource-constrained unmanned aerial vehicles (UAVs) could enable flexible
resource provisioning for supporting dynamic and computation-intensive UAV
applications. Existing resource trading could facilitate this paradigm with
proper incentives, which, however, may often incur unexpected negotiation
latency and energy consumption, trading failures and unfair pricing, due to the
unpredictable nature of the resource trading process. Motivated by these
challenges, an efficient futures-based resource trading mechanism for edge
computing-assisted UAV network is proposed, where a mutually beneficial and
risk-tolerable forward contract is devised to promote resource trading between
an MEC server (seller) and a UAV (buyer). Two key problems i.e. futures
contract design before trading and power optimization during trading are
studied. By analyzing historical statistics associated with future resource
supply, demand, and air-to-ground communication quality, the contract design is
formulated as a multi-objective optimization problem, aiming to maximize both
the seller's and the buyer's expected utilities, while estimating their
acceptable risk tolerance. Accordingly, we propose an efficient bilateral
negotiation scheme to help players reach a trading consensus on the amount of
resources and the relevant price. For the power optimization problem, we
develop a practical algorithm that enables the buyer to determine its optimal
transmission power via convex optimization techniques. Comprehensive
simulations demonstrate that the proposed mechanism offers both players
considerable utilities, while outperforming the onsite trading mechanism on
trading failures and fairness, negotiation latency, and cost.
