  Mobile edge computing (MEC) has become a promising solution to utilize
distributed computing resources for supporting computation-intensive vehicular
applications in dynamic driving environments. To facilitate this paradigm, the
onsite resource trading serves as a critical enabler. However, dynamic
communications and resource conditions could lead unpredictable trading
latency, trading failure, and unfair pricing to the conventional resource
trading process. To overcome these challenges, we introduce a novel
futures-based resource trading approach in edge computing-enabled internet of
vehicles (IoV), where a forward contract is used to facilitate resource trading
related negotiations between an MEC server (seller) and a vehicle (buyer) in a
given future term. Through estimating the historical statistics of future
resource supply and network condition, we formulate the futures-based resource
trading as the optimization problem aiming to maximize the seller's and the
buyer's expected utility, while applying risk evaluations to relieve possible
losses incurred by the uncertainties in the system. To tackle this problem, we
propose an efficient bilateral negotiation approach which facilitates the
participants reaching a consensus. Extensive simulations demonstrate that the
proposed futures-based resource trading brings considerable utilities to both
participants, while significantly outperforming the baseline methods on
critical factors, e.g., trading failures and fairness, negotiation latency and
cost.
