  The big data processing in distributed Internet of Things (IoT) systems calls
for innovative computing architectures and resource provisioning techniques to
support real-time and cost-effective computing services. This article
introduces a novel overbooking-promoted forward trading mechanism named
Overbook in Advance, Trade in Future (OATF), where computing resources can be
traded across three parties, i.e. end-users, an edge server and a remote cloud
server, under a hybrid device-edge-cloud network with uncertainties (e.g., "no
shows"). More importantly, OATF encourages a feasible overbooking rate that
allows the edge server to overbook resources to multiple end-users (e.g.,
exceed the resource supply), while purchasing backup resources from the cloud
server, by determining rights and obligations associated with forward contracts
in advance via analyzing historical statistics (e.g., network, resource
dynamics). Such a mechanism can greatly improve time efficiency and resource
utilization thanks to overbooking and pre-signed forward contracts. Critical
issues such as overbooking rate design and risk management are carefully
investigated in this article, while an interesting case study is proposed with
mathematical analysis. Comprehensive simulations demonstrate that OATF achieves
mutually beneficial utilities for different parties (cloud, edge, and
end-users), as well as substantial resource usage and commendable time
efficiency, in comparison with conventional trading methods.
