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The big data processing in distributed Internet of Things (IoT) systems callsfor innovative computing architectures and resource provisioning techniques tosupport real-time and cost-effective computing services. This articleintroduces a novel overbooking-promoted forward trading mechanism namedOverbook in Advance, Trade in Future (OATF), where computing resources can betraded across three parties, i.e. end-users, an edge server and a remote cloudserver, under a hybrid device-edge-cloud network with uncertainties (e.g., "noshows"). More importantly, OATF encourages a feasible overbooking rate thatallows the edge server to overbook resources to multiple end-users (e.g.,exceed the resource supply), while purchasing backup resources from the cloudserver, by determining rights and obligations associated with forward contractsin advance via analyzing historical statistics (e.g., network, resourcedynamics). Such a mechanism can greatly improve time efficiency and resourceutilization thanks to overbooking and pre-signed forward contracts. Criticalissues such as overbooking rate design and risk management are carefullyinvestigated in this article, while an interesting case study is proposed withmathematical analysis. Comprehensive simulations demonstrate that OATF achievesmutually beneficial utilities for different parties (cloud, edge, andend-users), as well as substantial resource usage and commendable timeefficiency, in comparison with conventional trading methods.

Overbook in Advance, Trade in Future: Computing Resource Provisioning in Hybrid Device-Edge-Cloud Networks