  Cloud-aided mobile edge networks (CAMENs) allow edge servers (ESs) to
purchase resources from remote cloud servers (CSs), while overcoming resource
shortage when handling computation-intensive tasks of mobile users (MUs).
Conventional trading mechanisms (e.g., onsite trading) confront many
challenges, including decision-making overhead (e.g., latency) and potential
trading failures. This paper investigates a series of cross-layer matching
mechanisms to achieve stable and cost-effective resource provisioning across
different layers (i.e., MUs, ESs, CSs), seamlessly integrated into a novel
hybrid paradigm that incorporates futures and spot trading. In futures trading,
we explore an overbooking-driven aforehand cross-layer matching (OA-CLM)
mechanism, facilitating two future contract types: contract between MUs and
ESs, and contract between ESs and CSs, while assessing potential risks under
historical statistical analysis. In spot trading, we design two backup plans
respond to current network/market conditions: determination on contractual MUs
that should switch to local processing from edge/cloud services; and an onsite
cross-layer matching (OS-CLM) mechanism that engages participants in real-time
practical transactions. We next show that our matching mechanisms theoretically
satisfy stability, individual rationality, competitive equilibrium, and weak
Pareto optimality. Comprehensive simulations in real-world and numerical
network settings confirm the corresponding efficacy, while revealing remarkable
improvements in time/energy efficiency and social welfare.
