Two-Timescale Hierarchical Contract for Joint Computation Offloading and Energy Management in Edge Computing System

To mitigate the rising energy costs in edge computing, edge servers (ESs) can receive revenues from reducing their energy usage by contracting with virtual power plant (VPP). ESs also respond to user equipment (UE) by providing computation offloading services. However, such two-layer coordinated trading of computation offloading and energy management in a VPP-ES-UE architecture should address the information asymmetry issue and uncertain task arrivals, posing challenges to maximizing the stakeholders' utility. In this paper, we formulate the two-layer coordinated trading as a hierarchical contracting problem, which addresses the information asymmetry using two contract models. We design a VPP-ES energy contract on a large timescale and an ES-UE computation contract on a small timescale, where ESs need to coordinate the future task arrivals under the energy reduction target assigned by VPP. We construct a two-timescale virtual queue to achieve the energy reduction goal by the long-term queue stability constraint and employ Lyapunov optimization to transform the original problem into an online optimization problem without requiring future information. An online two-timescale hierarchical contract optimization algorithm is proposed to solve the transformed problem. The simulation results demonstrate that our method achieves higher social welfare compared to other benchmarks.