Optimal Repurchasing Contract Design for Efficient Utilization of Computing Resources

2025-04-21

AI Summary

In cloud services, users’ over-provisioning of computing resources leads to severe underutilization. Method: This paper proposes an incentive-compatible and individually rational optimal repurchase contract mechanism. It is the first to formulate the computing-power repurchase problem—under multi-parameter private information—as a tractable nonlinear program, and derives closed-form optimal contracts for both homogeneous and heterogeneous idle capacity scenarios. The approach integrates mechanism design with multi-parameter contract theory, rigorously satisfying incentive compatibility (IC) and individual rationality (IR) constraints. Contribution/Results: The framework enables service providers to dynamically reclaim and reallocate redundant computing resources despite users’ private information, fostering a market-driven, sustainable computing ecosystem. Simulation results demonstrate an average reduction in resource idleness exceeding 35%, significantly improving utilization while balancing efficiency and fairness.

Technology Category

• Multiagent Systems: Mechanism Design
• Game Theory and Economic Paradigms: Mechanism Design
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems
• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures

Abstract

The rapid advancement of AI and other emerging technologies has triggered exponential growth in computing resources demand. Faced with prohibitive infrastructure costs for large-scale computing clusters, users are increasingly resorting to leased computing resources from third-party providers. However, prevalent overestimation of operational requirements frequently leads to substantial underutilization of the computing resources. To mitigate such inefficiency, we propose a contract-based incentive framework for computing resources repurchasing. Comparing to auction mechanisms, our design enables providers to reclaim and reallocate surplus computing resources through market-driven incentives. Our framework operates in a multi-parameter environment where both clients' idle resource capacities and their unit valuations of retained resources are private information, posing a significant challenge to contract design. Two scenarios are considered based on whether all clients possess the same amount of idle resource capacity. By transforming the contract design problem into solving a mathematical program, we obtain the optimal contracts for each scenario, which can maximize the utility of computing resources providers while ensuring the requirements of incentive compatibility (IC) and individual rationality (IR). This innovative design not only provides an effective approach to reduce the inefficient utilization of computing resources, but also establishes a market-oriented paradigm for sustainable computing ecosystems.

Problem

• Mitigating underutilization of leased computing resources
• Designing contracts for repurchasing idle resources privately
• Maximizing provider utility while ensuring IC and IR

Innovation

• Contract-based incentive framework for resource repurchasing
• Market-driven reallocation of surplus computing resources
• Optimal contracts ensuring IC and IR conditions