A Contract-Based Incentive Mechanism for Resources Trading in Computing Force Networks

Recently, Computing Force Networks (CFN) is emerging to deeply integrate and flexibly schedule multi-layer, multi-domain, distributed, and heterogeneous computing force resources among the cloud, edge network, and end devices. In CFN, the market monopoly of large resource providers results in a lack of bargaining power for small-sized providers. Existing resources pricing strategies ignore dynamic market factors affecting prices. Moreover, there is information asymmetry between resource consumers and providers. These problems destroy the fairness of the trading market and damage the benefits of consumers and providers, making them have a low degree of willingness to participate in resources trading. Therefore, this paper proposes a contract theory-based incentive mechanism to solve the above problems and motivate resource consumers and providers to join CFN. The proposed scheme classifies resource commodities into different types and enables the trading platform to provide appropriate rewards based on commodities' types and contributions. More specifically, we formulate an optimization problem aiming at maximizing the trading platform's utility and obtain an optimal contract scheme based on the individual rationality and incentive compatible constraints. Simulation results verify the feasibility and effectiveness of our scheme.