An Incentive Framework for Task Offloading in Edge Computing Marketplaces Under Price Competition

To efficiently execute tasks, computation resource requesters (CRRs) with limited resources can offload their tasks to nearby computation resource providers (CRPs) with spare computing capacity. These CRPs require appropriate incentives to compensate for their incurred costs when helping process the offloaded tasks. Although several mechanisms have been designed to incentivize CRPs, none of them have investigated the incentive mechanism considering price-setting and price-taking CRPs simultaneously. In this work, we propose an incentive framework for task offloading in the edge computing marketplace that includes both price-setting and price-taking CRPs. We model the CRR's interactions with both types of CRPs as a three-stage Stackelberg game to maximize the profit for both the CRR and CRPs. We prove the existence of a unique subgame perfect equilibrium (SPE) of the formulated game and further develop iterative algorithms for the CRR and price-setting CRPs to achieve the equilibrium. Through the designed algorithms, each CRP does not require complete information about the CRR and other CRPs. Extensive simulations demonstrate that offloading tasks to both price-setting and price-taking CRPs achieves higher profits for the CRR and price-setting CRPs compared to offloading tasks solely to price-setting CRPs. Additionally, the obtained SPE can achieve near-optimal social welfare.