Uncertain edge coalition game based EIP revenue estimation strategy

Abstract

In the edge computing environment, there are risks such as communication channel risks and edge server failures, which can lead to a mismatch between the computing resources required for task processing and the resources allocated by the edge coalition. In response, a revenue forecasting method for the edge coalition and its member edge infrastructure provider (EIP) based on the game theory of uncertain coalition structures was proposed. Firstly, a resource scheduling model was constructed using a mixed integer linear programming method to maximize the revenue of the edge coalition. Secondly, a belief structure was introduced to characterize the probabilities of high, medium, low, and unknown scenarios for the coalition's revenue. Finally, the uncertain Owen value was used to estimate the interval revenue of the EIP in the coalition one time slot in advance. The simulation results show that the accuracy of this forecasting method under the two risks of channel risk and server failure is 91.25% and 82.5% respectively, with an average accuracy of 86.88%, achieving a relatively accurate forecast of the EIP’ revenue.

Keywords

• edge computing
• uncertain coalition structure game
• belief structure
• uncertain Owen value
• revenue estimation