Double Auction Game-based Computing Resource Allocation in LEO Satellite System

Abstract

In the past few years, satellites have been widely influenced in our daily life, from Global Positioning System(GPS) to Military investigation. Due to the limitation of computation power and insufficient energy, the satellite has to offload their data to the ground station for further processing. However, long-range transmission has a great impact on many real-time services, such as hotspot tracing. As a remedy, in this paper, we introduce space stations to offload computation tasks of Low Earth Orbit(LEO) satellites to reduce the transmission delay. We formulate the problem of computing resource allocation between LEO satellites and space stations based on double auction mechanisms. Then, we describe an algorithm for searching Nash equilibrium based on Experience-Weighted Attraction(EWA) which is executed after each participant. Auction participants can obtain information from other adversaries and accumulate experience and reflection. So they can complete transactions with other participants in a fuzzy environment and maximize the overall benefit. Simulation results show the convergence and effectiveness of the algorithm.