Incomplete Information based Collaborative Computing in Emergency Communication Networks

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Due to the urgent and unpredictable nature of disaster relief, emergency management systems (EMS) faces an enormous challenge of real-time data analysis without the complete information from emergency communication networks (ECNs). In this letter, we propose an incomplete information based twotier game model (IITG) to realize collaborative computing at the edge of ECNs, which incentivizes idle computing devices (ICDs) to share computation resources through maximizing utilities of EMS and ICDs. Furthermore, we develop a near-optimal IITG algorithm (N-IITG) to seek the unique Bayesian Nash equilibrium. Simulation results reveal that N-IITG outperforms the existing incomplete information based methods in terms of computation latency and participants utilities.