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Incomplete Information based Collaborative Computing in Emergency Communication Networks
IEEE Communications Letters ( IF 3.7 ) Pub Date : 2020-09-01 , DOI: 10.1109/lcomm.2020.2995501
Qianqian Wang , Yongxu Zhu , Xianbin Wang

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 two-tier 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.

中文翻译:

应急通信网络中基于不完备信息的协同计算

由于救灾的紧迫性和不可预测性,应急管理系统 (EMS) 在没有来自应急通信网络 (ECN) 的完整信息的情况下面临着实时数据分析的巨大挑战。在这封信中,我们提出了一种基于不完全信息的两层博弈模型(IITG)来实现 ECN 边缘的协同计算,通过最大化 EMS 和 ICD 的效用来激励空闲计算设备(ICD)共享计算资源。此外,我们开发了一种近乎最优的 IITG 算法 (N-IITG) 来寻求独特的贝叶斯纳什均衡。仿真结果表明,N-IITG 在计算延迟和参与者效用方面优于现有的基于不完整信息的方法。
更新日期:2020-09-01
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