Work

Computing power networks for unmanned aerial vehicles: a hierarchical resources trading market

Year: 2025

Type: article

Abstract: Unmanned Aerial Vehicles (UAVs) are increasingly deployed across military and civilian domains due to their operational flexibility, low maintenance costs, and high mobility. With the growing complexity of UAV applications and tasks, robust support from computing power networks is essential. These networks, acting as resource integration paradigms, furnish UAVs with pooled resources to tackle extensive computational demands. In this paper, we develop a framework for trading computing power resources, modeling the transaction process through a three-stage Stackelberg game to facilitate sequential decision-making. We theoretically demonstrate the existence of a Nash equilibrium and introduce a Dynamic Game Reinforcement algorithm to identify optimal strategies. Our experimental results affirm the framework's efficacy and the superior performance of our algorithm. Additionally, we explore how variables like UAV quantity and network congestion influence the market dynamics of the computing power network.

Source: Digital Communications and Networks

DOI: 10.1016/j.dcan.2024.12.002

Authors: Xiaofei Wang, Hui Deng, Chao Qiu, Zheyuan Chen, Tao Luo, Zhao Ming

Institutions: Tianjin University, China Telecom (China), University of Oulu

Language: English

Topic: IoT and Edge/Fog Computing

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $800