Scheduling drone charging for multi-drone network based on consensus time-stamp and game theory

Abstract

Drones or Unmanned Aerial Vehicles (UAVs) can be highly efficient in various applications like hidden area exploration, delivery, or surveillance and can enhance the quality of experience (QoE) for end-users. However, the number of drone-based applications are not very high due to the constrained flight time. The weights of the drones need to be kept less, and intuitively they cannot be loaded with big batteries. Frequent recharging and battery replacement processes limit the appropriate use of drones in most applications. A peer-to-peer distributed network of drones and charging stations is a highly promising solution to empower drones to be used in multiple applications by increasing their flight time. The charging stations are limited, and therefore, an adequate, fair, and cost-optimal scheduling algorithm is required to serve the most needed drone first. The proposed model allows the drones to enter into the network and request for a charging time slot from the station. The stations are also the part of the same network, this work proposes a scheduling algorithm for drones who compete for charging slots with constraints of optimizing criticality and task deadline. A game-theoretic approach is used to model the energy trading between the drones and charging station in a cost-optimal manner. Numerical results based on simulations show that the proposed model provides a better price for the drones to get charged and better revenue for the charging stations simultaneously.