DSpace Repository

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

Show simple item record

dc.contributor.author Chamola, Vinay
dc.date.accessioned 2023-03-15T10:23:59Z
dc.date.available 2023-03-15T10:23:59Z
dc.date.issued 2020-01
dc.identifier.uri https://www.sciencedirect.com/science/article/pii/S014036641930948X#d1e1074
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/9752
dc.description.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. en_US
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.subject EEE en_US
dc.subject Directed acyclic graph en_US
dc.subject Unmanned aerial vehicles en_US
dc.subject Internet of Drones (IoD) en_US
dc.subject Distributed applications en_US
dc.subject Smart charging en_US
dc.title Scheduling drone charging for multi-drone network based on consensus time-stamp and game theory en_US
dc.type Article en_US


Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record

Search DSpace


Advanced Search

Browse

My Account