An adaptive task scheduler for a cloud of drones

Thumbnail Image
10266.pdf(3.31 MB)
Accepted version
Alshareef, Hazzaa N.
Grigoras, Dan
Journal Title
Journal ISSN
Volume Title
Institute of Electrical and Electronics Engineers (IEEE)
Research Projects
Organizational Units
Journal Issue
Drones are now being widely used in different civilian applications, such as delivering shipments to consumers, as proposed by Amazon, and providing internet access to users, as offered by Facebook and Google. Drones can also contribute in emergencies by helping to find victims in places that are not reachable by rescuers, as well as assisting emergency centers to better manage a reported emergency. However, drones have a short flying time due to limited battery life. Therefore, a reliable strategy that minimizes energy consumption and uses collaborative working is required in order to increase drones' ability to operate for longer periods in emergency situations. This paper presents an adaptive task scheduler that allows tasks to be shared/transferred among the drones in a cloud of drones, in order to extend the operational time, achieve faster task execution and, at the same time, reduce the usage of each drone's resources. The ultimate result is an extension of battery life that leads to longer flying and service time for individual drones.
Aerospace computing , Aerospace robotics , Cloud computing , Groupware , Mobile computing , Multi-robot systems , Remotely operated vehicles , Scheduling , Adaptive task scheduler , Mobile cloud , Drone resources , Collaborative working , Energy consumption , Internet access , Cloud of drones , Civilian applications , Drones , Task analysis , Batteries , Streaming media , Protocols , Collaboration , Emergency , Battery power , Task scheduling , Services
Alshareef, H. N. and Grigoras, D. (2018) 'An adaptive task scheduler for a cloud of drones'. 2018 4th International Conference on Cloud Computing Technologies and Applications (Cloudtech), Brussels, Belgium, 26-28 Nov., pp. 1-8. doi: 10.1109/CloudTech.2018.8713336
© 2018 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.