Research Article
A selfish approach to coalition formation among unmanned air vehicles in wireless networks
@INPROCEEDINGS{10.1109/GAMENETS.2009.5137409, author={Walid Saad and Zhu Han and Tamer Basar and Merouane Debbah and Are Hj\`{u}rungnes}, title={A selfish approach to coalition formation among unmanned air vehicles in wireless networks}, proceedings={1st International Conference on Game Theory for Networks}, publisher={IEEE}, proceedings_a={GAMENETS}, year={2009}, month={6}, keywords={}, doi={10.1109/GAMENETS.2009.5137409} }
- Walid Saad
Zhu Han
Tamer Basar
Merouane Debbah
Are Hjørungnes
Year: 2009
A selfish approach to coalition formation among unmanned air vehicles in wireless networks
GAMENETS
IEEE
DOI: 10.1109/GAMENETS.2009.5137409
Abstract
Autonomous agents such as unmanned aerial vehicles (UAVs) have a great potential for deployment in next generation wireless networks. While current literature has been mainly focused on the use of UAVs for connectivity enhancement and routing in military ad hoc networks, this paper proposes a novel usage model for UAVs in wireless communication networks. In the proposed model, a number of UAVs are required to collect data from a number of randomly located tasks and transmit this data wirelessly to a common receiver (such as the central command). Each task represents a queue of packets that require collection and transmission to the central receiver. This problem is modeled as a hedonic coalition formation game between the UAVs and the tasks that interact in order to form disjoint coalitions. Each formed coalition is modeled as a polling system consisting of a number of UAVs, designated as collectors, which act as a single server that moves between the different tasks present in the coalition, collects and transmits the packets to a common receiver. Within each coalition, some UAVs might also take the role as a relay for improving the packet success rate of the transmission. The proposed coalition formation algorithm allows the tasks and the UAVs to take local selfish decisions to join or leave a coalition, based on the achieved benefit, in terms of effective throughput, and the cost in terms of delay. Simulation results show how the proposed algorithm allows the UAVs and tasks to self-organize into independent coalitions, while improving the performance, in terms of average player (UAV or task) payoff, of at least 30.26% relatively to a scheme that allocates nearby tasks equally among UAVs.