RT info:eu-repo/semantics/conferenceObject
T1 Multi-agent nonlinear negotiation for Wi-Fi channel assignment
A1 Hoz de la Hoz, Enrique de la
A1 Marsá Maestre, Iván
A1 Giménez Guzmán, José Manuel
A1 Orden Martín, David
A1 Klein, Mark
AB Optimizing resource use in complex networks with self-interested participants (e.g. transportation networks, electric grids, Internet systems) is a challenging and increasingly critical real-world problem. We propose an approach for solving this problem based on multi-agent nonlinear negotiation, and demonstrate it in the context of Wi-Fi channel assignment.We compare the performance of our proposed approaches with a complete information optimizer based on particle swarms, together with the \emph{de facto} heuristic technique based on using the least congested channel. We have evaluated all these techniques in a wide range of settings, including randomly generated scenarios and real-world ones.Our experiments show that our approach outperforms the rest of techniques in terms of social welfare.The particle swarm optimizer is the only technique whose performance is close to ours, but its computation cost is much higher. Finally, we also study the effect of some graphs metrics on the gain that our approach can achieve.
PB International Foundation for Autonomous Agents and Multiagent Systems
YR 2017
FD 2017-05-08
LK http://hdl.handle.net/10017/28998
UL http://hdl.handle.net/10017/28998
LA eng
NO AAMAS 2017 - Sixteenth International Conference on Autonomous Agents and Multiagent Systems, 08/05/2017-12/05/2017, Sao Paulo, Brasil.
NO Ministerio de Economía y Competitividad
DS MINDS@UW
RD 19-abr-2024