TY - GEN
T1 - Distributed Multi-agent Negotiation for Wi-Fi Channel Assignment
AU - Tejedor-Romero, Marino
AU - Murukannaiah, Pradeep K.
AU - Gimenez-Guzman, Jose Manuel
AU - Marsa-Maestre, Ivan
AU - Jonker, Catholijn M.
N1 - Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
PY - 2023
Y1 - 2023
N2 - Channel allocation in dense, decentralized Wi-Fi networks is a challenging due to the highly nonlinear solution space and the difficulty to estimate the opponent’s utility model. So far, only centralized or mediated approaches have succeeded in applying negotiation to this setting. We propose the first two fully-distributed negotiation approaches for Wi-Fi channel assignment. Both of them leverage a pre-sampling of the utility space with simulated annealing and a noisy estimation of the Wi-Fi utility function. Regarding negotiation protocols, one of the approaches makes use of the Alternating Offers protocol, while the other uses the novel Multiple Offers Protocol for Multilateral Negotiations with Partial Consensus (MOPaC), which naturally matches the problem peculiarities. We compare the performance of our proposed approaches with the previous mediated approach, based on simple text mediation. Our experiments show that our approaches yield better utility outcomes, better fairness and less information disclosure than the mediated approach.
AB - Channel allocation in dense, decentralized Wi-Fi networks is a challenging due to the highly nonlinear solution space and the difficulty to estimate the opponent’s utility model. So far, only centralized or mediated approaches have succeeded in applying negotiation to this setting. We propose the first two fully-distributed negotiation approaches for Wi-Fi channel assignment. Both of them leverage a pre-sampling of the utility space with simulated annealing and a noisy estimation of the Wi-Fi utility function. Regarding negotiation protocols, one of the approaches makes use of the Alternating Offers protocol, while the other uses the novel Multiple Offers Protocol for Multilateral Negotiations with Partial Consensus (MOPaC), which naturally matches the problem peculiarities. We compare the performance of our proposed approaches with the previous mediated approach, based on simple text mediation. Our experiments show that our approaches yield better utility outcomes, better fairness and less information disclosure than the mediated approach.
KW - Automated negotiation
KW - Simulated annealing
KW - Wi-Fi networks
UR - http://www.scopus.com/inward/record.url?scp=85151094025&partnerID=8YFLogxK
U2 - 10.1007/978-981-99-0561-4_1
DO - 10.1007/978-981-99-0561-4_1
M3 - Conference contribution
AN - SCOPUS:85151094025
SN - 9789819905607
T3 - Studies in Computational Intelligence
SP - 3
EP - 14
BT - Recent Advances in Agent-Based Negotiation
A2 - Hadfi, Rafik
A2 - Ito, Takayuki
A2 - Arisaka, Ryuta
A2 - Aydoğan, Reyhan
PB - Springer
T2 - 13th International Workshop on Automated Negotiations, ACAN 2022 held in conjunction with 31st International Joint Conference on Artificial Intelligence, IJCAI 2022
Y2 - 22 July 2022 through 29 July 2022
ER -