B. Horine, L. Bölöni, and D. Turgut. Distributed Decision Making in Cognitive Radio Networks Through Argumentation. In Proceedings of IEEE GLOBECOM'13, pp. 1231–1236, December 2013.
We have developed a multi-agent negotiation system to distribute decision making in cognitive radio networks through argumentation. The challenge in wireless network negotiation is to efficiently exchange information to facilitate a deal without incurring excessive communication overhead or indeterminate negotiation time. Our goal is to improve both total network throughput and the number of total supported connections. We detail a set of rules, a protocol, and a compact set of messages to conduct these negotiations and complete in finite time and with little overhead. We describe our simulation environment and present results of an illustrative scenario with various conditions. This scenario includes the ability of an agent to assert high priority, possibly triggering a downgrade of an existing, non-priority connection to a slower rate in order to accommodate more connections. We compare our system's total network throughput, number of connections, and request satisfaction score to several baselines with various levels of reconsideration and conclude that our system outperforms these other approaches in all metrics.
@inproceedings{Horine-2013-GLOBECOM, author = "B. Horine and L. B{\"o}l{\"o}ni and D. Turgut", title = "Distributed Decision Making in Cognitive Radio Networks Through Argumentation", booktitle = "Proceedings of IEEE GLOBECOM'13", pages = "1231--1236", month = "December", year = "2013", abstract = { We have developed a multi-agent negotiation system to distribute decision making in cognitive radio networks through argumentation. The challenge in wireless network negotiation is to efficiently exchange information to facilitate a deal without incurring excessive communication overhead or indeterminate negotiation time. Our goal is to improve both total network throughput and the number of total supported connections. We detail a set of rules, a protocol, and a compact set of messages to conduct these negotiations and complete in finite time and with little overhead. We describe our simulation environment and present results of an illustrative scenario with various conditions. This scenario includes the ability of an agent to assert high priority, possibly triggering a downgrade of an existing, non-priority connection to a slower rate in order to accommodate more connections. We compare our system's total network throughput, number of connections, and request satisfaction score to several baselines with various levels of reconsideration and conclude that our system outperforms these other approaches in all metrics. }, }
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