TY - GEN
T1 - Local negotiation in cellular networks
T2 - 21st National Conference on Artificial Intelligence and the 18th Innovative Applications of Artificial Intelligence Conference, AAAI-06/IAAI-06
AU - Lin, Raz
AU - Dor-Shifer, Daphna
AU - Kraus, Sarit
AU - Sarne, David
PY - 2006
Y1 - 2006
N2 - This paper describes a novel negotiation protocol for cellular networks, which intelligently improves the performance of the network. Our proposed reactive mechanism enables the dynamic adaptation of the base stations to continuous changes in service demands, thereby improving the overall network performance. This mechanism is important when a frequent global optimization is infeasible or substantially costly. The proposed local negotiation mechanism is incorporated into a simulated network based on cutting-edge industry technologies. Experimental results suggest a rapid adjustment to changes in bandwidth demand and overall improvement in the number of served users over time. Although we tested our algorithm based on the service level, which is measured as the number of covered handsets, our algorithm supports negotiation for any set of parameters, aiming to optimize network's performance according to any measure of performance specified by the service provider.
AB - This paper describes a novel negotiation protocol for cellular networks, which intelligently improves the performance of the network. Our proposed reactive mechanism enables the dynamic adaptation of the base stations to continuous changes in service demands, thereby improving the overall network performance. This mechanism is important when a frequent global optimization is infeasible or substantially costly. The proposed local negotiation mechanism is incorporated into a simulated network based on cutting-edge industry technologies. Experimental results suggest a rapid adjustment to changes in bandwidth demand and overall improvement in the number of served users over time. Although we tested our algorithm based on the service level, which is measured as the number of covered handsets, our algorithm supports negotiation for any set of parameters, aiming to optimize network's performance according to any measure of performance specified by the service provider.
UR - http://www.scopus.com/inward/record.url?scp=33750712016&partnerID=8YFLogxK
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AN - SCOPUS:33750712016
SN - 1577352815
SN - 9781577352815
T3 - Proceedings of the National Conference on Artificial Intelligence
SP - 1801
EP - 1807
BT - Proceedings of the 21st National Conference on Artificial Intelligence and the 18th Innovative Applications of Artificial Intelligence Conference, AAAI-06/IAAI-06
Y2 - 16 July 2006 through 20 July 2006
ER -