TY - GEN
T1 - A context-aware approach for multimedia performance optimization using neural networks in wireless lan environments
AU - Lin, Po Chiang
AU - Wang, Chiapin
AU - Lin, Tsungnan
PY - 2006
Y1 - 2006
N2 - Packet size is one of the most important factors that would affect the user-perceived multimedia QoS in the wireless LAN environments. The time-varying channel characteristics make it difficult to find the exact relationship between the packet size and the throughput and decide an optimal packet size in advance. Furthermore, every node would suffer different channel conditions. In this paper, we tackle this problem by an optimization approach. A context-aware framework is designed to optimize the packet size adaptively in order to maximize the throughput. In this approach each node abstracts its specific context via the throughput from the time-varying wireless environments. The obtained throughput information is the instantaneous integrated effect of all contexts in wireless LAN environments. This approach adopts neural networks to learn the complex nonlinear function between the packet size and the throughput and adaptively adjusts the packet size. Simulation results show that out method can cope with the time-varying wireless channel conditions and improve the perceived QoS of wireless multimedia services.
AB - Packet size is one of the most important factors that would affect the user-perceived multimedia QoS in the wireless LAN environments. The time-varying channel characteristics make it difficult to find the exact relationship between the packet size and the throughput and decide an optimal packet size in advance. Furthermore, every node would suffer different channel conditions. In this paper, we tackle this problem by an optimization approach. A context-aware framework is designed to optimize the packet size adaptively in order to maximize the throughput. In this approach each node abstracts its specific context via the throughput from the time-varying wireless environments. The obtained throughput information is the instantaneous integrated effect of all contexts in wireless LAN environments. This approach adopts neural networks to learn the complex nonlinear function between the packet size and the throughput and adaptively adjusts the packet size. Simulation results show that out method can cope with the time-varying wireless channel conditions and improve the perceived QoS of wireless multimedia services.
UR - http://www.scopus.com/inward/record.url?scp=34247619864&partnerID=8YFLogxK
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U2 - 10.1109/ICME.2006.262746
DO - 10.1109/ICME.2006.262746
M3 - Conference contribution
AN - SCOPUS:34247619864
SN - 1424403677
SN - 9781424403677
T3 - 2006 IEEE International Conference on Multimedia and Expo, ICME 2006 - Proceedings
SP - 1177
EP - 1180
BT - 2006 IEEE International Conference on Multimedia and Expo, ICME 2006 - Proceedings
T2 - 2006 IEEE International Conference on Multimedia and Expo, ICME 2006
Y2 - 9 July 2006 through 12 July 2006
ER -