Work place: Kunming military academy, Kunming, Yunnan, China
E-mail: kmchenli@21cn.com
Website:
Research Interests: Computer Networks, Network Architecture
Biography
Li Chen, received her B.S. Degree in Application Electric Technology from East China University of Science and Technology, Shanghai, China in 1998; She received her Master Degree in Communication and Information Systems from Chongqing University, Chongqing, China in 2008. She served as a lecturer at Kunming military academy now.
Her research interests include the areas of Broadband Wireless Mobile Communication, MIMO OFDM.
By Yong Liu Li Chen Lifeng Sun Shiqiang Yang
DOI: https://doi.org/10.5815/ijitcs.2010.01.08, Pub. Date: 8 Nov. 2010
It is a tremendous challenge to transmit real-time video streams over wireless sensor network because of the poor wireless communication conditions and the high requirements of video transmission. The opportunistic routing protocol can take advantage of the broadcast nature of wireless communication and can improve transfer throughput significantly. But the bigger size of transmission unit also increases the end-to-end delay at the same time. In order to overcome this problem and improve the real-time video transmission quality in wireless video sensor network, we propose a source adaptive frame discard algorithm for MAC-independent Opportunistic Routing & Encoding (MORE) Protocol in this paper. In our approach, the historical transmission delay is recorded to estimate current network transmission rate. Based on the video deadline, frames predicted to be delayed are discarded adaptively in the source node to get better overall video quality. In some practice application scenarios, there are usually need to deliver multiple video streams over multi-hop wireless network. It can’t work effectively with the originally MORE protocol in such scenarios. Furthermore, we modify the MORE protocol and design an adaptive scheme to support multiple video streams over multi-hop wireless video sensor network in this paper. The simulation results show that our algorithm can reduce frame loss rate and improve video quality significantly.
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