Underwater sensor network（UWSN） adopts acoustic communication with more energy-consumption and longer propagation-delay, which bring great challenges to protocol design. In this paper, we proposed level-based adapti...Underwater sensor network（UWSN） adopts acoustic communication with more energy-consumption and longer propagation-delay, which bring great challenges to protocol design. In this paper, we proposed level-based adaptive geo-routing（LB-AGR） protocol. LB-AGR divides traffics into four categories, and routes different types of traffic in accordance with different decisions. Packets upstream to the sink are forwarded unicast to the best next-hop instead of broadcasting to all neighbor nodes as in present UWSN routing protocols. LB-AGR defines an integrated forwarding factor for each candidate node based on available energy, density, location, and level-difference between neighbor nodes, which is used to determine the best next-hop among multiple qualified candidates. Through simulation experiments, we show the promising performance of LB-AGR.展开更多
基金supported by the Program for New Century Excellent Talents in University of China(NCET-11-1025)the National Natural Science Foundation of China(61162003,61163050,6126104)+2 种基金Qinghai Office of Science and Technology(2012-Z-902)the National Basic Research Program of China(2011CB311809)the Natural Science Foundation of Tianjin(10JCYBJC00600)
文摘Underwater sensor network（UWSN） adopts acoustic communication with more energy-consumption and longer propagation-delay, which bring great challenges to protocol design. In this paper, we proposed level-based adaptive geo-routing（LB-AGR） protocol. LB-AGR divides traffics into four categories, and routes different types of traffic in accordance with different decisions. Packets upstream to the sink are forwarded unicast to the best next-hop instead of broadcasting to all neighbor nodes as in present UWSN routing protocols. LB-AGR defines an integrated forwarding factor for each candidate node based on available energy, density, location, and level-difference between neighbor nodes, which is used to determine the best next-hop among multiple qualified candidates. Through simulation experiments, we show the promising performance of LB-AGR.
