In wireless ad hoe network environments, every link is wireless and every node is mobile. Those features make data lost easily as well as multicasting inefficient and unreliable. Moreover, Efficient and reliable multi...In wireless ad hoe network environments, every link is wireless and every node is mobile. Those features make data lost easily as well as multicasting inefficient and unreliable. Moreover, Efficient and reliable multicast in wireless ad hoe network is a difficult issue. It is a major challenge to transmission delays and packet losses due to link changes of a multicast tree at the provision of high delivery ratio for each packet transmission in wireless ad hoe network environment. In this paler, we propose and evaluate Reliable Adaptive Multicast Protocol （RAMP） based on a relay node concept. Relay nodes are placed along the multieast tree. Data recovery is done between relay nodes. RAMP supports a reliable multicasting suitable for mobile ad hoe network by reducing the number of packet retransmissions. We compare RAMP with SRM （Scalable Reliable Multicast）. Simulation results show that the RAMP has high delivery ratio and low end-to-end delay for packet transmsission.展开更多
For wireless ad hoc networks simulation, node＇s mobility pattern and traffic pattern are two key elements. A new simulation model is presented based on the virtual reality collision detection algorithm in obstacle en...For wireless ad hoc networks simulation, node＇s mobility pattern and traffic pattern are two key elements. A new simulation model is presented based on the virtual reality collision detection algorithm in obstacle environment, and the model uses the path planning method to avoid obstacles and to compute the node＇s moving path. Obstacles also affect node＇s signal propagation. Considering these factors, this study implements the mobility model for wireless ad hoc networks. Simulation results show that the model has a significant impact on the performance of protocols.展开更多
认知无线Ad hoc网络(cognitive wireless ad hoc networks)是由一组具有认知决策能力的节点以多跳无线方式组成的智能网络.网络容量的求解与网络吞吐量的优化是该类网络研究的难点.作者首先推导了混叠模式下认知无线Ad hoc网络容量上界...认知无线Ad hoc网络(cognitive wireless ad hoc networks)是由一组具有认知决策能力的节点以多跳无线方式组成的智能网络.网络容量的求解与网络吞吐量的优化是该类网络研究的难点.作者首先推导了混叠模式下认知无线Ad hoc网络容量上界的闭合表达式,并指出该上界只与用户空间分布特性相关;然后提出了一种新的基于遗传算法的跨层优化算法,通过联合优化邻居选择与功率分配实现网络吞吐量的最大化;最后仿真验证了该算法的有效性,结果表明网络吞吐量能较好地逼近网络容量上界.展开更多
文摘In wireless ad hoe network environments, every link is wireless and every node is mobile. Those features make data lost easily as well as multicasting inefficient and unreliable. Moreover, Efficient and reliable multicast in wireless ad hoe network is a difficult issue. It is a major challenge to transmission delays and packet losses due to link changes of a multicast tree at the provision of high delivery ratio for each packet transmission in wireless ad hoe network environment. In this paler, we propose and evaluate Reliable Adaptive Multicast Protocol （RAMP） based on a relay node concept. Relay nodes are placed along the multieast tree. Data recovery is done between relay nodes. RAMP supports a reliable multicasting suitable for mobile ad hoe network by reducing the number of packet retransmissions. We compare RAMP with SRM （Scalable Reliable Multicast）. Simulation results show that the RAMP has high delivery ratio and low end-to-end delay for packet transmsission.
文摘For wireless ad hoc networks simulation, node＇s mobility pattern and traffic pattern are two key elements. A new simulation model is presented based on the virtual reality collision detection algorithm in obstacle environment, and the model uses the path planning method to avoid obstacles and to compute the node＇s moving path. Obstacles also affect node＇s signal propagation. Considering these factors, this study implements the mobility model for wireless ad hoc networks. Simulation results show that the model has a significant impact on the performance of protocols.
文摘认知无线Ad hoc网络(cognitive wireless ad hoc networks)是由一组具有认知决策能力的节点以多跳无线方式组成的智能网络.网络容量的求解与网络吞吐量的优化是该类网络研究的难点.作者首先推导了混叠模式下认知无线Ad hoc网络容量上界的闭合表达式,并指出该上界只与用户空间分布特性相关;然后提出了一种新的基于遗传算法的跨层优化算法,通过联合优化邻居选择与功率分配实现网络吞吐量的最大化;最后仿真验证了该算法的有效性,结果表明网络吞吐量能较好地逼近网络容量上界.
