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传统的分布多跳式网络吞吐量的优化方法并不能满足用户高移动性、高数据速率的要求.为了提高分布多跳式网络吞吐量的优化性能,提出并实现了分布多跳式网络吞吐量的分布式并行优化算法.首先将分布多跳式网络等效成M/M/m级联排队系统,并用流水线技术实现了优化算法.然后研究了用户移动速度和网络环境对吞吐量的影响,并以此得出一般的近似最优的分布式算法.最后分析了多用户之间的干扰问题对网络吞吐量的影响.仿真结果表明,并行优化算法可以提高分布多跳式网络的吞吐量和降低通信时延;理论分析结果也说明了在某些情况下可将干扰看作高斯噪声.
Traditional distributed multi-hop network throughput optimization methods can not meet the requirements of high mobility and high data rate of users.In order to improve the throughput performance of distributed multi-hop networks, a distributed multi-hop network throughput is proposed and implemented Distributed parallel optimization algorithm.Firstly, the distributed multi-hop network is equivalent to the M / M / m cascade queuing system, and the optimization algorithm is realized by using the pipeline technology.Furthermore, the influence of user movement speed and network environment on the throughput is studied, Finally, the influence of multi-user interference on the network throughput is analyzed.The simulation results show that the parallel optimization algorithm can improve the throughput of the distributed multi-hop network and Reduce the communication delay; theoretical analysis also shows that in some cases interference can be regarded as Gaussian noise.