摘要
针对无线Ad Hoc网络由于带宽限制和自组织的特点,容易导致网络负载过重产生拥塞问题,提出了基于贝叶斯网络的固定码率(CBR)发送速率调整的拥塞控制算法。该算法通过对影响网络拥塞状态的参数进行贝叶斯网络学习;然后,使用获得的贝叶斯网络(BN)对拥塞状态进行预测,根据预测结果对网络的发送速率进行调整来提高网络的服务质量;最后,利用NS2软件对上述算法进行仿真,结果表明改进算法能够使得网络服务质量得到提升。
Aiming at the situation that it is easy for Ad Hoc Network to cause congestion for the overweight load with the bandwidth limitations and the characteristics of self-organization. This paper proposed a congestion control algorithm based on Constant Bit Rate （CBR） of Bayesian Network to adjust sending rate. Firstly, the algorithm carried out Bayesian Network learning from the parameters influencing on its state. Secondly, it utilized the achieved Bayesian Network to predict the congestion state and then adjust the sending rate to improve the network Quality of Service （QoS）. Finally, NS2 software was employed to implement the algorithm simulation. The simulation results demonstrate that the algorithm can improve the network Quality of Service.
出处
《计算机仿真》
CSCD
北大核心
2014年第5期312-315,326,共5页
Computer Simulation
基金
国家自然科学基金(61162010)
海南大学青年基金(qnjj1243)
关键词
拥塞控制
固定码率
贝叶斯网络
自组织网络
服务质量
Congestion control
Constant bit rate
Bayesian network
Ad Hoc networks
Quality of service
