【作者】 任玲； 唐昊； 周雷； 魏振春；

【Author】 REN Ling~1,TANG Hao~(1,2),ZHOU Lei~1,WEI Zhenchun~(1,2) 1.School of Computer and Information,Hefei University of Technology,Hefei 23009,P.R.China 2.Engineering Research Center of Safety Critical Industry Measure and Control Technology,Ministry of Education,Hefei 23009,P.R.China

【机构】 合肥工业大学计算机与信息学院； 安全关键工业测控技术教育部工程研究中心；

【摘要】 针对当前大多数无线传感器网络传输协议不能高效利用传感器节点能量的问题,提出了一种基于信道和缓冲区状态的自适应传输方法,包括基于信道和缓冲区的传输机制(Channel and Buffer Based Transmission,简记为CBT)和基于信道和缓冲区的分片传输机制(Channel and Buffer Based Fragment Transmission,简记CBFT),CBFT在CBT的基础上结合虚拟分片传输技术。并将节点的数据传输问题建模成马尔可夫决策过程(Markov decisionprocess,简记MDP)模型,应用Q学习算法进行求解。最后,论文通过仿真实验验证了算法的有效性。仿真结果表明,传感器节点能量得到高效利用,无线传感器网络的寿命也得到延长。更多还原

【Abstract】 Most current transmission protocols can not achieve energy-efficient of Wireless Sensor Networks(WSNs),an energy-efficient adaptive transmission based on channel and buffer state is proposed,including Channel and Buffer Based Transmission(CBT) and Channel and Buffer Based Fragment Transmission(CBFT).The adaptive Transmission based on the current channel state to decide whether to transfer,avoid the energy waste caused by failed transmission.CBFT based on CBT,and combine with virtual fragment transmission technology.Data transfer problem of sensor node is modeled as Markov decision process(MDP) model,Q learning algorithm is proposed to solve the problem.Finally,the simulation is used to illustrate the effectiveness of the algorithm;the results show that the consumed energy of sensor node is efficient. The lifetime of wireless sensor network can be prolonged.更多还原