通信学报 ›› 2013, Vol. 34 ›› Issue (9): 41-52.doi: 10.3969/j.issn.1000-436x.2013.09.006

• 学术论文 • 上一篇    下一篇

面向混合业务的无线传感器网络能量有效接入策略

王亚松1,张钦宇2,李云鹤2,韩晶1   

  1. 1 北京邮电大学 信息与通信工程学院,北京 100876
    2 哈尔滨工业大学 深圳研究生院,广东 深圳 518055
  • 出版日期:2013-09-25 发布日期:2017-07-05
  • 基金资助:
    国家重点基础研究发展计划(“973”计划)基金资助项目;国家自然科学基金资助项目

Eenergy effiency access strategy:towards hybrid wireless sensor network

Ya-song WANG1,Qin-yu ZHANG2,Yun-he LI2,Jing HAN1   

  1. 1 School of Information and Communication Engineering,Beijing University of Posts and Telecommunications,Be jing 100876,China
    2 Shenzhen Graduate School,Harbin Institute of Technolo,Shenzhen 518055,China
  • Online:2013-09-25 Published:2017-07-05
  • Supported by:
    The National Basic Research Program of China (973 Program);The National Natural Science Foundation of China

摘要:

研究了在实时业务和非实时业务同时存在的混合背景下,非实时业务的无线传感器节点自适应侦听和睡眠的动态接入机制。网络节点处于睡眠状态时所需的能量很低,节约了无线传感器网络节点的平均能量消耗;但是,过长的睡眠时间可能使得网络节点错失传输机会。因此,根据信道的使用情况,合理地设定无线传感器网络节点的睡眠时间,能够在网络能量消耗和传输效率之间进行调整,从而最大化无线传感器网络的能量传输效率。首先,利用连续时间 Markov 方法对问题进行建模,并利用基于摄动分析理论对系统模型进行分析,获得求解无线传感器网络能量效率最大化的最优睡眠时间梯度算法。最后通过理论结果和计算机仿真模拟的对比,验证了推荐方法的可行性。

关键词: 无线传感器网络, 能量效率, 混合业务, 传输效率, 最佳睡眠时间

Abstract:

A dynamically access mechanism of non-real-time sensor nodes with adaptive listening and sleeping,against the background,co-existence of real-time traffic and non-real-time traffic in the networks,was studied.The energy consumption is very slow while the node is in a sleep state; however,the long sleep time may make the network nodes miss transmission opportunity.Thus,according to the usage of the channel,a reasonable set of wireless sensor network nodes sleep time in the network energy consumption and transmission efficiency could be adjusted to maximize the energy transmission efficiency of wireless sensor network.Firstly,the continuous-time Markov modeling the problem was used and analyzed.Then system model based on perturbation analysis theory was proposed to obtain the gradient algorithm for solving the optimal sleep time.Finally,the feasibility of the recommended program is verified by comparing the theoretical results and computer simulation.

Key words: wireless sensor network, energy-efficiency, mixed service, transmission-efficiency, optimal sleeping time

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