期刊文献+

一种基于删除信道的WSAN控制器自适应动态配置算法

An adaptive dynamic placement algorithm of WSAN controller based on erasure channel
原文传递
导出
摘要 针对无线传感器执行器网络(wireless sensor and actuator networks,WSAN)中的随机数据包丢失问题,提出了一种基于删除信道的WSAN控制器自适应动态配置算法。该算法采用模拟删除信道的多节点串联连接的网络控制架构,使用提出的配置算法对控制器进行自适应配置,并利用伯努利分布进行动态配置,通过导出马尔可夫链跳变线性系统模型,建立静止协方差的闭环表达形式。利用随机建模框架在衰落的无线电环境中进行仿真实验,结果表明,相比节点功能固定的配置算法,该算法可以更快地对设备输出做出响应,明显提升了控制器的性能,有效解决了WSAN中的随机数据包丢失问题。 For the issue of data-packet dropouts in wireless sensor and actuator networks,an adaptive placement algorithm of WSAN controller based on erasure channel is proposed. Multiple nodes in series connection of simulation erasure channel are used to propose flexible network control architecture. The proposed placement algorithm is used to adaptively place the controller,and use Bernoulli distribution to do dynamic placement. Still covariance closed loop form is established by exporting jump linear system model of Markov chain. Simulation experiment is done in declining radio environment by using stochastic modeling framework. Simulation results show that the proposed algorithm can respond faster to equipment output than the algorithm with fixed node function,which indicates the proposed algorithm has improved the performance of controller and it has settled the issue of data-packet dropouts.
作者 陈超
出处 《重庆邮电大学学报(自然科学版)》 CSCD 北大核心 2015年第5期683-691,共9页 Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition)
基金 四川省科技厅苗子工程资助项目(2014-054) 自贡市科技局资助项目(2014DZ08) 四川省重点实验室项目(NJ2013-11) 四川省高校重点实验室项目(2013WZY01)~~
关键词 无线传感器执行器网络 数据包丢失 模拟删除信道 自适应配置 马尔可夫链 wireless sensor and actuator network data-packet dropout simulation erasure channel adaptive placement Markov chain
  • 相关文献

参考文献15

  • 1易军,石为人,唐云建,许磊.无线传感器/执行器网络任务动态调度策略[J].电子学报,2010,38(6):1239-1244. 被引量:20
  • 2RODRIGUES T, BATISTA T, DELICATO F C, et al. Model-driven approach for building efficient wireless sensor and actuator network applications[C]//Software Engineering for Sensor Network Applications, 2013 4th International Workshop on. [s. l]: IEEE, 2013: 43-48.
  • 3易军,李太福,石为人.无线传感器/执行器网络SA协作分簇算法[J].华中科技大学学报(自然科学版),2011,39(12):89-93. 被引量:3
  • 4MEZEI I, LUKIC M, MALBASA V, et al. Auctions and iMesh based task assignment in wireless sensor and actuator networks[J]. Computer Communications, 2013, 36(9): 979-987.
  • 5PORTER B, COULSON G, ROEDIG U. Managing software evolution in large-scale wireless sensor and actuator networks[J]. ACM Transactions on Sensor Networks (TOSN), 2013, 9(4): 54-60.
  • 6LI S, PENG J, LIU W, et al. A uniform energy consumption algorithm for wireless sensor and actuator networks based on dynamic polling point selection[J]. Sensors, 2013, 14(1): 95-116.
  • 7YASSINE A, FARKA P. One hybrid ARQ for broadcasting or multicasting in wireless erasure channel[J]. Telecommunication Systems, 2013, 52(3): 1525-1532.
  • 8QUEVEDO D E, AHLéN A, JOHANSSON K H. State estimation over sensor networks with correlated wireless fading channels[J]. Automatic Control, IEEE Transactions on, 2013, 58(3): 581-593.
  • 9NGUYEN S T, CAYIRCI E, RONG C. A secure many-to-many routing protocol for wireless sensor and actuator networks[J]. Security and Communication Networks, 2014, 7(1): 88-98.
  • 10IRANOPPAIBOON M, TSUMURA K. Stabilizability of LTI MIMO systems with uncertain parameters under communication constraints[C]//American Control Conference (ACC). [s. l]: IEEE, 2013: 2319-2324.

二级参考文献49

  • 1董超,田畅,倪明放.Ad hoc网络时钟同步研究[J].通信学报,2006,27(9):110-117. 被引量:19
  • 2T Rappaport.Wireless Communication Principles and Practice (2nd Edition)[M].London:Prentice Hall PTR,2002.142-153.
  • 3J Kennedy,R C Eberhart.Particle swarm optimization[A].Proceedings of the IEEE International Conference on Neural Networks Ⅳ[C].piscataway,NJ:IEEE Service Center,1995.1942-1948.
  • 4She D Y,Hsu C Y.A hybrid particle swarm optimization for job shop scheduling problem[J].Computers & Industrial Engineering,2006,51(4):791-808.
  • 5Zhang H,Li X,Li H.et al.Particle swarm optimization-based schemes for resource-constrained project scheduling[J].Automation in Construction,2005,14(3):393-404.
  • 6Deb K.An efficient constraint handling method for genetic algorithms[J].Computer Methods in Applied Mechanics and Engineering,2000,186(2/4):311-338.
  • 7Fisher H,Thompson G L.Probabilistic Learning Combinations of Local Job-shop Scheduling Rules[M].Englewood Cliffs,NJ:Prentice-Hall,1963.225-251.
  • 8Lawrence S.Resource Constrained Project Scheduling:An Experimental Investigation of Heuristic Scheduling Techniques[D].Pittsburgh:School of Industrial Administration,Carnegie Mellon University,1984.
  • 9I F Akyildiz,I H Kasimoglul.Wireless sensor and actor networks:research challenges[J].Ad Hoc Networks Journal,2004,2(4):351-367.
  • 10Heemin P,Mani B S.Energy-efficient task assignment framework for wireless sensor networks[R].UC Los Angeles:The Berkeley Electronic Press,2003.

共引文献22

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部