• DocumentCode
    550757
  • Title

    An energy-efficient adaptive transmission method for Wireless Sensor Networks

  • Author

    Ren Ling ; Tang Hao ; Zhou Lei ; Wei Zhenchun

  • Author_Institution
    Sch. of Comput. & Inf., Hefei Univ. of Technol., Hefei, China
  • fYear
    2011
  • fDate
    22-24 July 2011
  • Firstpage
    5005
  • Lastpage
    5010
  • 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.
  • Keywords
    Markov processes; energy conservation; protocols; telecommunication network reliability; wireless channels; wireless sensor networks; CBFT; CBT; MDP model; Markov decision process model; Q learning algorithm; WSN; channel and buffer based fragment transmission; channel and buffer based transmission; data transfer problem; energy-efficient adaptive transmission method; transmission protocol; virtual fragment transmission technology; wireless sensor network; Adaptive systems; Binary phase shift keying; Electronic mail; Energy efficiency; Markov processes; Signal to noise ratio; Wireless sensor networks; CBFT; CBT; Fragment Transmission; Q-learning; WSNs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (CCC), 2011 30th Chinese
  • Conference_Location
    Yantai
  • ISSN
    1934-1768
  • Print_ISBN
    978-1-4577-0677-6
  • Electronic_ISBN
    1934-1768
  • Type

    conf

  • Filename
    6001097