SDRT: A reliable data transport protocol for underwater sensor networks

  • Authors:

  • Peng Xie;Zhong Zhou;Zheng Peng;Jun-Hong Cui;Zhijie Shi

  • Affiliations:

  • Department of Computer Science and Engineering, The University of Connecticut, Storrs, CT 06269, USA;Department of Computer Science and Engineering, The University of Connecticut, Storrs, CT 06269, USA;Department of Computer Science and Engineering, The University of Connecticut, Storrs, CT 06269, USA;Department of Computer Science and Engineering, The University of Connecticut, Storrs, CT 06269, USA;Department of Computer Science and Engineering, The University of Connecticut, Storrs, CT 06269, USA

  • Venue:
  • Ad Hoc Networks
  • Year:
  • 2010

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Abstract

In this paper, we investigate the reliable data transfer problem in underwater sensor networks. Underwater sensor networks are significantly different from terrestrial sensor networks in two aspects: acoustic channels are used for communications and most sensor nodes are mobile due to water current. These distinctions feature underwater sensor networks with low available bandwidth, large propagation delay, highly dynamic network topology, and high error probability, which pose many new challenges for reliable data transfer in underwater sensor networks. In this paper, we propose a protocol, called segmented data reliable transfer (SDRT), to achieve reliable data transfer in underwater sensor network scenarios. SDRT is essentially a hybrid approach of ARQ and FEC. It adopts efficient erasure codes, transferring encoded packets block by block and hop-by-hop. Compared with traditional reliable data transfer protocols, SDRT can reduce the total number of transmitted packets significantly, improve channel utilization, and simplify protocol management. In addition, we develop a mathematic model to estimate the expected number of packets actually needed in SDRT with SVT codes. Based on this model, we devise a new window control mechanism to further reduce energy consumption which is introduced by large propagation delay of acoustic channels. Moreover, this model enables us to set the appropriate size of the block to address the mobility of the nodes in the network. We conduct simulations to evaluate our model and SDRT. The results show that our model can closely predict the number of packets actually needed, and SDRT is energy efficient, and can achieve high channel utilization.