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Adaptive Power Controlled Routing for Underwater Sensor Networks

  • Manal Al-Bzoor
  • Yibo Zhu
  • Jun Liu
  • Ammar Reda
  • Jun-Hong Cui
  • Sanguthevar Rajasekaran
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7405)

Abstract

Energy efficiency and mobility robustness are two of the main performance metrics to be addressed when designing any routing protocol for underwater sensor network (UWSN). Energy efficiency leads to a prolonged network life time, while mobility robustness ensures high and stable delivery ratio. Most of the routing strategies designed for UWSN require a full knowledge of the three dimensional location of nodes. In this paper, we introduce an energy efficient routing schema that does not require any location information, and achieves high packet delivery ratio for both static and mobile scenarios in sparse or dense networks. In our routing strategy, nodes assign themselves to concentric layers. A node to layer assignment is determined by signal power of a received interest packet broadcast by sink nodes. Routing paths are determined on the fly, and a forwarder is chosen based on its layer number and residual energy. Nodes are assumed to be able to adjust their transmission power to a finite set of values. Low power level is most likely selected by nodes when the network is dense, whereas a higher power level is selected when the network is sparse or when nodes at layers closer to the sink has more residual energy. Simulation results shows that our routing protocol achieves a high delivery ratio and a low energy consumption while reducing the delay when compared with other routing strategies for both sparse and dense networks.

Keywords

Data Packet Delivery Ratio Sink Node Residual Energy High Power Level 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Manal Al-Bzoor
    • 1
  • Yibo Zhu
    • 1
  • Jun Liu
    • 1
  • Ammar Reda
    • 1
  • Jun-Hong Cui
    • 1
  • Sanguthevar Rajasekaran
    • 1
  1. 1.Department of Computer Science and EngineeringUniversity of ConnecticutStorrsUSA

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