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Peer-to-Peer Networking and Applications

, Volume 12, Issue 1, pp 189–208 | Cite as

Localized topology control and on-demand power-efficient routing for wireless ad hoc and sensor networks

  • Xu Qin
  • Baoxian ZhangEmail author
  • Cheng Li
Article
  • 52 Downloads

Abstract

Power use is a crucial design concern in wireless ad hoc and sensor networks since it corresponds directly to the network operational time. In this paper, we study the issue of power-efficient use in the following two aspects: Selecting power-efficient routes and performing efficient localized topology control to assign reduced transmit powers at nodes while preserving the global optimal connectivity. We proposed a localized topology control algorithm using two-hop neighborhood knowledge, which works to build local shortest path tree at each node independently in order to generate a reduced topology while preserving the global optimal connectivity. We derive the energy stretch ratio and maximum degree performance of our proposed algorithm as well as several existing algorithms in this aspect. We then devise three power-efficient on-demand routing protocols on top of various localized topology control algorithms, which are to acquire minimum-power paths while minimizing the associated protocol overhead for route discovery by utilizing local network state information and also packet receipt status at neighbor nodes. We further derive the asymptotical performance of the routing strategy in our protocols in terms of energy stretch ratio and route acquisition latency when network nodes operate at limited discrete power levels. Simulation results are provided to demonstrate the high performance of our topology control algorithm and also the devised routing protocols.

Keywords

Topology control Localized algorithm Power-aware routing On-demand routing Wireless ad hoc and sensor networks 

Notes

Acknowledgements

The work in this paper was supported partially by the NSF of China under Grant Nos. 61531006, 61471339, 61173158, the Natural Sciences and Engineering Research Council (NSERC) of Canada (Discovery Grant RGPIN-2018-03792), and the RDC SensorTECH Grant 5404-2061-101.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Research Center of Ubiquitous Sensor NetworkUniversity of Chinese Academy of SciencesBeijingChina
  2. 2.School of Computer and Information EngineeringTianjin Chengjian UniversityTianjinChina
  3. 3.Faculty of Engineering and Applied ScienceMemorial University of NewfoundlandSt. John’sCanada

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