Mobile Networks and Applications

, Volume 22, Issue 5, pp 931–942 | Cite as

Lifetime Enhancement of Dynamic Heterogeneous Wireless Sensor Networks with Energy-Harvesting Sensors

  • Chun-Cheng Lin
  • Yung-Chiao Chen
  • Jiann-Liang Chen
  • Der-Jiunn Deng
  • Shang-Bin Wang
  • Shun-Yu Jhong
Article
  • 249 Downloads

Abstract

Lifetime enhancement has been the major constraint of developing wireless sensor networks (WSNs). Most of previous related works separately considered dynamics and heterogeneity of WSNs, and did not consider energy-harvesting (EH) sensors, which can absorb natural power (e.g., solar and wind power) to extend lifetime of sensor devices. Therefore, this work investigates the problem of extending the lifetime of dynamic heterogeneous WSNs with EH sensors to enhancing the total WSN lifetime. This problem can be characterized as finding the maximal number of covers each of which is a part of all sensors so that all targets can be monitored by these sensors. Since the case for static WSNs has been shown to be NP-complete, the concerned problem is also NP-complete. Hence, this work first models this problem mathematically, and then proposes a novel harmony search algorithm with multiple populations and local search (HSAML) for this problem with dynamics, heterogeneity, and EH sensors. By simulation, the network lifetime, stability, and executing time of the proposed algorithm are analyzed. From experimental results, the proposed HSAML performs better than the conventional algorithm in terms of average network lifetime for larger-scale problems (i.e., when the number of common and EH sensors is small). In addition, the results confirm that adding EH sensors really helps extend the total WSN lifetime.

Keywords

Heterogeneous wireless sensor network Energy-harvesting sensor Harmony search algorithm Dynamic optimization 

Notes

Acknowledgements

The authors thank the anonymous referees for comments that improved the content as well as the presentation of this paper. This work has been supported in part by MOST 104-2221-E-009-134-MY2.

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.National Chiao Tung UniversityHsinchuTaiwan
  2. 2.Department of Electrical EngineeringNational Taiwan University of Science and TechnologyTaipeiTaiwan
  3. 3.Computer and Information Networking CenterNational Taiwan UniversityTaipeiTaiwan
  4. 4.Department of Computer Science and Information EngineeringNational Changhua University of EducationChanghuaTaiwan

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