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Wireless Personal Communications

, Volume 101, Issue 3, pp 1731–1747 | Cite as

Achieve Adaptive Data Storage and Retrieval Using Mobile Sinks in Wireless Sensor Networks

  • Xingpo MaEmail author
  • Yin Li
  • Tian Wang
  • Junbin Liang
Article

Abstract

In WSNs (Wireless Sensor Networks), data storage and retrieval is a challenging problem because of the limited resource and the short communication radius of the sensor nodes. Most of the existed schemes choose one or more static sensor nodes or Sinks to act as the rendezvous nodes, which can be seen as the connectors between the data producers and the data consumers. However, those schemes cannot avoid both the “hot spot” problem and the “bottleneck” problem, which refer to the much higher load balance of the sensor nodes around the rendezvous nodes. Moreover, most of the existing schemes never consider the dynamic nature of WSNs, which leads to the lack of adaptability. In this paper, we propose a novel dynamic-optimization-based framework named SRMSN using mobile Sinks to solve such a problem. SRMSN utilizes two heuristic methods, which are based on the virtual-grid-division technology and the diversity-factor-analysis technology, to determine the optimal target locations of the mobile Sinks in each time interval when each Sink node stay at a certain position and the optimal length of each of the time intervals adaptively, aiming at improving the adaptability and the efficiency of WSNs on data storage and retrieval. Simulation results show that SRMSN can reduce and balance the energy consumption greatly as well as decrease the average delay of data storage and retrieval in comparison with the state-of-the-art scheme on data storage and retrieval in WSNs.

Keywords

Wireless sensor networks Data storage and retrieval Mobile Sinks Virtual-grid division Diversity-factor analysis 

Notes

Acknowledgement

This research is supported by NSFC (Natural Science Foundation of P. R. China, No. 61562005, 61402393), CSC (China Scholarship Council, No. 201508410271), the Natural Science Foundation of Henan Province of P. R. China (162300410234), the Nanhu Scholars Program for Young Scholars of XYNU, and the supporting program of young backbone teachers in Xinyang Normal University in Henan Province of P. R. China.

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Copyright information

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

Authors and Affiliations

  1. 1.Xinyang Normal UniversityXinyangPeople’s Republic of China
  2. 2.College of Computer ScienceHuaqiao UniversityQuanzhouPeople’s Republic of China
  3. 3.School of Computer and Electronics InformationGuangxi UniversityNanningPeople’s Republic of China

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