Energy-efficient big data storage and retrieval for wireless sensor networks with nonuniform node distribution

Jinhai Xu, Songtao Guo, Bin Xiao, Jing He

Research output: Journal article publicationJournal articleAcademic researchpeer-review

15 Citations (Scopus)

Abstract

Summary Distributed data-centric storage in wireless sensor networks (WSNs) is considered as a promising big data storage approach, because it contributes to reducing the communication overhead inside the networks. However, most of the existing distributed methods rely on locating systems, which consume more energy, and assume that sensors are uniformly distributed, which is clearly not applicable for the scenarios with nonuniform sensor distribution. To address these issues, in this paper, we propose a big data storage and retrieval algorithm for WSNs with nonuniform node distribution, which aims at estimating the real distribution and the addresses of sensor nodes. In particular, we consider the data redundancy among neighbor nodes in the proposed algorithm and exploit a simple routing based on the algorithm. Experimental results show that our approach outperforms other approaches in terms of data querying efficiency and data loss rate.
Original languageEnglish
Pages (from-to)5765-5779
Number of pages15
JournalConcurrency Computation
Volume27
Issue number18
DOIs
Publication statusPublished - 25 Dec 2015

Keywords

  • big data
  • data storage and retrieval
  • nonuniform distribution
  • wireless sensor networks

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Computer Science Applications
  • Computer Networks and Communications
  • Computational Theory and Mathematics

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