A Novel Approach for Efficient Management of Data Lifespan of IoT Devices

Mohammed Asiri, Tarek Sheltami*, Louai Al-Awami, Ansar Yasar

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


Wireless sensor networks (WSNs) are mainly data-driven networks adopted to improve the Internet of Things (IoT) in terms of data throughput, energy efficiency, and self-management. Improving the data lifespan of WSN impacts the performance of the IoT. Achieving data reliability in applications of WSNs deployed in harsh environments is challenging due to the extreme constraints in resources of sensor nodes (SNs). Motivated by the inexpensive infrastructure of WSNs, a number of distributed storage systems have been proposed focusing on achieving data survivability rather than network reliability. In this article, we focus on data storage at the things layer (wireless sensors). We evaluate the performance of a number of distributed data storage systems (DDSSs) over WSN running over the ZigBee MAC protocol. Based on our findings, we introduce a new efficient-energy data dissemination scheme called data survivability with energy efficiency (DSwEE) that outperforms the existing schemes. We compare DSwEE against two prominent protocols in data storage, namely, decentralized erasure code for data survivability (DEC-DS) and decentralized erasure code encode-and-disseminate (DEC-EaD). Results show that DSwEE achieves better performance than both DEC-DS and DEC-EaD in terms of the energy consumption and data recoverability for localized failures, which improves the lifespan of the network.

Original languageEnglish
Article number8910366
Pages (from-to)4566-4574
Number of pages9
JournalIEEE Internet of Things Journal
Issue number5
StatePublished - May 2020

Bibliographical note

Publisher Copyright:
© 2014 IEEE.


  • Data survivability
  • Internet of Things (IoT)
  • decentralized erasure codes (DEC)
  • distributed data storage
  • wireless sensor networks (WSNs)

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications


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