Optimizing Energy Consumption for Big Data Collection in Large-Scale Wireless Sensor Networks With Mobile Collectors

Li-Minn Ang; J K P Seng; A M Zungeru

doi:10.1109/JSYST.2016.2630691

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Optimizing Energy Consumption for Big Data Collection in Large-Scale Wireless Sensor Networks With Mobile Collectors

Journal article

Peer reviewed

Optimizing Energy Consumption for Big Data Collection in Large-Scale Wireless Sensor Networks With Mobile Collectors

Li-Minn Ang, J K P Seng and A M Zungeru

IEEE Systems Journal, Vol.12(1), pp.616-626

2018

DOI: https://doi.org/10.1109/JSYST.2016.2630691

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Abstract

Analytical models

Big Data

Data collection using data mule (MULE)

Data models

Energy consumption

large-scale wireless sensor networks (LS-WSNs)

Mobile communication

mobile data collectors

sensor network with mobile access point (SENMA)

Wireless sensor networks

Big sensor-based data environment and the emergence of large-scale wireless sensor networks (LS-WSNs), which are spread over wide geographic areas and contain thousands of sensor nodes, require new techniques for energy-efficient data collection. Recent approaches for data collection in WSNs have focused on techniques using mobile data collectors (MDCs) or sinks. Compared to traditional methods using static sinks, the MDC techniques give two advantages for data collection in LS-WSNs. These techniques can handle data collection over spatially separated geographical regions, and have been shown to require lower node energy consumption. Two common models for data collection using MDCs have been proposed: data collection using data mule (MULE), and sensor network with mobile access point (SENMA). The MULE and SENMA approaches can be characterized as representative of the multihop and the single-hop approaches for mobile data collection in WSNs. Although the basic architectures for MULE and SENMA have been well studied, the emergence of LS-WSNs which require partitioning the network into multiple groups and clusters prior to data collection has not been particularly addressed. This paper presents analytical approaches to determine the node energy consumption for LS-WSN MDC schemes and gives models for determining the optimal number of clusters for minimizing the energy consumption. The paper also addresses the tradeoffs when the LS-WSN MULE and SENMA models perform well.

Details

Title: Optimizing Energy Consumption for Big Data Collection in Large-Scale Wireless Sensor Networks With Mobile Collectors
Authors: Li-Minn Ang (Author) - Charles Sturt University
J K P Seng (Author) - Charles Sturt University
A M Zungeru (Author) - Botswana International University of Science and Technology, Botswana
Publication details: IEEE Systems Journal, Vol.12(1), pp.616-626
Publisher: Institute of Electrical and Electronics Engineers
Date published: 2018
DOI: 10.1109/JSYST.2016.2630691
ISSN: 1932-8184; 1937-9234
Grant note: A541-2006-121-25411 / Charles Sturt University Compact Funding
Organisation Unit: School of Science and Engineering - Legacy; University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; Engage Research Lab
Language: English
Record Identifier: 99450962102621
Output Type: Journal article

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Collaboration types: International collaboration
Web Of Science research areas: Computer Science, Information Systems; Engineering, Electrical & Electronic; Operations Research & Management Science; Telecommunications