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  •   Open Research
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  • Faculty of Design and Creative Technologies (Te Ara Auaha)
  • School of Engineering, Computer and Mathematical Sciences - Te Kura Mātai Pūhanga, Rorohiko, Pāngarau
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Energy-efficient Massive Data Dissemination Through Vehicle Mobility in Smart Cities

Naseer, S; Liu, W; Sarkar, NI
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http://hdl.handle.net/10292/13107
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Abstract
One of the main challenges of operating a smart city (SC) is collecting the massive data generated from multiple data sources (DSs) and transmitting them to the control units (CUs) for further data processing and analysis. These ever-increasing data demands require not only more and more capacity of the transmission channels but also results in resource over-provision to meet the resilience requirements, thus the unavoidable waste as a result of the data fluctuations throughout the day. In addition, the high energy consumption (EC) and carbon discharge from these data transmissions posing serious issues to the environment we live in. Therefore, to overcome the issues of intensive EC and carbon emission (CE) of massive data dissemination in SCs, we propose an energy-efficient and carbon reduction approach by using the daily mobility of the existing vehicles as an alternative communications channel to accommodate the data dissemination in SCs. To illustrate the effectiveness and efficiency of our approach, we take the Auckland City in New Zealand as an example, assuming massive data generated by various sources geographically scattered throughout the Auckland region, to the control centres located in the city. Results obtained show that our proposed approach can provide up to four times faster transferring the large volume of data by using the existing daily vehicles’ mobility, than the conventional transmission network. Moreover, our proposed approach offers about 32% less EC and CE than that of conventional network transmission approach.
Keywords
Smart city; Delay tolerant network; Infrastructure offloading; Opportunistic network; Vehicular mobility; Energy consumption; Carbon emission
Date
2019
Source
Sensors, 19(21), 4735. doi:10.3390/s19214735
Item Type
Journal Article
Publisher
MDPI
DOI
10.3390/s19214735
Publisher's Version
https://www.mdpi.com/1424-8220/19/21/4735
Rights Statement
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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