Modeling the Total Energy Consumption of Mobile Network Services and Applications

Ming Yan, Chien Aun Chan, André F. Gygax, Jinyao Yan, Leith Campbell, Ampalavanapillai Nirmalathas and Christopher Leckie
Additional contact information
Ming Yan: Faculty of Science and Technology, Communication University of China, Beijing 100024, China
Chien Aun Chan: Networked Society Institute, University of Melbourne, Melbourne, VIC 3010, Australia
André F. Gygax: Networked Society Institute, University of Melbourne, Melbourne, VIC 3010, Australia
Jinyao Yan: Faculty of Science and Technology, Communication University of China, Beijing 100024, China
Leith Campbell: Department of Electrical and Electronic Engineering, University of Melbourne, Melbourne, VIC 3010, Australia
Ampalavanapillai Nirmalathas: Department of Electrical and Electronic Engineering, University of Melbourne, Melbourne, VIC 3010, Australia
Christopher Leckie: School of Computing and Information Systems, University of Melbourne, Melbourne, VIC 3010, Australia

Energies, 2019, vol. 12, issue 1, 1-18

Abstract: Reducing the energy consumption of Internet services requires knowledge about the specific traffic and energy consumption characteristics, as well as the associated end-to-end topology and the energy consumption of each network segment. Here, we propose a shift from segment-specific to service-specific end-to-end energy-efficiency modeling to align engineering with activity-based accounting principles. We use the model to assess a range of the most popular instant messaging and video play applications to emerging augmented reality and virtual reality applications. We demonstrate how measurements can be conducted and used in service-specific end-to-end energy consumption assessments. Since the energy consumption is dependent on user behavior, we then conduct a sensitivity analysis on different usage patterns and identify the root causes of service-specific energy consumption. Our main findings show that smartphones are the main energy consumers for web browsing and instant messaging applications, whereas the LTE wireless network is the main consumer for heavy data applications such as video play, video chat and virtual reality applications. By using small cell offloading and mobile edge caching, our results show that the energy consumption of popular and emerging applications could potentially be reduced by over 80%.

Keywords: mobile service; energy consumption; energy model; end-to-end communication networks; service-specific (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/1996-1073/12/1/184/pdf (application/pdf)
https://www.mdpi.com/1996-1073/12/1/184/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:12:y:2019:i:1:p:184-:d:195469

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().