Robust Header Compression version 2 power consumption on Android devices via tunnelling

Research output: Contribution to book/conference proceedings/anthology/reportConference contributionContributedpeer-review

Contributors

Abstract

Next generation use-cases of wireless IP networks, including especially the Massive Machine Type Communications and IoT applications for the distribution of sensory and similar data will require the capability to handle large number of connections while maintaining a low-power footprint in order to function efficiently during long-term deployments. The reduction of the packetisation overhead resulting from the adaptation of header compression could potentially decrease the battery usage of network heavy applications via diminished wireless interface activity. Normally header compression is employed to minimise the overhead of IP-based cellular traffic between two connected peers. This paper presents for the first time comparative power consumption measurements for Robust Header Compression version 2 (RoHCv2) using WiFi and LTE. We find that the adoption of header compression on modern mobile devices will generally not result in increased power consumption based on the extra complexity added by the execution of the algorithms. We also show that the usage of RoHCv2 can potentially even decrease the battery drain on average by about 0.05 W when payloads are small.

Details

Original languageEnglish
Title of host publication2017 IEEE International Conference on Communications Workshops, ICC Workshops 2017
EditorsConstantinos B. Papadias, Abbas Jamalipour
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages418-423
Number of pages6
ISBN (electronic)9781509015252
Publication statusPublished - 29 Jun 2017
Peer-reviewedYes

Conference

Title2017 IEEE International Conference on Communications Workshops, ICC Workshops 2017
Duration21 - 25 May 2017
CityParis
CountryFrance

Keywords

Sustainable Development Goals

Keywords

  • Bandwidth savings, Cellular networks, Energy efficiency, IoT, Power consumption, Robust Header Compression