Predicting Energy Consumption of Ontology Reasoning over Mobile Devices

Isa Guclu, Yuan Fang Li, Jeff Z Pan, Martin J Kollingbaum

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

8 Citations (Scopus)


The unprecedented growth in mobile devices, combined with advances in Semantic Web (SW) Technologies, has given birth to opportunities for more intelligent systems on-the-go. Limited resources of mobile devices demand approaches that make mobile reasoning more applicable. While Mobile-Cloud integration is a promising method for harnessing the power of semantic technologies in the mobile infrastructure, it is an open question how to decide when to reason over ontologies on mobile devices. In this paper, we introduce an energy consumption prediction mechanism for ontology reasoning on mobile devices that allows an analysis of the feasibility of performing an ontology reasoning on a mobile device with respect to energy consumption. The developed prediction model contributes to mobile–cloud integration and helps to improve further developments in semantic reasoning in general.
Original languageEnglish
Title of host publicationThe Semantic Web – ISWC 2016
Subtitle of host publication5th International Semantic Web Conference, Kobe, Japan, October 17–21, 2016, Proceedings, Part I
EditorsPaul Groth, Elena Simperl, Alasdair Gray, Marta Sabou, Markus Krötzsch, Freddy Lecue, Fabian Flöck, Yolanda Gil
Number of pages16
ISBN (Electronic)978-3-319-46523-4
ISBN (Print)978-3-319-46522-7
Publication statusPublished - 2016

Publication series

NameInformation Systems and Applications, incl. Internet/Web, and HCI

Bibliographical note

This work is partially funded by the EU IAPP K-Drive project (286348). We would like to thanks Prof. Breiman for making the Fortran code of his Random Forests algorithm available and thank Edgaras Valincius for providing us with his codes in energy measurement over mobile devices.


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