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 proceedingConference contribution


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 publication15th 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
Place of PublicationCham
PublisherSpringer International Publishing
Number of pages16
ISBN (Electronic)978-3-319-46523-4
ISBN (Print)978-3-319-46522-7
Publication statusPublished - 23 Sep 2016
EventThe 15th International Semantic Web Conference - Kobe, Japan
Duration: 17 Oct 201621 Oct 2016

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceThe 15th International Semantic Web Conference
Abbreviated titleISWC 2016
Internet address


  • Energy
  • Semantic web
  • Ontology reasoning
  • Mobile computing
  • Prediction
  • Random forests


Dive into the research topics of 'Predicting Energy Consumption of Ontology Reasoning over Mobile Devices'. Together they form a unique fingerprint.

Cite this