Predicting Energy Consumption of Ontology Reasoning over Mobile Devices

Isa Guclu; Yuan-Fang Li; Jeff Z. Pan; Martin J. Kollingbaum

doi:10.1007/978-3-319-46523-4_18

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 proceeding › Conference contribution

Abstract

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 language	English
Title of host publication	The Semantic Web -- ISWC 2016
Subtitle of host publication	15th International Semantic Web Conference, Kobe, Japan, October 17–21, 2016, Proceedings, Part I
Editors	Paul Groth, Elena Simperl, Alasdair Gray, Marta Sabou, Markus Krötzsch, Freddy Lecue, Fabian Flöck, Yolanda Gil
Place of Publication	Cham
Publisher	Springer
Pages	289-304
Number of pages	16
ISBN (Electronic)	978-3-319-46523-4
ISBN (Print)	978-3-319-46522-7
DOIs	https://doi.org/10.1007/978-3-319-46523-4_18
Publication status	Published - 23 Sept 2016
Event	The 15th International Semantic Web Conference - Kobe, Japan Duration: 17 Oct 2016 → 21 Oct 2016 https://iswc2016.semanticweb.org/

Publication series

Name	Lecture Notes in Computer Science
Volume	9981
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	The 15th International Semantic Web Conference
Abbreviated title	ISWC 2016
Country/Territory	Japan
City	Kobe
Period	17/10/16 → 21/10/16
Internet address	https://iswc2016.semanticweb.org/

Keywords / Materials (for Non-textual outputs)

Energy
Semantic web
Ontology reasoning
Mobile computing
Prediction
Random forests

Access to Document

10.1007/978-3-319-46523-4_18Licence: All Rights Reserved

https://link.springer.com/chapter/10.1007/978-3-319-46523-4_18Licence: All Rights Reserved

Cite this

Guclu, I., Li, Y.-F., Pan, J. Z., & Kollingbaum, M. J. (2016). Predicting Energy Consumption of Ontology Reasoning over Mobile Devices. In P. Groth, E. Simperl, A. Gray, M. Sabou, M. Krötzsch, F. Lecue, F. Flöck, & Y. Gil (Eds.), The Semantic Web -- ISWC 2016: 15th International Semantic Web Conference, Kobe, Japan, October 17–21, 2016, Proceedings, Part I (pp. 289-304). (Lecture Notes in Computer Science ; Vol. 9981). Springer. https://doi.org/10.1007/978-3-319-46523-4_18

Guclu, Isa ; Li, Yuan-Fang ; Pan, Jeff Z. et al. / Predicting Energy Consumption of Ontology Reasoning over Mobile Devices. The Semantic Web -- ISWC 2016: 15th International Semantic Web Conference, Kobe, Japan, October 17–21, 2016, Proceedings, Part I. editor / Paul Groth ; Elena Simperl ; Alasdair Gray ; Marta Sabou ; Markus Krötzsch ; Freddy Lecue ; Fabian Flöck ; Yolanda Gil. Cham : Springer, 2016. pp. 289-304 (Lecture Notes in Computer Science ).

@inproceedings{fe63bb2e256a4bc98f56f890e5bdeffe,

title = "Predicting Energy Consumption of Ontology Reasoning over Mobile Devices",

abstract = "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.",

keywords = "Energy, Semantic web, Ontology reasoning, Mobile computing, Prediction, Random forests",

author = "Isa Guclu and Yuan-Fang Li and Pan, \{Jeff Z.\} and Kollingbaum, \{Martin J.\}",

year = "2016",

month = sep,

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doi = "10.1007/978-3-319-46523-4\_18",

language = "English",

isbn = "978-3-319-46522-7",

series = "Lecture Notes in Computer Science ",

publisher = "Springer",

pages = "289--304",

editor = "Paul Groth and Elena Simperl and Alasdair Gray and Marta Sabou and Markus Kr{\"o}tzsch and Freddy Lecue and Fabian Fl{\"o}ck and Yolanda Gil",

booktitle = "The Semantic Web -- ISWC 2016",

address = "United Kingdom",

note = "The 15th International Semantic Web Conference, ISWC 2016 ; Conference date: 17-10-2016 Through 21-10-2016",

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Guclu, I, Li, Y-F, Pan, JZ & Kollingbaum, MJ 2016, Predicting Energy Consumption of Ontology Reasoning over Mobile Devices. in P Groth, E Simperl, A Gray, M Sabou, M Krötzsch, F Lecue, F Flöck & Y Gil (eds), The Semantic Web -- ISWC 2016: 15th International Semantic Web Conference, Kobe, Japan, October 17–21, 2016, Proceedings, Part I. Lecture Notes in Computer Science , vol. 9981, Springer, Cham, pp. 289-304, The 15th International Semantic Web Conference, Kobe, Japan, 17/10/16. https://doi.org/10.1007/978-3-319-46523-4_18

Predicting Energy Consumption of Ontology Reasoning over Mobile Devices. / Guclu, Isa; Li, Yuan-Fang; Pan, Jeff Z. et al.
The Semantic Web -- ISWC 2016: 15th International Semantic Web Conference, Kobe, Japan, October 17–21, 2016, Proceedings, Part I. ed. / Paul Groth; Elena Simperl; Alasdair Gray; Marta Sabou; Markus Krötzsch; Freddy Lecue; Fabian Flöck; Yolanda Gil. Cham: Springer, 2016. p. 289-304 (Lecture Notes in Computer Science ; Vol. 9981).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Predicting Energy Consumption of Ontology Reasoning over Mobile Devices

AU - Guclu, Isa

AU - Li, Yuan-Fang

AU - Pan, Jeff Z.

AU - Kollingbaum, Martin J.

PY - 2016/9/23

Y1 - 2016/9/23

N2 - 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.

AB - 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.

KW - Energy

KW - Semantic web

KW - Ontology reasoning

KW - Mobile computing

KW - Prediction

KW - Random forests

U2 - 10.1007/978-3-319-46523-4_18

DO - 10.1007/978-3-319-46523-4_18

M3 - Conference contribution

SN - 978-3-319-46522-7

T3 - Lecture Notes in Computer Science

SP - 289

EP - 304

BT - The Semantic Web -- ISWC 2016

A2 - Groth, Paul

A2 - Simperl, Elena

A2 - Gray, Alasdair

A2 - Sabou, Marta

A2 - Krötzsch, Markus

A2 - Lecue, Freddy

A2 - Flöck, Fabian

A2 - Gil, Yolanda

PB - Springer

CY - Cham

T2 - The 15th International Semantic Web Conference

Y2 - 17 October 2016 through 21 October 2016

ER -

Guclu I, Li YF, Pan JZ, Kollingbaum MJ. Predicting Energy Consumption of Ontology Reasoning over Mobile Devices. In Groth P, Simperl E, Gray A, Sabou M, Krötzsch M, Lecue F, Flöck F, Gil Y, editors, The Semantic Web -- ISWC 2016: 15th International Semantic Web Conference, Kobe, Japan, October 17–21, 2016, Proceedings, Part I. Cham: Springer. 2016. p. 289-304. (Lecture Notes in Computer Science ). doi: 10.1007/978-3-319-46523-4_18

Predicting Energy Consumption of Ontology Reasoning over Mobile Devices

Abstract

Publication series

Conference

Keywords / Materials (for Non-textual outputs)

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Cite this