Improving Energy Saving Techniques by Ambient Intelligence Scheduling

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedings – Annual report year: 2015Researchpeer-review

Standard

Improving Energy Saving Techniques by Ambient Intelligence Scheduling. / Cristani, Matteo; Karafili, Erisa; Tomazzoli, Claudio.

Proceedings of the Proceedings IEEE 29th International Conference on Advanced Information Networking and Applications (AINA 2015). ed. / Leonard Barolli; Makoto Takizawa; Fatos Xhafa; Tomoya Enokido; Jong Hyuk Park. IEEE, 2015. p. 324-331.

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedings – Annual report year: 2015Researchpeer-review

Harvard

Cristani, M, Karafili, E & Tomazzoli, C 2015, Improving Energy Saving Techniques by Ambient Intelligence Scheduling. in L Barolli, M Takizawa, F Xhafa, T Enokido & JH Park (eds), Proceedings of the Proceedings IEEE 29th International Conference on Advanced Information Networking and Applications (AINA 2015). IEEE, pp. 324-331, 29th IEEE International Conference on Advanced Information Networking and Applications (AINA 2015), Gwangju, Korea, Democratic People's Republic of, 25/03/2015. https://doi.org/10.1109/AINA.2015.202

APA

Cristani, M., Karafili, E., & Tomazzoli, C. (2015). Improving Energy Saving Techniques by Ambient Intelligence Scheduling. In L. Barolli, M. Takizawa, F. Xhafa, T. Enokido, & J. H. Park (Eds.), Proceedings of the Proceedings IEEE 29th International Conference on Advanced Information Networking and Applications (AINA 2015) (pp. 324-331). IEEE. https://doi.org/10.1109/AINA.2015.202

CBE

Cristani M, Karafili E, Tomazzoli C. 2015. Improving Energy Saving Techniques by Ambient Intelligence Scheduling. Barolli L, Takizawa M, Xhafa F, Enokido T, Park JH, editors. In Proceedings of the Proceedings IEEE 29th International Conference on Advanced Information Networking and Applications (AINA 2015). IEEE. pp. 324-331. https://doi.org/10.1109/AINA.2015.202

MLA

Cristani, Matteo, Erisa Karafili and Claudio Tomazzoli "Improving Energy Saving Techniques by Ambient Intelligence Scheduling"., Barolli, Leonard , Takizawa, Makoto Xhafa, Fatos Enokido, Tomoya Park, Jong Hyuk (editors). Proceedings of the Proceedings IEEE 29th International Conference on Advanced Information Networking and Applications (AINA 2015). IEEE. 2015, 324-331. https://doi.org/10.1109/AINA.2015.202

Vancouver

Cristani M, Karafili E, Tomazzoli C. Improving Energy Saving Techniques by Ambient Intelligence Scheduling. In Barolli L, Takizawa M, Xhafa F, Enokido T, Park JH, editors, Proceedings of the Proceedings IEEE 29th International Conference on Advanced Information Networking and Applications (AINA 2015). IEEE. 2015. p. 324-331 https://doi.org/10.1109/AINA.2015.202

Author

Cristani, Matteo ; Karafili, Erisa ; Tomazzoli, Claudio. / Improving Energy Saving Techniques by Ambient Intelligence Scheduling. Proceedings of the Proceedings IEEE 29th International Conference on Advanced Information Networking and Applications (AINA 2015). editor / Leonard Barolli ; Makoto Takizawa ; Fatos Xhafa ; Tomoya Enokido ; Jong Hyuk Park. IEEE, 2015. pp. 324-331

Bibtex

@inproceedings{9b15d412ad9a404a9c8ae533a91e257e,
title = "Improving Energy Saving Techniques by Ambient Intelligence Scheduling",
abstract = "Energy saving is one of the most challenging aspects of modern ambient intelligence technologies, for both domestic and business usages. In this paper we show how to combine Ambient Intelligence and Artificial Intelligence techniques to solve the problem of scheduling a set of devices under a given set of constraints, like limits to the maximal energy usage (Energy Span) and maximal energy absorption (Energy Peak). We provide a method that can be used to schedule the usage of devices in a given environment in a way that respects the input constraints. We adapt an existent approach to scheduling for Ambient Intelligence to a specific framework and exhibit a sample usage for a real life system, Elettra, that is in use in an industrial context.",
keywords = "Communication, Networking and Broadcast Technologies, Computing and Processing, Absorption, Ambient intelligence, Energy consumption, Performance evaluation, Plugs, Servers, Time factors",
author = "Matteo Cristani and Erisa Karafili and Claudio Tomazzoli",
year = "2015",
doi = "10.1109/AINA.2015.202",
language = "English",
isbn = "978-1-4799-7904-2",
pages = "324--331",
editor = "Barolli, {Leonard } and Takizawa, {Makoto } and Xhafa, {Fatos } and Enokido, {Tomoya } and Park, {Jong Hyuk}",
booktitle = "Proceedings of the Proceedings IEEE 29th International Conference on Advanced Information Networking and Applications (AINA 2015)",
publisher = "IEEE",

}

RIS

TY - GEN

T1 - Improving Energy Saving Techniques by Ambient Intelligence Scheduling

AU - Cristani, Matteo

AU - Karafili, Erisa

AU - Tomazzoli, Claudio

PY - 2015

Y1 - 2015

N2 - Energy saving is one of the most challenging aspects of modern ambient intelligence technologies, for both domestic and business usages. In this paper we show how to combine Ambient Intelligence and Artificial Intelligence techniques to solve the problem of scheduling a set of devices under a given set of constraints, like limits to the maximal energy usage (Energy Span) and maximal energy absorption (Energy Peak). We provide a method that can be used to schedule the usage of devices in a given environment in a way that respects the input constraints. We adapt an existent approach to scheduling for Ambient Intelligence to a specific framework and exhibit a sample usage for a real life system, Elettra, that is in use in an industrial context.

AB - Energy saving is one of the most challenging aspects of modern ambient intelligence technologies, for both domestic and business usages. In this paper we show how to combine Ambient Intelligence and Artificial Intelligence techniques to solve the problem of scheduling a set of devices under a given set of constraints, like limits to the maximal energy usage (Energy Span) and maximal energy absorption (Energy Peak). We provide a method that can be used to schedule the usage of devices in a given environment in a way that respects the input constraints. We adapt an existent approach to scheduling for Ambient Intelligence to a specific framework and exhibit a sample usage for a real life system, Elettra, that is in use in an industrial context.

KW - Communication, Networking and Broadcast Technologies

KW - Computing and Processing

KW - Absorption

KW - Ambient intelligence

KW - Energy consumption

KW - Performance evaluation

KW - Plugs

KW - Servers

KW - Time factors

U2 - 10.1109/AINA.2015.202

DO - 10.1109/AINA.2015.202

M3 - Article in proceedings

SN - 978-1-4799-7904-2

SP - 324

EP - 331

BT - Proceedings of the Proceedings IEEE 29th International Conference on Advanced Information Networking and Applications (AINA 2015)

A2 - Barolli, Leonard

A2 - Takizawa, Makoto

A2 - Xhafa, Fatos

A2 - Enokido, Tomoya

A2 - Park, Jong Hyuk

PB - IEEE

ER -