Service Placement and Request Scheduling for Data-intensive Applications in Edge Clouds

Vajiheh Farhadi; Fidan Mehmeti; Ting He; Tom La Porta; Hana Khamfroush; Shiqiang Wang; Kevin S. Chan

doi:10.1109/INFOCOM.2019.8737368

Service Placement and Request Scheduling for Data-intensive Applications in Edge Clouds

Vajiheh Farhadi, Fidan Mehmeti, Ting He, Tom La Porta, Hana Khamfroush, Shiqiang Wang, Kevin S. Chan

Computer Science

Producción científica: Conference contribution › revisión exhaustiva

164 Citas (Scopus)

Resumen

Mobile edge computing allows wireless users to exploit the power of cloud computing without the large communication delay. To serve data-intensive applications (e.g., augmented reality, video analytics) from the edge, we need, in addition to CPU cycles and memory for computation, storage resource for storing server data and network bandwidth for receiving user-provided data. Moreover, the data placement needs to be adapted over time to serve time-varying demands, while considering system stability and operation cost. We address this problem by proposing a two-time-scale framework that jointly optimizes service (data code) placement and request scheduling, under storage, communication, computation, and budget constraints. We fully characterize the complexity of our problem by analyzing the hardness of various cases. By casting our problem as a set function optimization, we develop a polynomial-time algorithm that achieves a constant-factor approximation under certain conditions. Extensive synthetic and trace-driven simulations show that the proposed algorithm achieves 90% of the optimal performance.

Idioma original	English
Título de la publicación alojada	INFOCOM 2019 - IEEE Conference on Computer Communications
Páginas	1279-1287
Número de páginas	9
ISBN (versión digital)	9781728105154
DOI	https://doi.org/10.1109/INFOCOM.2019.8737368
Estado	Published - abr 2019
Evento	2019 IEEE Conference on Computer Communications, INFOCOM 2019 - Paris, France Duración: abr 29 2019 → may 2 2019

Serie de la publicación

Nombre	Proceedings - IEEE INFOCOM
Volumen	2019-April
ISSN (versión impresa)	0743-166X

Conference

Conference	2019 IEEE Conference on Computer Communications, INFOCOM 2019
País/Territorio	France
Ciudad	Paris
Período	4/29/19 → 5/2/19

Nota bibliográfica

Publisher Copyright:
© 2019 IEEE.

Financiación

This research was sponsored by the U.S. Army Research Laboratory and the U.K. Ministry of Defence under Agreement Number W911NF-16-3-0001. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the U.S. Army Research Laboratory, the U.S. Government, the U.K. Ministry of Defence or the U.K. Government. The U.S. and U.K. Governments are authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation hereon.

Financiadores	Número del financiador
Army Research Laboratory
United Kingdom Ministry of Defence	W911NF-16-3-0001

ASJC Scopus subject areas

General Computer Science
Electrical and Electronic Engineering

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10.1109/INFOCOM.2019.8737368

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Farhadi, V., Mehmeti, F., He, T., Porta, T. L., Khamfroush, H., Wang, S., & Chan, K. S. (2019). Service Placement and Request Scheduling for Data-intensive Applications in Edge Clouds. En INFOCOM 2019 - IEEE Conference on Computer Communications (pp. 1279-1287). Artículo 8737368 (Proceedings - IEEE INFOCOM; Vol. 2019-April). https://doi.org/10.1109/INFOCOM.2019.8737368

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Farhadi, V, Mehmeti, F, He, T, Porta, TL, Khamfroush, H, Wang, S & Chan, KS 2019, Service Placement and Request Scheduling for Data-intensive Applications in Edge Clouds. En INFOCOM 2019 - IEEE Conference on Computer Communications., 8737368, Proceedings - IEEE INFOCOM, vol. 2019-April, pp. 1279-1287, 2019 IEEE Conference on Computer Communications, INFOCOM 2019, Paris, France, 4/29/19. https://doi.org/10.1109/INFOCOM.2019.8737368

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AU - Farhadi, Vajiheh

AU - Mehmeti, Fidan

AU - He, Ting

AU - Porta, Tom La

AU - Khamfroush, Hana

AU - Wang, Shiqiang

AU - Chan, Kevin S.

PY - 2019/4

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AB - Mobile edge computing allows wireless users to exploit the power of cloud computing without the large communication delay. To serve data-intensive applications (e.g., augmented reality, video analytics) from the edge, we need, in addition to CPU cycles and memory for computation, storage resource for storing server data and network bandwidth for receiving user-provided data. Moreover, the data placement needs to be adapted over time to serve time-varying demands, while considering system stability and operation cost. We address this problem by proposing a two-time-scale framework that jointly optimizes service (data code) placement and request scheduling, under storage, communication, computation, and budget constraints. We fully characterize the complexity of our problem by analyzing the hardness of various cases. By casting our problem as a set function optimization, we develop a polynomial-time algorithm that achieves a constant-factor approximation under certain conditions. Extensive synthetic and trace-driven simulations show that the proposed algorithm achieves 90% of the optimal performance.

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Service Placement and Request Scheduling for Data-intensive Applications in Edge Clouds

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