End-to-end energy models for Edge Cloud-based IoT platforms : Application to data stream analysis in IoT

Yunbo Li; Anne Cécile Orgerie; Ivan Rodero; Betsegaw Lemma Amersho; Manish Parashar; Jean Marc Menaud

doi:10.1016/j.future.2017.12.048

End-to-end energy models for Edge Cloud-based IoT platforms : Application to data stream analysis in IoT

Yunbo Li
, Anne Cécile Orgerie^*
, Ivan Rodero
, Betsegaw Lemma Amersho
, Manish Parashar
, Jean Marc Menaud

^*Corresponding author for this work

Department of Computer Science

Research output: Contribution to journal › Article › Scientific › peer-review

71 Citations (Scopus)

Abstract

Internet of Things (IoT) is bringing an increasing number of connected devices that have a direct impact on the growth of data and energy-hungry services. These services are relying on Cloud infrastructures for storage and computing capabilities, transforming their architecture into more a distributed one based on edge facilities provided by Internet Service Providers (ISP). Yet, between the IoT device, communication network and Cloud infrastructure, it is unclear which part is the largest in terms of energy consumption. In this paper, we provide end-to-end energy models for Edge Cloud-based IoT platforms. These models are applied to a concrete scenario: data stream analysis produced by cameras embedded on vehicles. The validation combines measurements on real test-beds running the targeted application and simulations on well-known simulators for studying the scaling-up with an increasing number of IoT devices. Our results show that, for our scenario, the edge Cloud part embedding the computing resources consumes 3 times more than the IoT part comprising the IoT devices and the wireless access point.

Original language	English
Pages (from-to)	667-678
Number of pages	12
Journal	Future Generation Computer Systems
Volume	87
DOIs	https://doi.org/10.1016/j.future.2017.12.048
Publication status	Published - Oct 2018
MoE publication type	A1 Journal article-refereed

Funding

This work has received a French state support granted to the CominLabs excellence laboratory and managed by the National Research Agency in the “Investing for the Future” program under reference Nb. ANR-10-LABX-07-01. The research presented in this work is supported in part by National Science Foundation (NSF) via grants numbers ACI-1464317 , ACI-1339036 , ACI-1310283 , and CNS-1305375 . We thank Yifu Tang for numerous fruitful discussions.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Data stream analysis
Edge Cloud computing
End-to-end energy model
Energy-efficiency
IoT

Access to Document

10.1016/j.future.2017.12.048

Cite this

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title = "End-to-end energy models for Edge Cloud-based IoT platforms : Application to data stream analysis in IoT",

abstract = "Internet of Things (IoT) is bringing an increasing number of connected devices that have a direct impact on the growth of data and energy-hungry services. These services are relying on Cloud infrastructures for storage and computing capabilities, transforming their architecture into more a distributed one based on edge facilities provided by Internet Service Providers (ISP). Yet, between the IoT device, communication network and Cloud infrastructure, it is unclear which part is the largest in terms of energy consumption. In this paper, we provide end-to-end energy models for Edge Cloud-based IoT platforms. These models are applied to a concrete scenario: data stream analysis produced by cameras embedded on vehicles. The validation combines measurements on real test-beds running the targeted application and simulations on well-known simulators for studying the scaling-up with an increasing number of IoT devices. Our results show that, for our scenario, the edge Cloud part embedding the computing resources consumes 3 times more than the IoT part comprising the IoT devices and the wireless access point.",

keywords = "Data stream analysis, Edge Cloud computing, End-to-end energy model, Energy-efficiency, IoT",

author = "Yunbo Li and Orgerie, \{Anne C{\'e}cile\} and Ivan Rodero and Amersho, \{Betsegaw Lemma\} and Manish Parashar and Menaud, \{Jean Marc\}",

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AU - Li, Yunbo

AU - Orgerie, Anne Cécile

AU - Rodero, Ivan

AU - Amersho, Betsegaw Lemma

AU - Parashar, Manish

AU - Menaud, Jean Marc

PY - 2018/10

Y1 - 2018/10

N2 - Internet of Things (IoT) is bringing an increasing number of connected devices that have a direct impact on the growth of data and energy-hungry services. These services are relying on Cloud infrastructures for storage and computing capabilities, transforming their architecture into more a distributed one based on edge facilities provided by Internet Service Providers (ISP). Yet, between the IoT device, communication network and Cloud infrastructure, it is unclear which part is the largest in terms of energy consumption. In this paper, we provide end-to-end energy models for Edge Cloud-based IoT platforms. These models are applied to a concrete scenario: data stream analysis produced by cameras embedded on vehicles. The validation combines measurements on real test-beds running the targeted application and simulations on well-known simulators for studying the scaling-up with an increasing number of IoT devices. Our results show that, for our scenario, the edge Cloud part embedding the computing resources consumes 3 times more than the IoT part comprising the IoT devices and the wireless access point.

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KW - Data stream analysis

KW - Edge Cloud computing

KW - End-to-end energy model

KW - Energy-efficiency

KW - IoT

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ER -

End-to-end energy models for Edge Cloud-based IoT platforms : Application to data stream analysis in IoT

Abstract

Funding

UN SDGs

Keywords

Access to Document

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