Multilayer resource-aware partitioning for fog application placement

Zahra Najafabadi Samani; Nishant Saurabh; Radu Prodan

doi:10.1109/ICFEC51620.2021.00010

Multilayer resource-aware partitioning for fog application placement

Zahra Najafabadi Samani, Nishant Saurabh, Radu Prodan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

Fog computing emerged as a crucial platform for the deployment of IoT applications. The complexity of such applications require methods that handle the resource diversity and network structure of Fog devices, while maximizing the service placement and reducing the resource wastage. Prior studies in this domain primarily focused on optimizing application-specific requirements and fail to address the network topology combined with the different types of resources encountered in Fog devices. To overcome these problems, we propose a multilayer resource-aware partitioning method to minimize the resource wastage and maximize the service placement and deadline satisfaction rates in a Fog infrastructure with high multi-user application placement requests. Our method represents the heterogeneous Fog resources as a multilayered network graph and partitions them based on network topology and resource features. Afterwards, it identifies the appropriate device partitions for placing an application according to its requirements, which need to overlap in the same network topology partition. Simulation results show that our multilayer resource-aware partitioning method is able to place twice as many services, satisfy deadlines for three times as many application requests, and reduce the resource wastage by up to 15-32 times compared to two availability-aware and resource-aware state-of-the-art methods.

Original language	English
Title of host publication	Proceedings - 5th IEEE International Conference on Fog and Edge Computing, ICFEC 2021
Editors	Yogesh Simmhan, Blesson Varghese, Lena Mashayekhy, Raj Buyya, Omer Rana
Publisher	IEEE
Pages	9-18
Number of pages	10
ISBN (Electronic)	9781665402910
DOIs	https://doi.org/10.1109/ICFEC51620.2021.00010
Publication status	Published - May 2021
Event	5th IEEE International Conference on Fog and Edge Computing, ICFEC 2021 - Virtual, Online Duration: 10 May 2021 → …

Publication series

Name	Proceedings - 5th IEEE International Conference on Fog and Edge Computing, ICFEC 2021

Conference

Conference	5th IEEE International Conference on Fog and Edge Computing, ICFEC 2021
City	Virtual, Online
Period	10/05/21 → …

Bibliographical note

Funding Information:
a) European Union’s Horizon 2020: research and innovation programme funded this work though two grants: • ARTICONF: “Smart Social Media Ecosytstem in a Blockchain Federated Environment” (grant 825134); « DataCloud: “Enabling the Big Data Pipeline Lifecycle on the Computing Continuum” (grant 101016835). b) Carinthian AgencyforInvestment Promotionand Public Shareholding (BABEG): supported the use case application and Fog infrastructure simulation.

Publisher Copyright:
© 2021 IEEE.

Funding

a) European Union’s Horizon 2020: research and innovation programme funded this work though two grants: • ARTICONF: “Smart Social Media Ecosytstem in a Blockchain Federated Environment” (grant 825134); « DataCloud: “Enabling the Big Data Pipeline Lifecycle on the Computing Continuum” (grant 101016835). b) Carinthian AgencyforInvestment Promotionand Public Shareholding (BABEG): supported the use case application and Fog infrastructure simulation.

Keywords

application placement
deadline satisfaction.
Fog computing
resource partitioning
resource wastage

Access to Document

10.1109/ICFEC51620.2021.00010

Cite this

Samani, Z. N., Saurabh, N., & Prodan, R. (2021). Multilayer resource-aware partitioning for fog application placement. In Y. Simmhan, B. Varghese, L. Mashayekhy, R. Buyya, & O. Rana (Eds.), Proceedings - 5th IEEE International Conference on Fog and Edge Computing, ICFEC 2021 (pp. 9-18). Article 9458908 (Proceedings - 5th IEEE International Conference on Fog and Edge Computing, ICFEC 2021). IEEE. https://doi.org/10.1109/ICFEC51620.2021.00010

Samani, Zahra Najafabadi ; Saurabh, Nishant ; Prodan, Radu. / Multilayer resource-aware partitioning for fog application placement. Proceedings - 5th IEEE International Conference on Fog and Edge Computing, ICFEC 2021. editor / Yogesh Simmhan ; Blesson Varghese ; Lena Mashayekhy ; Raj Buyya ; Omer Rana. IEEE, 2021. pp. 9-18 (Proceedings - 5th IEEE International Conference on Fog and Edge Computing, ICFEC 2021).

@inproceedings{3c851f035feb46a4b787ffd2fdd90ef2,

title = "Multilayer resource-aware partitioning for fog application placement",

abstract = "Fog computing emerged as a crucial platform for the deployment of IoT applications. The complexity of such applications require methods that handle the resource diversity and network structure of Fog devices, while maximizing the service placement and reducing the resource wastage. Prior studies in this domain primarily focused on optimizing application-specific requirements and fail to address the network topology combined with the different types of resources encountered in Fog devices. To overcome these problems, we propose a multilayer resource-aware partitioning method to minimize the resource wastage and maximize the service placement and deadline satisfaction rates in a Fog infrastructure with high multi-user application placement requests. Our method represents the heterogeneous Fog resources as a multilayered network graph and partitions them based on network topology and resource features. Afterwards, it identifies the appropriate device partitions for placing an application according to its requirements, which need to overlap in the same network topology partition. Simulation results show that our multilayer resource-aware partitioning method is able to place twice as many services, satisfy deadlines for three times as many application requests, and reduce the resource wastage by up to 15-32 times compared to two availability-aware and resource-aware state-of-the-art methods. ",

keywords = "application placement, deadline satisfaction., Fog computing, resource partitioning, resource wastage",

author = "Samani, {Zahra Najafabadi} and Nishant Saurabh and Radu Prodan",

note = "Funding Information: a) European Union{\textquoteright}s Horizon 2020: research and innovation programme funded this work though two grants: • ARTICONF: “Smart Social Media Ecosytstem in a Blockchain Federated Environment” (grant 825134); « DataCloud: “Enabling the Big Data Pipeline Lifecycle on the Computing Continuum” (grant 101016835). b) Carinthian AgencyforInvestment Promotionand Public Shareholding (BABEG): supported the use case application and Fog infrastructure simulation. Publisher Copyright: {\textcopyright} 2021 IEEE.; 5th IEEE International Conference on Fog and Edge Computing, ICFEC 2021 ; Conference date: 10-05-2021",

year = "2021",

month = may,

doi = "10.1109/ICFEC51620.2021.00010",

language = "English",

series = "Proceedings - 5th IEEE International Conference on Fog and Edge Computing, ICFEC 2021",

publisher = "IEEE",

pages = "9--18",

editor = "Yogesh Simmhan and Blesson Varghese and Lena Mashayekhy and Raj Buyya and Omer Rana",

booktitle = "Proceedings - 5th IEEE International Conference on Fog and Edge Computing, ICFEC 2021",

address = "United States",

}

Samani, ZN, Saurabh, N & Prodan, R 2021, Multilayer resource-aware partitioning for fog application placement. in Y Simmhan, B Varghese, L Mashayekhy, R Buyya & O Rana (eds), Proceedings - 5th IEEE International Conference on Fog and Edge Computing, ICFEC 2021., 9458908, Proceedings - 5th IEEE International Conference on Fog and Edge Computing, ICFEC 2021, IEEE, pp. 9-18, 5th IEEE International Conference on Fog and Edge Computing, ICFEC 2021, Virtual, Online, 10/05/21. https://doi.org/10.1109/ICFEC51620.2021.00010

Multilayer resource-aware partitioning for fog application placement. / Samani, Zahra Najafabadi; Saurabh, Nishant; Prodan, Radu.
Proceedings - 5th IEEE International Conference on Fog and Edge Computing, ICFEC 2021. ed. / Yogesh Simmhan; Blesson Varghese; Lena Mashayekhy; Raj Buyya; Omer Rana. IEEE, 2021. p. 9-18 9458908 (Proceedings - 5th IEEE International Conference on Fog and Edge Computing, ICFEC 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Multilayer resource-aware partitioning for fog application placement

AU - Samani, Zahra Najafabadi

AU - Saurabh, Nishant

AU - Prodan, Radu

N1 - Funding Information: a) European Union’s Horizon 2020: research and innovation programme funded this work though two grants: • ARTICONF: “Smart Social Media Ecosytstem in a Blockchain Federated Environment” (grant 825134); « DataCloud: “Enabling the Big Data Pipeline Lifecycle on the Computing Continuum” (grant 101016835). b) Carinthian AgencyforInvestment Promotionand Public Shareholding (BABEG): supported the use case application and Fog infrastructure simulation. Publisher Copyright: © 2021 IEEE.

PY - 2021/5

Y1 - 2021/5

N2 - Fog computing emerged as a crucial platform for the deployment of IoT applications. The complexity of such applications require methods that handle the resource diversity and network structure of Fog devices, while maximizing the service placement and reducing the resource wastage. Prior studies in this domain primarily focused on optimizing application-specific requirements and fail to address the network topology combined with the different types of resources encountered in Fog devices. To overcome these problems, we propose a multilayer resource-aware partitioning method to minimize the resource wastage and maximize the service placement and deadline satisfaction rates in a Fog infrastructure with high multi-user application placement requests. Our method represents the heterogeneous Fog resources as a multilayered network graph and partitions them based on network topology and resource features. Afterwards, it identifies the appropriate device partitions for placing an application according to its requirements, which need to overlap in the same network topology partition. Simulation results show that our multilayer resource-aware partitioning method is able to place twice as many services, satisfy deadlines for three times as many application requests, and reduce the resource wastage by up to 15-32 times compared to two availability-aware and resource-aware state-of-the-art methods.

AB - Fog computing emerged as a crucial platform for the deployment of IoT applications. The complexity of such applications require methods that handle the resource diversity and network structure of Fog devices, while maximizing the service placement and reducing the resource wastage. Prior studies in this domain primarily focused on optimizing application-specific requirements and fail to address the network topology combined with the different types of resources encountered in Fog devices. To overcome these problems, we propose a multilayer resource-aware partitioning method to minimize the resource wastage and maximize the service placement and deadline satisfaction rates in a Fog infrastructure with high multi-user application placement requests. Our method represents the heterogeneous Fog resources as a multilayered network graph and partitions them based on network topology and resource features. Afterwards, it identifies the appropriate device partitions for placing an application according to its requirements, which need to overlap in the same network topology partition. Simulation results show that our multilayer resource-aware partitioning method is able to place twice as many services, satisfy deadlines for three times as many application requests, and reduce the resource wastage by up to 15-32 times compared to two availability-aware and resource-aware state-of-the-art methods.

KW - application placement

KW - deadline satisfaction.

KW - Fog computing

KW - resource partitioning

KW - resource wastage

UR - http://www.scopus.com/inward/record.url?scp=85113809601&partnerID=8YFLogxK

U2 - 10.1109/ICFEC51620.2021.00010

DO - 10.1109/ICFEC51620.2021.00010

M3 - Conference contribution

AN - SCOPUS:85113809601

T3 - Proceedings - 5th IEEE International Conference on Fog and Edge Computing, ICFEC 2021

SP - 9

EP - 18

BT - Proceedings - 5th IEEE International Conference on Fog and Edge Computing, ICFEC 2021

A2 - Simmhan, Yogesh

A2 - Varghese, Blesson

A2 - Mashayekhy, Lena

A2 - Buyya, Raj

A2 - Rana, Omer

PB - IEEE

T2 - 5th IEEE International Conference on Fog and Edge Computing, ICFEC 2021

Y2 - 10 May 2021

ER -

Samani ZN, Saurabh N, Prodan R. Multilayer resource-aware partitioning for fog application placement. In Simmhan Y, Varghese B, Mashayekhy L, Buyya R, Rana O, editors, Proceedings - 5th IEEE International Conference on Fog and Edge Computing, ICFEC 2021. IEEE. 2021. p. 9-18. 9458908. (Proceedings - 5th IEEE International Conference on Fog and Edge Computing, ICFEC 2021). doi: 10.1109/ICFEC51620.2021.00010

Multilayer resource-aware partitioning for fog application placement

Abstract

Publication series

Conference

Bibliographical note

Funding

Keywords

Access to Document

Other files and links

Fingerprint

Cite this