Performance estimation of container-based cloud-to-fog ofloading

Ayesha Abdul Majeed; Blesson Varghese; Ivor Spence; Peter Kilpatrick

doi:10.1145/3368235.3368847

Performance estimation of container-based cloud-to-fog ofloading

Ayesha Abdul Majeed, Blesson Varghese, Ivor Spence, Peter Kilpatrick

School of Electronics, Electrical Engineering and Computer Science

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

10 Citations (Scopus)

Abstract

Fog computing oloads latency critical services of a Cloud application onto resources located at the edge of the network that are in close proximity to end-user devices. The research in this paper is motivated towards characterising and estimating the time taken to oload a service using containers, which is investigated in the context of the ‘Save and Load’ container migration technique. To this end, the research addresses questions such as whether fog ofloading can be accurately modelled and which system and network related parameters inluence oloading. These are addressed by exploring a catalogue of 21 diferent metrics both at the system and process levels that is used as input to four estimation techniques using a collective model and individual models to predict the time taken for oloading. The study is pursued by collecting over 1.1 million data points and the preliminary results indicate that oloading can be modelled accurately.

Original language	English
Title of host publication	UCC 2019 Companion - Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing
Publisher	Association for Computing Machinery
Pages	151-156
ISBN (Electronic)	9781450370448
DOIs	https://doi.org/10.1145/3368235.3368847
Publication status	Published - 02 Dec 2019
Event	12th IEEE/ACM International Conference on Utility and Cloud Computing, UCC Companion 2019 - Auckland, New Zealand Duration: 02 Dec 2019 → 05 Dec 2019

Publication series

Name	UCC 2019 Companion - Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing

Conference

Conference	12th IEEE/ACM International Conference on Utility and Cloud Computing, UCC Companion 2019
Country/Territory	New Zealand
City	Auckland
Period	02/12/2019 → 05/12/2019

Keywords

Containers
Edge computing
Fog computing
Oloading

ASJC Scopus subject areas

Computer Networks and Communications
Hardware and Architecture

Access to Document

10.1145/3368235.3368847Licence: Unspecified

Strategies for maintaining efficiency of edge services
Abdul Majeed, A. (Author), Spence, I. (Supervisor) & Varghese, B. (Supervisor), Jul 2023
Student thesis: Doctoral Thesis › Doctor of Philosophy

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Cite this

Abdul Majeed, A., Varghese, B., Spence, I., & Kilpatrick, P. (2019). Performance estimation of container-based cloud-to-fog ofloading. In UCC 2019 Companion - Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing (pp. 151-156). (UCC 2019 Companion - Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing). Association for Computing Machinery. https://doi.org/10.1145/3368235.3368847

Abdul Majeed, Ayesha ; Varghese, Blesson ; Spence, Ivor et al. / Performance estimation of container-based cloud-to-fog ofloading. UCC 2019 Companion - Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing. Association for Computing Machinery, 2019. pp. 151-156 (UCC 2019 Companion - Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing).

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title = "Performance estimation of container-based cloud-to-fog ofloading",

abstract = "Fog computing oloads latency critical services of a Cloud application onto resources located at the edge of the network that are in close proximity to end-user devices. The research in this paper is motivated towards characterising and estimating the time taken to oload a service using containers, which is investigated in the context of the {\textquoteleft}Save and Load{\textquoteright} container migration technique. To this end, the research addresses questions such as whether fog ofloading can be accurately modelled and which system and network related parameters inluence oloading. These are addressed by exploring a catalogue of 21 diferent metrics both at the system and process levels that is used as input to four estimation techniques using a collective model and individual models to predict the time taken for oloading. The study is pursued by collecting over 1.1 million data points and the preliminary results indicate that oloading can be modelled accurately.",

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Abdul Majeed, A, Varghese, B, Spence, I & Kilpatrick, P 2019, Performance estimation of container-based cloud-to-fog ofloading. in UCC 2019 Companion - Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing. UCC 2019 Companion - Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing, Association for Computing Machinery, pp. 151-156, 12th IEEE/ACM International Conference on Utility and Cloud Computing, UCC Companion 2019, Auckland, New Zealand, 02/12/2019. https://doi.org/10.1145/3368235.3368847

Performance estimation of container-based cloud-to-fog ofloading. / Abdul Majeed, Ayesha; Varghese, Blesson; Spence, Ivor et al.
UCC 2019 Companion - Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing. Association for Computing Machinery, 2019. p. 151-156 (UCC 2019 Companion - Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing).

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

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AU - Abdul Majeed, Ayesha

AU - Varghese, Blesson

AU - Spence, Ivor

AU - Kilpatrick, Peter

PY - 2019/12/2

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N2 - Fog computing oloads latency critical services of a Cloud application onto resources located at the edge of the network that are in close proximity to end-user devices. The research in this paper is motivated towards characterising and estimating the time taken to oload a service using containers, which is investigated in the context of the ‘Save and Load’ container migration technique. To this end, the research addresses questions such as whether fog ofloading can be accurately modelled and which system and network related parameters inluence oloading. These are addressed by exploring a catalogue of 21 diferent metrics both at the system and process levels that is used as input to four estimation techniques using a collective model and individual models to predict the time taken for oloading. The study is pursued by collecting over 1.1 million data points and the preliminary results indicate that oloading can be modelled accurately.

AB - Fog computing oloads latency critical services of a Cloud application onto resources located at the edge of the network that are in close proximity to end-user devices. The research in this paper is motivated towards characterising and estimating the time taken to oload a service using containers, which is investigated in the context of the ‘Save and Load’ container migration technique. To this end, the research addresses questions such as whether fog ofloading can be accurately modelled and which system and network related parameters inluence oloading. These are addressed by exploring a catalogue of 21 diferent metrics both at the system and process levels that is used as input to four estimation techniques using a collective model and individual models to predict the time taken for oloading. The study is pursued by collecting over 1.1 million data points and the preliminary results indicate that oloading can be modelled accurately.

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Abdul Majeed A, Varghese B, Spence I , Kilpatrick P. Performance estimation of container-based cloud-to-fog ofloading. In UCC 2019 Companion - Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing. Association for Computing Machinery. 2019. p. 151-156. (UCC 2019 Companion - Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing). doi: 10.1145/3368235.3368847

Performance estimation of container-based cloud-to-fog ofloading

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Student theses

Strategies for maintaining efficiency of edge services

Cite this