A Framework for Performance Optimization of Internet of Things Applications

Osama Almurshed; Souham Meshoul; Asmail Muftah; Ashish Kumar Kaushal; Osama Almoghamis; Ioan Petri; Nitin Auluck; Omer Rana

doi:10.1007/978-3-031-50684-0_13

A Framework for Performance Optimization of Internet of Things Applications

Osama Almurshed
, Souham Meshoul
, Asmail Muftah
, Ashish Kumar Kaushal
, Osama Almoghamis
, Ioan Petri
, Nitin Auluck
, Omer Rana

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

1 Scopus citations

Abstract

A framework to support optimised application placement across the cloud-edge continuum is described, making use of the Optimized-Greedy Nominator Heuristic (EO-GNH). The framework can be employed across a range of different Internet of Things (IoT) applications, such as smart agriculture and healthcare. The framework uses asynchronous MapReduce and parallel meta-heuristics to support the management of IoT applications, focusing on metrics such as execution performance, resource utilization and system resilience. We evaluate EO-GNH using service quality achieved through real-time resource management, across multiple application domains. Performance analysis and optimisation of EO-GNH has also been carried out to demonstrate how it can be configured for use across different IoT usage contexts.

Original language	English
Title of host publication	Euro-Par 2023
Subtitle of host publication	Parallel Processing Workshops - Euro-Par 2023 International Workshops, Limassol, Cyprus, August 28 – September 1, 2023, Revised Selected Papers
Editors	Demetris Zeinalipour, Dora Blanco Heras, George Pallis, Herodotos Herodotou, Demetris Trihinas, Daniel Balouek, Patrick Diehl, Terry Cojean, Karl Fürlinger, Maja Hanne Kirkeby, Matteo Nardelli, Pierangelo Di Sanzo
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	165-176
Number of pages	12
ISBN (Print)	9783031506833
DOIs	https://doi.org/10.1007/978-3-031-50684-0_13
State	Published - 2024
Externally published	Yes
Event	International workshops held at the 29th International Conference on Parallel and Distributed Computing, Euro-Par 2023 - Limassol, Cyprus Duration: 28 Aug 2023 → 1 Sep 2023

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	14351 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International workshops held at the 29th International Conference on Parallel and Distributed Computing, Euro-Par 2023
Country/Territory	Cyprus
City	Limassol
Period	28/08/23 → 1/09/23

Keywords

Cancer Classification
Edge Computing
Industrial IoT
IoT Management
Meta-heuristics
Precision Agriculture
System Resilience

UN SDGs

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

Access to Document

10.1007/978-3-031-50684-0_13

Cite this

Almurshed, O., Meshoul, S., Muftah, A., Kaushal, A. K., Almoghamis, O., Petri, I., Auluck, N., & Rana, O. (2024). A Framework for Performance Optimization of Internet of Things Applications. In D. Zeinalipour, D. Blanco Heras, G. Pallis, H. Herodotou, D. Trihinas, D. Balouek, P. Diehl, T. Cojean, K. Fürlinger, M. H. Kirkeby, M. Nardelli, & P. Di Sanzo (Eds.), Euro-Par 2023: Parallel Processing Workshops - Euro-Par 2023 International Workshops, Limassol, Cyprus, August 28 – September 1, 2023, Revised Selected Papers (pp. 165-176). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14351 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-50684-0_13

Almurshed, Osama ; Meshoul, Souham ; Muftah, Asmail et al. / A Framework for Performance Optimization of Internet of Things Applications. Euro-Par 2023: Parallel Processing Workshops - Euro-Par 2023 International Workshops, Limassol, Cyprus, August 28 – September 1, 2023, Revised Selected Papers. editor / Demetris Zeinalipour ; Dora Blanco Heras ; George Pallis ; Herodotos Herodotou ; Demetris Trihinas ; Daniel Balouek ; Patrick Diehl ; Terry Cojean ; Karl Fürlinger ; Maja Hanne Kirkeby ; Matteo Nardelli ; Pierangelo Di Sanzo. Springer Science and Business Media Deutschland GmbH, 2024. pp. 165-176 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "A framework to support optimised application placement across the cloud-edge continuum is described, making use of the Optimized-Greedy Nominator Heuristic (EO-GNH). The framework can be employed across a range of different Internet of Things (IoT) applications, such as smart agriculture and healthcare. The framework uses asynchronous MapReduce and parallel meta-heuristics to support the management of IoT applications, focusing on metrics such as execution performance, resource utilization and system resilience. We evaluate EO-GNH using service quality achieved through real-time resource management, across multiple application domains. Performance analysis and optimisation of EO-GNH has also been carried out to demonstrate how it can be configured for use across different IoT usage contexts.",

keywords = "Cancer Classification, Edge Computing, Industrial IoT, IoT Management, Meta-heuristics, Precision Agriculture, System Resilience",

author = "Osama Almurshed and Souham Meshoul and Asmail Muftah and Kaushal, \{Ashish Kumar\} and Osama Almoghamis and Ioan Petri and Nitin Auluck and Omer Rana",

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Almurshed, O, Meshoul, S, Muftah, A, Kaushal, AK, Almoghamis, O, Petri, I, Auluck, N & Rana, O 2024, A Framework for Performance Optimization of Internet of Things Applications. in D Zeinalipour, D Blanco Heras, G Pallis, H Herodotou, D Trihinas, D Balouek, P Diehl, T Cojean, K Fürlinger, MH Kirkeby, M Nardelli & P Di Sanzo (eds), Euro-Par 2023: Parallel Processing Workshops - Euro-Par 2023 International Workshops, Limassol, Cyprus, August 28 – September 1, 2023, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14351 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 165-176, International workshops held at the 29th International Conference on Parallel and Distributed Computing, Euro-Par 2023, Limassol, Cyprus, 28/08/23. https://doi.org/10.1007/978-3-031-50684-0_13

A Framework for Performance Optimization of Internet of Things Applications. / Almurshed, Osama; Meshoul, Souham; Muftah, Asmail et al.
Euro-Par 2023: Parallel Processing Workshops - Euro-Par 2023 International Workshops, Limassol, Cyprus, August 28 – September 1, 2023, Revised Selected Papers. ed. / Demetris Zeinalipour; Dora Blanco Heras; George Pallis; Herodotos Herodotou; Demetris Trihinas; Daniel Balouek; Patrick Diehl; Terry Cojean; Karl Fürlinger; Maja Hanne Kirkeby; Matteo Nardelli; Pierangelo Di Sanzo. Springer Science and Business Media Deutschland GmbH, 2024. p. 165-176 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14351 LNCS).

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

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AU - Almurshed, Osama

AU - Meshoul, Souham

AU - Muftah, Asmail

AU - Kaushal, Ashish Kumar

AU - Almoghamis, Osama

AU - Petri, Ioan

AU - Auluck, Nitin

AU - Rana, Omer

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

PY - 2024

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N2 - A framework to support optimised application placement across the cloud-edge continuum is described, making use of the Optimized-Greedy Nominator Heuristic (EO-GNH). The framework can be employed across a range of different Internet of Things (IoT) applications, such as smart agriculture and healthcare. The framework uses asynchronous MapReduce and parallel meta-heuristics to support the management of IoT applications, focusing on metrics such as execution performance, resource utilization and system resilience. We evaluate EO-GNH using service quality achieved through real-time resource management, across multiple application domains. Performance analysis and optimisation of EO-GNH has also been carried out to demonstrate how it can be configured for use across different IoT usage contexts.

AB - A framework to support optimised application placement across the cloud-edge continuum is described, making use of the Optimized-Greedy Nominator Heuristic (EO-GNH). The framework can be employed across a range of different Internet of Things (IoT) applications, such as smart agriculture and healthcare. The framework uses asynchronous MapReduce and parallel meta-heuristics to support the management of IoT applications, focusing on metrics such as execution performance, resource utilization and system resilience. We evaluate EO-GNH using service quality achieved through real-time resource management, across multiple application domains. Performance analysis and optimisation of EO-GNH has also been carried out to demonstrate how it can be configured for use across different IoT usage contexts.

KW - Cancer Classification

KW - Edge Computing

KW - Industrial IoT

KW - IoT Management

KW - Meta-heuristics

KW - Precision Agriculture

KW - System Resilience

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AN - SCOPUS:85192223534

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A2 - Diehl, Patrick

A2 - Cojean, Terry

A2 - Fürlinger, Karl

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A2 - Nardelli, Matteo

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Almurshed O, Meshoul S, Muftah A, Kaushal AK, Almoghamis O, Petri I et al. A Framework for Performance Optimization of Internet of Things Applications. In Zeinalipour D, Blanco Heras D, Pallis G, Herodotou H, Trihinas D, Balouek D, Diehl P, Cojean T, Fürlinger K, Kirkeby MH, Nardelli M, Di Sanzo P, editors, Euro-Par 2023: Parallel Processing Workshops - Euro-Par 2023 International Workshops, Limassol, Cyprus, August 28 – September 1, 2023, Revised Selected Papers. Springer Science and Business Media Deutschland GmbH. 2024. p. 165-176. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-50684-0_13