Almurshed, Osama, Meshoul, Souham, Muftah, Asmail, Kaushal, Ashish Kumar, Almoghamis, Osama, Petri, Ioan  ORCID: https://orcid.org/0000-0002-1625-8247, Auluck, Nitin and Rana, Omer ORCID: https://orcid.org/0000-0003-3597-2646
2024.
A framework for performance optimization of internet of things applications.
Presented at: Euro-Par 2023: Parallel Processing Workshops,
Limassol, Cyprus,
28 August - 01 September 2023.
Euro-Par 2023: Parallel Processing Workshops. Euro-Par 2023.
Lecture Notes in Computer Science
, vol.14351
Cham, Switzerland:
Springer,
pp. 165-176.
10.1007/978-3-031-50684-0_13
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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.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Date Type: | Published Online |
| Status: | Published |
| Schools: | Schools > Computer Science & Informatics |
| Publisher: | Springer |
| ISBN: | 9783031506833 |
| ISSN: | 0302-9743 |
| Date of First Compliant Deposit: | 28 May 2024 |
| Date of Acceptance: | 15 February 2023 |
| Last Modified: | 29 Apr 2025 14:23 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/169232 |
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