A framework for performance optimization of internet of things applications

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:	Computer Science & Informatics
Publisher:	Springer
ISBN:	978-3-031-50683-3
Date of First Compliant Deposit:	28 May 2024
Date of Acceptance:	15 February 2023
Last Modified:	02 Aug 2024 01:30
URI:	https://orca.cardiff.ac.uk/id/eprint/169232

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