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Conference Papers Year : 2023

RAP-G: Reliability-aware service placement using genetic algorithm for deep edge computing

Abstract

To ensure low latency, service providers are increasingly turning to edge computing, pushing services and resources from the Cloud to the Edge of the network, as close as possible to users. However, since video and image processing applications are particularly computationally intensive, their deployment is typically based on distributed provisioning between the Edge and the Cloud, which can increase the risk of failure when relying on unreliable networks. In this work, we proposed the algorithm RAP-G (Reliability-Aware service Placement with Genetics), which considers the reliability of network links and distributes services between the Cloud and the Edge using a genetic algorithm (GA). We have also developed a new variant of the first-fit algorithm called RF2 (Reliability-Aware First-Fit) that considers reliability within a reasonable time. The performance of the RAP-G algorithm was evaluated and compared with the RF2 algorithm. The experimental results show the importance of considering reliability in service delivery and the superiority of RAP-G.
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Dates and versions

hal-04368569 , version 1 (01-01-2024)

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Abdellah Kaci, Soraya Aït-Chellouche, Yassine Hadjadj-Aoul, Miloud Bagaa. RAP-G: Reliability-aware service placement using genetic algorithm for deep edge computing. CCNC 2023 - IEEE 20th Consumer Communications & Networking Conference, Jan 2023, Las Vegas, United States. pp.255-260, ⟨10.1109/CCNC51644.2023.10060108⟩. ⟨hal-04368569⟩
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