Szczegóły publikacji
Opis bibliograficzny
MicroFaaS: adaptive serverless computing for Internet of Things / Olgierd Królik, Tomasz SZYDŁO // Future Generation Computer Systems ; ISSN 0167-739X. — 2026 — vol. 174 art. no. 107914, s. 1–9. — Bibliogr. s. 8–9, Abstr. — Publikacja dostępna online od: 2025-05-29. — T. Szydło - dod. afiliacja: School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
Autorzy (2)
- Królik Olgierd
- AGHSzydło Tomasz
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 163937 |
|---|---|
| Data dodania do BaDAP | 2025-11-27 |
| Tekst źródłowy | URL |
| DOI | 10.1016/j.future.2025.107914 |
| Rok publikacji | 2026 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Czasopismo/seria | Future Generation Computer Systems |
Abstract
Cloud and edge computing solutions, and especially serverless offerings, are promising areas of technology that can provide additional computing resources to Internet of Things (IoT) devices. This research aims to design and evaluate a novel adaptive computations offloading framework for the IoT domain that leverages serverless Function-as-a-Service (FaaS) solutions capabilities to intelligently select the most suitable execution environment to run the computations in. Pretrained cost estimation models are constructed for each function and each environment (FaaS platform) and they are used by offloading strategies on IoT devices to determine the best execution environment for each invocation. Conducted research demonstrate that pretraining of cost estimation models significantly reduces the time required to calibrate the decision-making offloading algorithm on devices. Evaluation results also prove that it is possible to achieve better function execution times by using offloading algorithms that intelligently select the execution environment for each invocation and can adapt themselves quickly to sudden deterioration of network conditions by monitoring the network state. © 2025
