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Analytical model for task offloading in a fog computing system with batch-size-dependent service
Islamic Azad University, Iran.
National Yunlin University of Science and Technology, Taiwan.
RISE Research Institutes of Sweden, Digitala system, Industriella system.ORCID-id: 0000-0002-4473-7763
Shahed University, Iran.
2022 (engelsk)Inngår i: Computer Communications, ISSN 0140-3664, E-ISSN 1873-703X, Vol. 190, s. 201-215Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Task offloading is one of the main concepts in fog computing which improves the system efficiency and decreases latency. Previously proposed models, such as exponential queue models, addressed the offloading models in a simple model. This study proposes a novel analytical model that examines batch queuing systems and the influence of batch size-dependent service time on system performance. Some of the system's properties are indicated using this model, and the correctness of the suggested model via numerical evaluations and simulations is shown. The evaluation results show that our proposed model provides acceptable accuracy and enables efficient task offloading, applied to fog computing systems. 

sted, utgiver, år, opplag, sider
Elsevier B.V. , 2022. Vol. 190, s. 201-215
Emneord [en]
Analytical approximation model, Batch processing, Fog computing, Task offloading, Analytical models, Batch data processing, Fog, Analytical approximation, Approximation modeling, Batch sizes, Computing system, Exponentials, Queue models, Size dependent, System efficiency
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Identifikatorer
URN: urn:nbn:se:ri:diva-59215DOI: 10.1016/j.comcom.2022.04.010Scopus ID: 2-s2.0-85129703685OAI: oai:DiVA.org:ri-59215DiVA, id: diva2:1667536
Tilgjengelig fra: 2022-06-10 Laget: 2022-06-10 Sist oppdatert: 2025-09-23bibliografisk kontrollert

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