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Fogfaas: providing serverless computing simulation for iFogSim and edge cloud

delete2025-03-28
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PRE
AI
M
Mohammad Mahdi Ghaseminya
S
Seyed Abolfazl Shahzadeh Fazeli *
J
Jamshid Abouei
A
Abbasi, Elham
DOI:10.1007/s11227-025-07173-2delete
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Abstract

Abstract

En 中文
Serverless computing, or function as a service (FaaS), has transformed application development by abstracting server management and enabling event-driven execution of stateless functions. In the internet of things (IoT) context, FaaS is particularly useful due to the dynamic and resource-constrained nature of IoT devices. FaaS allows IoT applications to scale efficiently without needing to manage physical servers, which is crucial for IoT environments with fluctuating workloads and real-time data processing needs. In this paper, we address these issues and introduce FoGFaaS, an extension of the iFogSim simulator that incorporates the ability to simulate FaaS in fog computing environments. FoGFaaS leverages the robust modeling capabilities of iFogSim, but with extensive modifications (nearly 70%) to its core classes, providing a dedicated architecture for evaluating serverless platforms. These modifications maintain the core functionality of iFogSim, allowing users to perform fog and edge computing simulations using FoGFaaS in both traditional and serverless computing paradigms. This novel simulation tool enables researchers to analyze task scheduling, resource allocation, and performance metrics, advancing the study of FaaS in IoT and edge scenarios.
Keywords:
Serverless computing
Function as a services (FaaS)
iFogSim
Modeling and simulation

Journal

Journal of Supercomputing cover
Journal of Supercomputing
IF:
2.7
Papers:
1.2K
Citations:
1.0W

Organization

Y
yazd univ
Scholars:
97
Papers: 51
Citations: 12
Cited Papers

Cited Papers

Estimating the Energy Consumption of Applications in the Computing Continuum with iFogSim
err2023-08-25
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PREAI
errSaeedeh Baneshi; Ana-Lucia Varbanescu; Anuj Pathania; Benny Akesson; Andy Pimentel
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Correlation adaptive task scheduling
err2023-06-24
err3
PREAI
errMoustakas, Thanasis; Kolomvatsos, Kostas
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Data and resource aware incremental ML training in support of pervasive applications
err2024-08-16
err2
PREAI
errMoustakas, Thanasis; Tziouvaras, Athanasios; Kolomvatsos, Kostas
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Drift-based task management in support of pervasive edge applications
err2024-10-01
err0
PREAI
errMoustakas, Thanasis; Kolomvatsos, Kostas
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Auto-scaling mechanisms in serverless computing: A comprehensive review
err2024-08-01
err8
PREAI
errTari, Mohammad; Ghobaei-Arani, Mostafa; Pouramini, Jafar; Ghorbian, Mohsen
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Survey on serverless computing
err2021-07-12
err12
errOAAI
errHassan, Hassan B.; Barakat, Saman A.; Sarhan, Qusay I.
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faas‐sim: A trace‐driven simulation framework for serverless edge computing platforms
err2023-10-18
err0
errOAAI
errPhilipp Raith; Thomas Rausch; Alireza Furutanpey; Schahram Dustdar
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