A Comparative Analysis of Dynamic Scheduling Algorithms for Enhanced Resource Management in Homogeneous and Heterogeneous Fog Computing Environments

Fog computing, an emerging paradigm, extends cloud capabilities to the network's edge, enhancing real-time data processing and analysis. This study focuses on optimizing fog computing systems using an adaptive scheduling algorithm. It efficiently categorizes incoming tasks based on their securi...

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Vydané v:Procedia computer science Ročník 230; s. 542 - 553
Hlavní autori: Sehgal, Nikita, Bansal, Savina, Bansal, RK
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier B.V 2023
Predmet:
fog computing
Internet of things
resource utilization;optimization;security,energy efficiency
scheduling
scheduling
Internet of things
fog computing
resource utilization;optimization;security,energy efficiency
ISSN:1877-0509, 1877-0509
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Shrnutí:Fog computing, an emerging paradigm, extends cloud capabilities to the network's edge, enhancing real-time data processing and analysis. This study focuses on optimizing fog computing systems using an adaptive scheduling algorithm. It efficiently categorizes incoming tasks based on their security requirements into private, semi-private, and public groups, distributing them among Mobile Data Centers (MDCs) and Cloud Data Centers (CDCs). By considering various parameters like job quantities, MDCs, CDCs, their capacities, and communication delays, the algorithm ensures tasks are allocated optimally. The performance of three scheduling algorithms (FCFS, SJF, EDF) is analyzed in both homogeneous and heterogeneous fog environments, shedding light on system efficiency, workload distribution, and resource management. This study provides valuable guidance for the design and operation of efficient fog computing infrastructures tailored to the diverse requirements of IoT applications while optimizing resource utilization.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2023.12.110