Resource Scheduling Techniques for Optimal Quality of Service in Fog Computing Environment: A Review

Goel, Gaurav; Tiwari, Rajeev

doi:10.1007/s11277-023-10421-4

Cited by 3 publications

(1 citation statement)

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“…Modules and devices will be placed in priority order by the algorithm. In order to reduce network traffic, the devices are arranged in the order nearest to the source of data (sensor) [42].…”

Section: Related Workmentioning

confidence: 99%

Security-Aware Resource Allocation in Fog Computing Environments

Kumar

2024

Preprint

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Fog computing, an innovative approach building upon cloud technology, taps into local user resources to enhance services. It boasts cost-effectiveness, improved security, and reduced network delays, making it a popular choice for real-time applications. However, due to the heterogeneity of fog devices, resource allocation and scheduling pose challenges. This paper introduces a novel solution using a crow-inspired search mechanism and a multi-objective evolutionary approach for fog computing environments. The primary objectives are to optimize security and success rates simultaneously. A local search method enhances the performance of the crow search algorithm (CSA). The proposed method utilizes evolutionary techniques to allocate and schedule resources effectively. We compared our hybrid CSA with the original CSA and Genetic Algorithm (GA) across seven scenarios with varying parameters. Our hybrid CSA consistently outperformed existing methods, demonstrating its effectiveness in achieving the desired objectives.

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Section: Related Workmentioning

confidence: 99%