Scheduling Algorithms for Hierarchical Fog Networks
Amanjot Kaur, Nitin Auluck

TL;DR
This paper introduces two hierarchical fog scheduling algorithms, FiFSA and EFSA, which optimize job placement across fog device tiers to improve completion time and cost efficiency in fog computing systems.
Contribution
The paper proposes two novel fog scheduling algorithms, FiFSA and EFSA, tailored for hierarchical fog networks with diverse device tiers and job requirements.
Findings
FiFSA improves total completion time by up to 57.9%.
EFSA achieves up to 70% reduction in total completion time.
Both algorithms outperform LTF and cloud-only scheduling methods.
Abstract
Fog computing brings the functionality of the cloud near the edge of the network with the help of fog devices/micro data centers (). Job scheduling in such systems is a complex problem due to the hierarchical and geo-distributed nature of fog devices. We propose two fog scheduling algorithms, named (Hierarchical rst og cheduling lgorithm) and ( Hierarchical lected og cheduling lgorithm). We consider a hierarchical model of fog devices, where the computation power of fog devices present in higher tiers is greater than those present in lower tiers. However, the higher tier fog devices are located at greater physical distance from data generation sources as compared to lower tier fog devices. Jobs with varying granularity and cpu requirements have been considered. In general, jobs with modest cpu requirements are scheduled on lower tier fog…
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