Performance Optimization of Task Scheduling in Fog and Edge Computing using meta-heuristic algorithms for IoT Networks: A Comparative Study

Baxla, Pratyush Nigel (2023) Performance Optimization of Task Scheduling in Fog and Edge Computing using meta-heuristic algorithms for IoT Networks: A Comparative Study. Masters thesis, Dublin, National College of Ireland.

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Abstract

In the dynamic landscape of edge computing, efficient task scheduling plays a pivotal role in optimizing resource utilization and enhancing system performance. In order to better understand how meta-heuristic algorithms can handle the complexities of this situation, this study delves into the area of cloud-edge task scheduling. Focusing on a simulated environment with varying edge device counts (50, 100, and 200), our research investigates the performance of diverse algorithms in terms of tasks executed, energy consumption, and waiting time. The results highlight the complex interplay between orchestration strategies and execution location and reveal refined patterns in task distribution between edge and cloud resources. Notably, the Hybrid Grey Wolf- Whale Optimization Algorithm consistently stands out in tasks executed, balancing edge and cloud utilization efficiently. However, each algorithm showcases unique strengths and weaknesses, driving insightful discussions around energy efficiency and waiting time trade-offs. This study highlights the need for customized orchestration strategies in edge computing while also providing valuable insights for practitioners and researchers alike through a thorough analysis of the results. Future research might concentrate on adjusting algorithmic parameters and investigating hybrid strategies to further optimize task scheduling in this changing environment.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Gupta, Punit UNSPECIFIED
Subjects:	T Technology > T Technology (General) > Information Technology > Cloud computing Q Science > QA Mathematics > Algebra > Algorithms > Computer algorithms T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunications > Computer networks > Internet of things
Divisions:	School of Computing > Master of Science in Cloud Computing
Depositing User:	Tamara Malone
Date Deposited:	10 Aug 2024 13:18
Last Modified:	10 Aug 2024 13:18
URI:	https://norma.ncirl.ie/id/eprint/7043

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