A Fault Tolerant Framework Using Salp Swarm Optimization and Decision Tree for Fog Edge Environment

Madhusudhan, H. S., Gupta, Punit and Vidyarthi, Ankit (2026) A Fault Tolerant Framework Using Salp Swarm Optimization and Decision Tree for Fog Edge Environment. IEEE Communications Standards Magazine. ISSN 24712825 (Submitted)

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Abstract

Fog-Edge computing is an emerging paradigm that has the potential to perform computation and store the data closer to the sources of the data, reduces latency and facilitating real-time processing. This also provides an opportunity to improve the performance at the cloud computing layer by completing small task at the edge layer. This opens a new challenge of distributed task scheduling with resource constraints and computing near to client. Thus, an essential requirement for fog-edge systems is efficient and fault tolerance system with high performance and reliability. This work proposes a hybrid task scheduling algorithm formed using Salp Swarm optimization and a Decision Tree model to improve fault tolerance and enhance the execution time and power consumption. The proposed model ensures the reliability and availability of the services. The work has been compared with existing algorithms and the result shows improvement in average energy efficiency by 76%, improvement in average execution time by 20% and increase in the number of tasks completed by 12% as compared to existing fuzzy login, Genetic algorithm, and PSO(Particle swarm optimization). The proposed model is tested under a scaling environment to study the performance in underloaded, overloaded and average load conditions. The proposed model can further be tested with a neural network-based model for more complex task schedules. The work aims to provide a model that takes the least time to find a solution as compared to existing metaheuristics with high computation time.

Item Type:	Article
Uncontrolled Keywords:	Fault tolerant systems; Fault tolerance; Peer-to-peer computing; Reliability; Internet of Things; Edge computing; Checkpointing; Swarm intelligence; Load modeling; Computational modeling
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Cloud computing Q Science > QA Mathematics > Algebra > Algorithms > Computer algorithms
Divisions:	School of Computing > Staff Research and Publications
Depositing User:	Tamara Malone
Date Deposited:	28 Mar 2026 16:26
Last Modified:	28 Mar 2026 16:26
URI:	https://norma.ncirl.ie/id/eprint/9240

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