Dynamic Fault Tolerance Aware Scheduling for Healthcare System on Fog Computing

Rajab, Hadeel T.; Younis, Manal F.

doi:10.24996/ijs.2021.62.1.29

Cited by 10 publications

(2 citation statements)

References 27 publications

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“…Rajab et al [39] introduced a Dynamic Weighted Round Robin (DWRR) approach for scheduling and distributing fog server data based on CPU and memory factors to maximize system performance. Even with high user loads, the approach offers a high throughput.…”

Section: Background and Relevant Workmentioning

confidence: 99%

A hybrid approach for fault-tolerance aware load balancing in fog computing

Kashyap,

Ahuja,

Kumar

2024

Cluster Comput

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Fog computing has grown in popularity in recent years because to its potential to deliver real-time processing, low latency, and reduce network congestion. However, the implementation of Internet of Things (IoT) enabled smart devices in environments using fog computing may lead to resource limitations and higher computational demands. Load balancing and fault tolerance strategies are necessary to tackle these difficulties for optimal resource usage and system availability. In order to accomplish fault tolerance aware load balancing in fog computing, a hybrid meta-heuristic approach in this study that combines the Modified Harris-Hawks Optimization (MHHO) and Ant Colony Optimization (ACO) is proposed. The MHHO algorithm is utilized for load balancing, whereas the ACO algorithm is used for fault tolerance. By employing the proposed technique, the load on fog nodes is balanced, the makespan time is minimized, energy consumption and execution costs are minimized, and fault tolerance in fog computing environments is ensured. It is evaluated using a simulation framework built on the iFogSim toolkit. In terms of load balancing, fault tolerance, and other factors, the results of the experiments show that the suggested hybrid algorithm performs better than earlier state-of-the-art methods.

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Section: Background and Relevant Workmentioning

confidence: 99%

A hybrid approach for fault-tolerance aware load balancing in fog computing

Kashyap,

Ahuja,

Kumar

2024

Cluster Comput

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“…Total number of completed tasks Total execution time (7) Latency: Latency is the time delay between the initiation of a task and the receipt of the corresponding response or completion notification [33][34][35][36]. It is an important metric for real-time applications and communication systems.…”

Section: Throughput =mentioning

confidence: 99%

Optimization of Maritime Communication Workflow Execution with a Task-Oriented Scheduling Framework in Cloud Computing

Ahmad,

Acarer,

Kim

2023

JMSE

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To ensure safe, effective, and efficient marine operations, the optimization of maritime communication workflows with a task-oriented scheduling framework is of the utmost importance. Navigation, vessel traffic management, emergency response, and cargo operations are all made possible by maritime communication, which necessitates seamless information sharing between ships, ports, coast guards, and regulatory bodies. However, traditional communication methods face challenges in adapting to the dynamic and distributed nature of maritime activities. This study suggests a novel approach for overcoming these difficulties that combines task-oriented scheduling and resource-aware cloud environments to enhance marine communication operations. Utilizing cloud computing offers a scalable, adaptable infrastructure that can manage various computational and communication needs. Even during busy times, effective data processing, improved decision making, and improved communication are made possible by utilizing the cloud. The intelligent allocation and prioritization of communication activities using a task-oriented scheduling framework ensures that urgent messages receive prompt attention while maximizing resource utilization. The proposed approach attempts to improve marine communication workflows’ task prioritization, scalability, and resource optimization. In order to show the effectiveness of the proposed approach, simulations were performed in CloudSim. The performance evaluation parameters, i.e., throughput, latency, execution cost, and energy consumption, have been evaluated. Simulation results reflect the efficacy and practical usability of the framework in various maritime communication configurations. By making marine communication methods more durable, dependable, and adaptable to the changing needs of the maritime industry, this study advances maritime communication techniques. The findings of this research have the potential to revolutionize maritime communication, leading to safer, more efficient, and more resilient maritime operations on a large scale.

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Load balancing techniques for fog computing environment: Comparison, taxonomy, open issues, and challenges

Kashyap

Kumar

2022

Concurrency and Computation

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SUMMARY Load balancing (LB) is nothing but the systematic distribution of load over different servers. The fog server is handling the maximum data of the cloud server to enhance the advancement of users' requests. The growth in data requests is escalating, and fog computing has intensified the accessibility of the data. Fog computing achieves many challenges according to the demands of the users, but even so, some challenges require more progress. The problem faced by fog computing is LB due to an increase in traffic on the network layer. Various LB techniques have already been proposed in the cloud layer, but until now they have only been in progress in the fog layer. Inefficient LB may cause a decrease in service quality, like delays in response time, processing time, security, and many more. In this survey, several algorithms have been discussed that are based on LB, which works out the issue of overloaded data on the network. Some parameters that authors have focused in LB are latency, bandwidth, deadlines, cost, security, execution time, and response time. Other parameters based on fault tolerance are also discussed with their quality parameter table and algorithm. In addition to this some of the limitations of the author's work, that is discussed in this article.

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Dynamic Fault Tolerance Aware Scheduling for Healthcare System on Fog Computing

Cited by 10 publications

References 27 publications

A hybrid approach for fault-tolerance aware load balancing in fog computing

A hybrid approach for fault-tolerance aware load balancing in fog computing

Optimization of Maritime Communication Workflow Execution with a Task-Oriented Scheduling Framework in Cloud Computing

Load balancing techniques for fog computing environment: Comparison, taxonomy, open issues, and challenges

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