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Fault-Tolerant Trust-Based Task Scheduling Algorithm Using Harris Hawks Optimization in Cloud Computing.

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  • 1School of Computer Science and Engineering, VIT-AP University, Amaravati 522237, India.

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Summary
This summary is machine-generated.

This study introduces a fault-tolerant, trust-based task scheduling algorithm (FTTATS) for cloud computing. FTTATS enhances reliability and efficiency by minimizing task failures and makespan, improving service availability and success rates.

Keywords:
Harris hawks optimizationSLA-based trust parametersavailabilityrate of failuressuccess rate

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Area of Science:

  • Cloud Computing
  • Distributed Systems
  • Artificial Intelligence

Background:

  • Cloud computing services require high availability and fault tolerance.
  • Single-point failures remain a challenge in cloud environments.
  • Effective task scheduling is crucial for reliability and user trust.

Purpose of the Study:

  • To propose a fault-tolerant, trust-based task scheduling algorithm (FTTATS) for cloud computing.
  • To enhance the reliability and efficiency of cloud services.
  • To improve user trust through better service level agreement (SLA) parameter fulfillment.

Main Methods:

  • Developed a fault-tolerant trust-based task scheduling algorithm (FTTATS).
  • Utilized Harris Hawks Optimization for scheduler design.
  • Employed CloudSim for simulation using synthetic and real-world data.

Main Results:

  • FTTATS significantly minimized makespan compared to ACO, PSO, and GA.
  • Achieved substantial reductions in failure rates (up to 65.4%).
  • Improved key SLA parameters including availability (up to 35.71%) and success rates (up to 52.69%).

Conclusions:

  • The proposed FTTATS algorithm offers superior performance in fault tolerance and task scheduling.
  • FTTATS enhances cloud service reliability, efficiency, and user trust.
  • The algorithm demonstrates significant improvements over existing state-of-the-art methods.