October 8, 2024 Thesis Open Access

Fetudin Hussen

DCAT Export

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        <foaf:name>Fetudin Hussen</foaf:name>
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    <dct:title>Department of Information Technology Disaster Recovery and Fault Tolerance Techniques to Increase Resilience and Reduce Hazards in Cloud Computing</dct:title>
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    <dcat:keyword>Cloud Computing, Disaster Recovery, Fault Tolerance, Triple Modular Redundancy, Check pointing, Resilience, Hazards.</dcat:keyword>
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        <foaf:name>Chandra Srinivas (PhD)</foaf:name>
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    <dct:description>&lt;p&gt;Abstract&lt;/p&gt; &lt;p&gt;This study looks into fault tolerance and disaster recovery strategies to increase cloud computing environments&amp;#39; resilience and reduce risks. The main goal is to investigate the efficacy of rollback strategies for recovery mechanisms and Triple Modular Redundancy (TMR) strategies for fault tolerance and checkpoints. The Monte Carlo simulations to model a system&amp;lsquo;s and google colab environment was used to run simulations in order to examine system performance in a variety of failure scenarios. The results of simulations carried out at low, moderate, and high fault rates show fault scenarios related to system availability and realability, error detection and correction, and recovery time. It also examines resource utilization cost implications of the CPU, memory, and storage to give a realistic realization of their financial impact on cloud service providers. It further presents scalability solutions in a distributed and multi-cloud environments. Future work will be focused on applies adaptive fault tolerance techniques to provide possible solutions for storage and scalability issues.&lt;/p&gt;</dct:description>
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