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            <name>Title</name>
            <description>A name given to the resource</description>
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                <text>Faculty Publications</text>
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    <name>Conference Paper</name>
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          <name>Creator</name>
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              <text>Sripavithra, C.K.; Kirubanand, V.B.; Dhushyanth, S.P.; Bavana, P.T.</text>
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          <name>Title</name>
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              <text>Dynamic Scheduling of Scientific Workflows with Budget-Constraints in the Cloud</text>
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              <text>01-01-2025</text>
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              <text>Smart Innovation, Systems and Technologies;Volume;435 SIST;pp.575-588</text>
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              <text>&lt;a href="https://doi.org/10.1007/978-981-96-2182-8_43" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-981-96-2182-8_43&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105011347659?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105011347659?origin=resultslist&lt;/a&gt;</text>
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              <text>Sripavithra C.K., Maharanis Science College for Women, Mysore, India, Christ (Deemed to be University), Bangalore, India; Kirubanand V.B., Christ (Deemed to be University), Bangalore, India; Dhushyanth S.P., School of Electronics and Communication Engineering, Vellore Institute of Technology, Vellore, India; Bavana P.T., Nokia Networks, Bangalore, India</text>
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              <text>This research presents a novel approach to dynamic scheduling in cloud computing environments, directing on budget-constrained workflows and towards optimizing makespan, Quality of Service (QoS) metrics, and energy efficiency. Exploiting the Task Duplication Scheduling Algorithm (TDSA) and Salp Swarm Algorithm (SSA) which is influenced by the motion patterns of marine life forms, the proposed Enhanced Salp Swarm Algorithm (ESSA) algorithm dynamically assigns tasks to cloud resources while bearing budget curbs. The algorithm seeks to reduce makespan, guaranteeing efficient completion of workflows, at the same time boosting the QoS metric resource utilization. Moreover, the incorporation of energy-efficient scheduling techniques further donates to the sustainability of cloud environment operations. By constructing a mathematical representation which captures the trade-off between makespan, resource utilization, and budget constraints, the mechanism productively balances competing objectives to reach optimal scheduling outcomes. Through substantial experimentation with 5 Scientific Workflows, the success and efficiency of the suggested methodology are assessed, exhibiting its potential to significantly improve the performance of budget-restricted workflow in cloud environments while boosting workflows makespan (up to 9%) and improving asset usage (up to 5%) and energy efficiency (up to 10.5%). This research presents to advancing the latest in dynamic scheduling techniques for cloud environment, benefitting practical solutions for real-world deployment and operation.  The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.</text>
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              <text>Budget constraint; Energy; Makespan; Optimization; QoS; Scientific workflows</text>
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              <text>Springer Science and Business Media Deutschland GmbH</text>
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              <text>ISSN: 21903018; ISBN: 978-981962181-1;</text>
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              <text>Restricted Access; Hardcopy may be available in the library</text>
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