Journal article Open Access

An Energy Efficient Hybrid PSO Algorithm in Cloud Environment

Ranjandeep Kaur Khera; V. K. Banga

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<identifier identifierType="URL">https://zenodo.org/record/5595544</identifier>
<creators>
<creator>
<creatorName>Ranjandeep Kaur Khera</creatorName>
<affiliation>Assistant Professor, Department of  Computer Science, Khalsa College for Women, Amritsar, Punjab, India</affiliation>
</creator>
<creator>
<creatorName>V. K. Banga</creatorName>
<affiliation>Principal and Professor, Department of  Electronics &amp; Communication Engineering, Amritsar College of  Engineering and Technology, Amritsar, Punjab, India.</affiliation>
</creator>
</creators>
<titles>
<title>An Energy Efficient Hybrid PSO Algorithm in  Cloud Environment</title>
</titles>
<publisher>Zenodo</publisher>
<publicationYear>2020</publicationYear>
<subjects>
<subject>Cloud Computing, Particle Swarm optimization, Invasive Weed optimization.</subject>
<subject subjectScheme="issn">2249-8958</subject>
</subjects>
<contributors>
<contributorName>Blue Eyes Intelligence Engineering  &amp; Sciences Publication (BEIESP)</contributorName>
<affiliation>Publisher</affiliation>
</contributor>
</contributors>
<dates>
<date dateType="Issued">2020-02-29</date>
</dates>
<language>en</language>
<resourceType resourceTypeGeneral="JournalArticle"/>
<alternateIdentifiers>
<alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/5595544</alternateIdentifier>
</alternateIdentifiers>
<relatedIdentifiers>
<relatedIdentifier relatedIdentifierType="ISSN" relationType="IsCitedBy" resourceTypeGeneral="JournalArticle">2249-8958</relatedIdentifier>
<relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.35940/ijeat.C4704.029320</relatedIdentifier>
</relatedIdentifiers>
<rightsList>
<rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
</rightsList>
<descriptions>
<description descriptionType="Abstract">&lt;p&gt;Algorithms exist to schedule various tasks in real time cloud environment. Nowadays many researchers are trying to schedule heavily loaded situations in real time cloud environment using swarming technique. For such studies many parameters need to be considered like cost of the system, processor latency, number of tasks and so on. With the increase in the number of tasks in the set, processing time also increases. In this situation, processor latency is at peak as the number of tasks increases and system costs increase. So the above mentioned problem is handled by proposing a task scheduler that uses a PSO algorithm to remove the limitations of past studies in a heavily loaded situation. The Particle Swarm optimization (PSO) and Invasive Weed Optimization (IWO) are combined to propose a new technique called the HWO algorithm. The proposed algorithm is recommended for preventive tasks in the single-processor in real-time environment systems.&lt;/p&gt;</description>
</descriptions>
</resource>

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