Thesis Open Access

LOAD BALANCING ALGORITHM FOR OPTIMAL RESOURCE UTILIZATION IN CLOUDCOMPUTING ENVIRONMENT

BEKEMA GIDISSA DADI


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  <identifier identifierType="DOI">10.20372/nadre/4383</identifier>
  <creators>
    <creator>
      <creatorName>BEKEMA GIDISSA DADI</creatorName>
      <affiliation>ADDIS ABABA SCIENCE AND TECHNOLOGY UNIVERSITY</affiliation>
    </creator>
  </creators>
  <titles>
    <title>LOAD BALANCING ALGORITHM FOR OPTIMAL RESOURCE UTILIZATION IN CLOUDCOMPUTING ENVIRONMENT</title>
  </titles>
  <publisher>National Academic Digital Repository of Ethiopia</publisher>
  <publicationYear>2019</publicationYear>
  <subjects>
    <subject>Cloud computing, Load balancing, Virtual machines, Round-robin, CloudAnalyst, Minimum completion time, Resource utilization and Enhanced weighted round robin</subject>
  </subjects>
  <contributors>
    <contributor contributorType="Supervisor">
      <contributorName>Deepak K. Sinha (PhD)</contributorName>
      <affiliation>ADDIS ABABA SCIENCE AND TECHNOLOGY UNIVERSITY</affiliation>
    </contributor>
  </contributors>
  <dates>
    <date dateType="Issued">2019-11-25</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Text">Thesis</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://nadre.ethernet.edu.et/record/4383</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.20372/nadre/4382</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://nadre.ethernet.edu.et/communities/aastu</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://nadre.ethernet.edu.et/communities/nadre</relatedIdentifier>
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  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Cloud computing involves virtualization, distributed computing, networking, software and&lt;br&gt;
web services. A cloud consists of several elements such as clients, datacenter and&lt;br&gt;
distributed servers. This research issues intending to study the establishment of an effective&lt;br&gt;
and efficient load balancing algorithm. Load balancing is the process of distributing the&lt;br&gt;
load among various nodes of a distributed system to improve both resource utilization and&lt;br&gt;
job response time while avoiding a situation where some of the nodes are heavily loaded&lt;br&gt;
while other nodes are idle or doing very little work. Load balancing is one of the main&lt;br&gt;
challenges in cloud computing which is required to distribute the workload evenly across&lt;br&gt;
all the nodes. Load is a measure of the amount of work that a computation system performs&lt;br&gt;
which can be classified as CPU load, network load, memory capacity and storage capacity.&lt;br&gt;
It helps to achieve a high user satisfaction and resource utilization ratio by ensuring an&lt;br&gt;
efficient and fair allocation of every computing resource in cloud environment.&lt;br&gt;
The objective of the thesis is to propose efficient load balancing algorithm for efficient&lt;br&gt;
utilization of resource in cloud computing environment and to compare the performance of&lt;br&gt;
proposed algorithms with well-known load balancing algorithms. The newly proposed&lt;br&gt;
algorithm consider size of cloudlet, expected completion time of tasks by virtual machine&lt;br&gt;
and runtime properties virtual machines to map&amp;rsquo;s the incoming request to virtual machine&lt;br&gt;
in impartially and efficiently. Proposing a virtual machine load balancing algorithm that&lt;br&gt;
aims to improve the average response time and average processing time of the system in&lt;br&gt;
the cloud environment.&lt;br&gt;
The experiments is carried out using CloudAnalyst simulator to analyze the performance&lt;br&gt;
of proposed algorithm with Round-robin, Throttled and Ant-colony optimization load&lt;br&gt;
balancing algorithms and the result show the proposed algorithm have optimized response&lt;br&gt;
time and datacenter processing time.&lt;br&gt;
&amp;nbsp;&lt;/p&gt;</description>
  </descriptions>
</resource>
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