Thesis Open Access
BEKEMA GIDISSA DADI
<?xml version='1.0' encoding='utf-8'?> <resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd"> <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> </relatedIdentifiers> <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"><p>Cloud computing involves virtualization, distributed computing, networking, software and<br> web services. A cloud consists of several elements such as clients, datacenter and<br> distributed servers. This research issues intending to study the establishment of an effective<br> and efficient load balancing algorithm. Load balancing is the process of distributing the<br> load among various nodes of a distributed system to improve both resource utilization and<br> job response time while avoiding a situation where some of the nodes are heavily loaded<br> while other nodes are idle or doing very little work. Load balancing is one of the main<br> challenges in cloud computing which is required to distribute the workload evenly across<br> all the nodes. Load is a measure of the amount of work that a computation system performs<br> which can be classified as CPU load, network load, memory capacity and storage capacity.<br> It helps to achieve a high user satisfaction and resource utilization ratio by ensuring an<br> efficient and fair allocation of every computing resource in cloud environment.<br> The objective of the thesis is to propose efficient load balancing algorithm for efficient<br> utilization of resource in cloud computing environment and to compare the performance of<br> proposed algorithms with well-known load balancing algorithms. The newly proposed<br> algorithm consider size of cloudlet, expected completion time of tasks by virtual machine<br> and runtime properties virtual machines to map&rsquo;s the incoming request to virtual machine<br> in impartially and efficiently. Proposing a virtual machine load balancing algorithm that<br> aims to improve the average response time and average processing time of the system in<br> the cloud environment.<br> The experiments is carried out using CloudAnalyst simulator to analyze the performance<br> of proposed algorithm with Round-robin, Throttled and Ant-colony optimization load<br> balancing algorithms and the result show the proposed algorithm have optimized response<br> time and datacenter processing time.<br> &nbsp;</p></description> </descriptions> </resource>
All versions | This version | |
---|---|---|
Views | 54 | 54 |
Downloads | 23 | 23 |
Data volume | 41.7 MB | 41.7 MB |
Unique views | 28 | 28 |
Unique downloads | 17 | 17 |