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dc.contributor.authorVeerisetty, Neeharika
dc.date.accessioned2014-02-04T01:46:12Z
dc.date.available2014-02-04T01:46:12Z
dc.date.issued2013en_NZ
dc.identifier.urihttps://hdl.handle.net/10652/2364
dc.description.abstractWith the incidence of technology at each and every juncture of human life, there has been an accelerated growth in computational needs to satisfy the technological cravings. Computer networks have evolutionarily emerged and have evolved as life blood of today’s global communication challenges. To fulfil the dynamic needs of present day networks, distributed and parallel computing applications are gaining momentum rapidly. Distributed networks have apparently become a better choice favouring the processing of large scale intensive applications which was previously unimaginable. However, it is evident that the load on a network is always relative to the volume of the application being processed. Eventually if the load on the network is not fairly distributed among all the available processing elements, it might result in improper resource usage and degraded network performance. Efficient load balancing approaches are essential to achieve proportional distribution of load among the network nodes to preserve the overall system integrity. Therefore, the process of identifying an efficient method to achieve proportional distribution of load is of paramount importance. To achieve an affective balance in load, this thesis investigates into an already existing Ant Colony based prototype called Messor and establishes a new approach based on dynamic load table concept augmented with ant search using Artificial Neural Networks. The proposed approach is simulated on a software based model network and the results are presented. The performance of the approach is evaluated based on certain performance criteria.en_NZ
dc.language.isoenen_NZ
dc.subjectdistributed systemen_NZ
dc.subjectload balancingen_NZ
dc.subjectworkloaden_NZ
dc.subjectMessoren_NZ
dc.subjectresource utilizationen_NZ
dc.subjectjob response timeen_NZ
dc.subjectant colony optimizationen_NZ
dc.subjectmulti agenten_NZ
dc.subjectmeta-heuristicen_NZ
dc.subjectdynamic load tableen_NZ
dc.subjectArtificial Neural Network (ANN)en_NZ
dc.subjectdecision makingen_NZ
dc.subjectMessoren_NZ
dc.titleLoad balancing in a distributed network environment : an ant colony inspired approachen_NZ
dc.typeMasters Thesisen_NZ
thesis.degree.nameMaster of Computingen_NZ
thesis.degree.levelMastersen_NZ
thesis.degree.grantorUnitec Institute of Technologyen_NZ
dc.subject.marsden080501 Distributed and Grid Systemsen_NZ
dc.identifier.bibliographicCitationVeerisetty, N. (2013). Load balancing in a distributed network environment: An ant colony inspired approach (Unpublished document submitted in partial fulfilment of the requirements for the degree of Master of Computing). Unitec Institute of Technology, Auckland, New Zealand. Retrieved from https://hdl.handle.net/10652/2364
unitec.pages77en_NZ
dc.contributor.affiliationUnitec Institute of Technologyen_NZ
unitec.advisor.principalJayawardena, Chandimal
unitec.advisor.associatedPang, Paul
unitec.institution.studyareaComputing


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