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    A comparative experiment in distributed load balancing

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    Type
    Conference Paper
    Authors
    Randles, Martin
    Odat, Enas M. cc
    Lamb, David J.
    Osama, Abu Rahmeh
    Taleb-Bendiab, Azzelarabe
    KAUST Department
    Computer Science Program
    Date
    2009-12
    Permanent link to this record
    http://hdl.handle.net/10754/564244
    
    Metadata
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    Abstract
    The anticipated uptake of Cloud computing, built on the well-established research fields of web services, networks, utility computing, distributed computing and virtualisation, will bring many advantages in cost, flexibility and availability for service users. These benefits are expected to further drive the demand for cloud services, increasing both the cloud customer base and the scale of cloud installations. This has implications for many technical issues in such Service Oriented Architectures and Internet of Services (IoS) type applications; fault tolerance, high availability and scalability for examples. Central to these issues is the establishment of effective load balancing techniques. It is clear that the scale and complexity of these systems makes centralized individual assignment of jobs to specific servers infeasible; leading to the need for an effective distributed solution. This paper investigates three possible distributed solutions, which have been proposed for load balancing: An approach inspired by the foraging behaviour of the Honeybee, Biased Random Sampling and Active Clustering. © 2009 IEEE.
    Citation
    Randles, M., Odat, E., Lamb, D., Abu-Rahmeh, O., & Taleb-Bendiab, A. (2009). A Comparative Experiment in Distributed Load Balancing. 2009 Second International Conference on Developments in eSystems Engineering. doi:10.1109/dese.2009.20
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    2009 Second International Conference on Developments in eSystems Engineering
    Conference/Event name
    International Conference on Developments in eSystems Engineering, DeSE 2009
    ISBN
    9780769539126
    DOI
    10.1109/DeSE.2009.20
    ae974a485f413a2113503eed53cd6c53
    10.1109/DeSE.2009.20
    Scopus Count
    Collections
    Conference Papers; Computer Science Program

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