TY - GEN
T1 - A comparative experiment in distributed load balancing
AU - Randles, Martin
AU - Odat, Enas M.
AU - Lamb, David J.
AU - Osama, Abu Rahmeh
AU - Taleb-Bendiab, Azzelarabe
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2009/12
Y1 - 2009/12
N2 - 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.
AB - 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.
UR - http://hdl.handle.net/10754/564244
UR - http://ieeexplore.ieee.org/document/5395118/
UR - http://www.scopus.com/inward/record.url?scp=77949598855&partnerID=8YFLogxK
U2 - 10.1109/DeSE.2009.20
DO - 10.1109/DeSE.2009.20
M3 - Conference contribution
SN - 9780769539126
SP - 258
EP - 265
BT - 2009 Second International Conference on Developments in eSystems Engineering
PB - Institute of Electrical and Electronics Engineers (IEEE)
ER -