A
Load Balancing Model Based on Cloud Partitioning for the Public Cloud
ABSTRACT:
Load balancing in the cloud computing
environment has an important impact on the performance. Good load balancing
makes cloud computing more efficient and improves user satisfaction. This
article introduces a better load balance model for the public cloud based on
the cloud partitioning concept with a switch mechanism to choose different
strategies for different situations. The algorithm applies the game theory to
the load balancing strategy to improve the efficiency in the public cloud
environment.
EXISTING SYSTEM:
Since the job arrival pattern is not predictable and
the capacities of each node in the cloud differ, for load balancing problem,
workload control is crucial to improve system performance and maintain stability.
Load balancing schemes depending on whether the system dynamics are important
can be either static and dynamic. Static schemes do not use the system
information and are less complex while dynamic schemes will bring additional
costs for the system but can change as the system status changes. A dynamic
scheme is used here for its flexibility.
DISADVANTAGES
OF EXISTING SYSTEM:
·
Cloud computing environment is a very
complex problem with load balancing receiving.
·
The job arrival pattern is not
predictable and the capacities of each node in the cloud differ, for load
balancing problem, workload control is crucial to improve system performance
and maintain stability.
PROPOSED SYSTEM:
The load balancing model given in this article is
aimed at the public cloud which has numerous nodes with distributed computing
resources in many different geographic locations. Thus, this model divides the
public cloud into several cloud partitions. When the environment is very large
and complex, these divisions simplify the load balancing. The cloud has a main
controller that chooses the suitable partitions for arriving jobs while the
balancer for each cloud partition chooses the best load balancing strategy.
Load balancing schemes depending on whether the
system dynamics are important can be either static or dynamic. Static schemes
do not use the system information and are less complex while dynamic schemes
will bring additional costs for the system but can change as the system status
changes. A dynamic scheme is used here for its flexibility. The model has a
main controller and balancers to gather and analyze the information. Thus, the
dynamic control has little influence on the other working nodes. The system status
then provides a basis for choosing the right load balancing strategy.
ADVANTAGES
OF PROPOSED SYSTEM:
·
This model divides the public cloud into
several cloud partitions. When the environment is very large and complex, these
divisions simplify the load balancing.
·
The role that loads balancing plays in
improving the performance and maintaining stability.
SYSTEM ARCHITECTURE:
PROJECT FLOW:
SYSTEM CONFIGURATION:-
HARDWARE CONFIGURATION:-
ü Processor - Pentium –IV
ü Speed - 1.1
Ghz
ü RAM - 256
MB(min)
ü Hard
Disk - 20
GB
ü Key
Board - Standard
Windows Keyboard
ü Mouse - Two
or Three Button Mouse
ü Monitor - SVGA
SOFTWARE CONFIGURATION:-
ü Operating System : Windows XP
ü Programming Language : JAVA
ü Java Version : JDK 1.6 & above.
REFERENCE:
Gaochao Xu, Junjie Pang, and Xiaodong Fu “A Load
Balancing Model Based on Cloud Partitioning for the Public Cloud” TSINGHUA SCIENCE AND TECHNOLOGY ISSN
1007 - 0214 04 /12 pp 34-39 Volume 18, Number 1, February 2013.
