Cloud computing is usually a novel trend emerging
in IT environment together with huge requirements of
infrastructure as well as resources. Load Balancing is a crucial
part of cloud computing environment. The technique of load
balancing is essential in cloud computing to further improve the
efficiency from the cloud. Efficient load balancing strategy
ensures efficient resource utilization by simply provisioning of
resources to be able to cloud user’s on-demand basis in pay-asyou-
say-manner. Load Balancing could even assistance
prioritizing users by making use of appropriate scheduling
criteria. Good load balancing can make cloud computing
extremely effective and improves user satisfaction. This
particular paper gives a technique for balance the actual
incoming load in cloud environment by looking into making
partitions from the public cloud.
Published In : IJCAT Journal Volume 1, Issue 11
Date of Publication : 31 December 2014
Pages : 593 - 598
Figures :03
Tables : 01
Publication Link :A Novel Approach for Efficient Load Balancing in
Cloud Computing Environment by Using
Partitioning
P. Vijay Kumar : Completed my B.Tech in Shree
institute of technical education, Pursuing M.Tech
in Chadalawada Ramanamma Engineering
college. His areas of interests include Image
Processing, software Engineering, Object
Oriented systems and Data Mining & Image
Mining.
Prof. R.Suresh : received B.E.degree from
SVNIT(REC) in 1996 and M.Tech., degree from
JNTU Hyderabad in 2001 and pursuing the
Ph.D degree from JNTUA, Anantapuramu.
From 1998 to Till date he is with the JNTUA,
Anantapur working at different levels. His areas
of interests includes Image Processing, software
ingineering , Object Oriented systems and Data
Mining & Image Mining. His Current interests
include Texture model approach to
Mammograms’ classification and Detection.
Outsourcing data storage
Dynamic
environment
Mutual trust
CSP
Cheating detection module
Access control
TTP
Load Balancing is a vital task within Cloud Computing
environment to attain maximum usage of resources.
Various works continues to be completed in these studies
area to improve the performance as well as efficiency
from the cloud system. Our proposed system provides a
simple approach associated with load balancing within
the cloud while using the thought of cloud partitioning.
However, more work has to be carried out this area. In the
future study, some other load balancing algorithms can be
located out, simply because other algorithms can provide
much better load balancing results. Numerous load
balancing algorithms should be compared. Extremely
effective algorithms needs to be designed in order that the
distribution from the load on the list of nodes within the
cloud partition will probably be simpler and minimize
enough time complexity. Cloud division just isn't an easy
task. Several things have to be thought to be while
making cloud partition, including the nodes in the cluster
could possibly be still apart.
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