A LOAD BALANCING MODEL BASED ON CLOUD

PARTITIONING FOR THE PUBLIC CLOUD

K.Poojitha(10NP1A1219)

J.Pooja Naidu(10NP1A1220)G.Prathyusha (10NP1A1235)V.Lavanya(10NP1A1247)

VISION• 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.

• 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.

• In general ,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.

PROPOSED SYSTEM

• The load balancing model given in this article is aimedat the public cloud which has numerous nodes withdistributed computing resources in many differentgeographic locations.

• Thus, this model divides the public cloud into severalcloud partitions.

• The model has a main controller and balancers togather and analyze the information. Thus, the dynamiccontrol has little influence on the other workingnodes. The system status then provides a basis forchoosing the right load balancing strategy.

MODULES

• The load balance solution is done by the main controller and the

balancers. The main controller first assigns jobs to the suitable

cloud partition and then communicates with the balancers in each

partition to refresh this status information. Since the main

controller deals with information for each partition, smaller data

sets will lead to the higher processing rates. The balancers in each

partition gather the status information from every node and then

choose the right strategy to distribute the jobs. The relationship

between the balancers and the main controller

SYSTEM ARCHITECTURE

When a job arrives at the public cloud, the first step is to choose theright partition. The cloud partition status can be divided into threetypes:(1) Idle: When the percentage of idle nodes exceeds “ALPHA”, changeto idle status.(2) Normal: When the percentage of the normal nodes exceeds“BETA”, change to normal load status.(3) Overload: When the percentage of the overloaded nodes exceeds,”GAMMA” change to overloaded status.The parameters ALPHA,BETA,GAMMA and are set by the cloudpartition balancers.

The main controller has to communicate with the balancers frequentlyto refresh the status information.

FUNCTIONAL REQUIREMENTS

SYSTEM CONFIGURATION

• HARDWARE CONFIGURATION

• Processor - Pentium –IV

• Speed - 1.1 Ghz

• RAM - 256 MB(min)

• Hard Disk - 20 GB

• Key Board - Standard Windows Keyboard

• Mouse - Two or Three Button Mouse

• Monitor - SVGA-Super video graphics array

SYSTEM CONFIGURATION

• SOFTWARE CONFIGURATION

• Operating System : Windows XP,7

• Programming Language : JAVA

• Java Version : JDK 1.6 & above.

• Till now we have discussed on basic concepts of CloudComputing and Load balancing. The research work canbe proceeded to implement the total solution of loadbalancing in a complete cloud environment. Ourobjective for this paper is to develop an effectiveload balancing algorithm using Round Robin techniqueto maximize or minimize different performanceparameters like CPU load, Memory capacity, Delay ornetwork load for the clouds of different sizes.

CONCLUSION

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.