4. WHAT IS CLOUD COMPUTING?
Cloud:
Cloud refers to a Network or Internet. Cloud can provide services over
network.
Cloud Computing:
Cloud computing means "a type of Internet-based computing," where
different services — such as servers, storage and applications — are
delivered to an clients computers or devices through the Internet.
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6. SERVICE MODELS:
INFRASTRUCTURE AS A SERVICE (IAAS):
IaaS provides access to fundamental resources such as physical
machines, virtual machines, virtual storage, etc.
PLATFORM AS A SERVICE (PAAS):
PaaS provides the runtime environment for applications, development &
deployment tools, etc.
SOFTWARE AS A SERVICE (SAAS):
SaaS model allows to use software applications as a service to end users.
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7. DEPLOYMENT MODELS:
Public Cloud:
The Public Cloud allows systems and services to be easily accessible to the general public. Public
cloud may be less secure because of its openness, e.g., e-mail.
Private Cloud:
The Private Cloud allows systems and services to be accessible within an organization. It offers
increased security because of its private nature.
Community Cloud:
The Community Cloud allows systems and services to be accessible by group of organizations.
Hybrid Cloud:
The Hybrid Cloud is mixture of public and private cloud. However, the critical activities are
performed using private cloud while the non-critical activities are performed using public cloud.
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8. ADVANTAGES:
• Cost Efficient: All the maintenance works are done by cloud service
provider.Additional costs are minimised
• Mobility: Cloud mobility enables users to access anywhere with a
internet connection.
• Backup and Disaster Recovery: Most cloud providers offer backup and
recovery capabilities.
• Storage and Scalability: With the cloud,we have access to unlimited
storage and scalability.
9. DISADVANTAGES:
• Security and Privacy: Security is a major concern in clouds.Managing
confidential data may require deploying a private cloud.
• Compatibility: Softwares developed in one cloud may not be compatible
in other clouds.
11. LOAD BALANCING:
• Load Balancing is a process of reassigning the total load to the
individual nodes of the collective system.
• It makes resource utilization effective and to improve the
response time of the job.
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• A large public cloud includes many nodes and the nodes
in different geographical locations.
• Cloud partitioning is used to manage this large cloud. A
cloud partition is a subarea of the public cloud with
divisions based on the geographic locations.
• The load balancing strategy is based on the cloud
partitioning concept.
SYSTEM MODEL:
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MAIN CONTROLLER AND BALANCER:
After creating the cloud partitions, the load balancing then starts:
• when a job arrives at the system, the main controller decides which
cloud partition should receive the job.
• The partition load balancer then decides how to assign the jobs to
the nodes.
• When the load status of a cloud partition is normal, this partitioning
can service the request.
• If the cloud partition load status is not normal, this job should be
transferred to another partition.
17. LOAD DEGREE CALCULATION:
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• Load degree of node is related to various static and dynamic parameters
Static parameters:
• No of CPUs.
• CPU processing speed.
• Memory speed.
Dynamic parameters:
• Memory utilisation.
• CPU utilization.
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LOAD DEGREE OF NODES:
• Step 1: Define a load parameter set
• F = { F1 , F2 ,F3…, Fm}
where Fi’s are static & dynamic load parameters and m is total no of
parameters
• Step 2: Compute the load degree as
Load Degree (N) = ∑
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• Step 3: Three node load status levels are then defined as
• Idle When
Load Degree( N ) = 0
there is no job being processed by this node
• Normal When
0 < Load Degree(N)<= Load Degree
The node is normal and it can process other jobs.
• Overload When
Load Degree <= Load Degree( N)
The node is not available and can’t receive jobs until it returns to the normal.
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LOAD DEGREE OF PARTITION:
• Load degree of partition can be calculated as:
Load_degree avg =
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BEST PARTITION SEARCH ALGORITHM:
begin
while job do
SearchBestPartition(job);
if partitionState == idle || partitionState==normal then
send job to partition
else
search for another partition.
end if
end while
end
22. WEIGHTED ROUND ROBIN ALGORITHM:
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STEP 1: Calculate the load degree of each node.
STEP 2: Make a circular queue of nodes ,arranged in ascending order
of their load degrees and queue ptr pointing to nodes with lowest
load degree.
Algorithm:
begin
while job do
Assign job to the node to which queue ptr is currently pointing to.
Move the queue ptr to next.
Re-calculate the load degree of the node and arrange nodes in circular queue.
end while
end
33. CONCLUSION:
• Load balancing in cloud computing environment has an important
impact on the performance.
• In this project we have proposed a better load balance model for very
large and complex public cloud.
• With cloud partitioning concept it is possible to provide good load
balancing and hence improving the overall performance.
34. REFERENCES:
1. Microsoft Academic Research,Cloud computing,
http://libra.msra.cn/Keyword/6051/cloud-
computing?query=cloud%20computing,2012.
2. A load balancing model based on cloud partitioning for the public cloud
by Gaochao Xu, Junjie Pang and Xiaodong Fu.
3. http://www.javatpoint.com/cloud-computing-tutorial.
4. http://www.tutorialpoint.com/cloud_computing/
5. B.Adler,Load balancing in the cloud: Tools,tips and
techniques,http://www.rightscal.com/info_center/white-papers/Load-
Balancing-in-the-Cloud.pdf,2012.
