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OUTLINE Introduction
Objectives
Literature survey
Proposed system
Design document
Module Description
Application
Conclusion
Future Enhancement
INTRODUCTION
Cloud computing is a type of computing that relies
on sharing computing resources to handle
applications.
Load balancing in cloud environment is one of the
critical issue while processing and storing the
various multimedia application at the same time.
Cloud based multimedia system offers services of
generating, editing, processing of multimedia data
OBJECTIVES
To distribute the cloud data for more users at the same
time
Client can get the data without any interruptions.
To minimize the cost for transmitting multimedia data
between server clusters and clients
LITERATURE REVIEWS.No Paper Title Publicatio
n detailsProposed
workMerits Demerits
1 Dynamic
Multi-Service
Load Balancing in
Cloud-based
Multimedia
System
May 2013 in
IEEE
Transaction
To increase
the load
balancing
efficiency for
Cloud
Multimedia
files
Load
balancing
for all
multimedia
service tasks
are of the
same type is
maintained
Inability to
consider load
balancing
should adapt
to time
change in
dynamic
scenario
2 Multi-service
Load Balancing in
a Heterogeneous
Network with
Vertical Handover
November
2008 in
Springer
To overlay
heterogeneou
s
WiMAX/WL
AN network
thro’ vertical
handover
To improve
the
performance
of handover
user
Load
balancing in
WiMAX6
affect the
whole system
performance
PROPOSED SYSTEM
Huge number of clients request for different
Multimedia services through internet .
To implement a centralized Cloud-based Multimedia
System(CMS), we proposed a genetic algorithm for
concerned dynamic load balancing problem in CMS.
PROPOSED SYSTEM
The resource manager of CMS stores the global
service task load information collected from server
clusters
Decides the amount of client’s requests assigned to
each server cluster.
Then the load of each server cluster is distributed as
balanced as possible
GENETIC ALGORITHM
Solution to a problem solved by genetic algorithms, is
evolved
Algorithm is started with a set of solution
(represented by chromosomes) called Population
Solutions from one population are taken and used to
form a new population for a better one.
GENETIC ALGORITHM
Solutions which are selected to form new solutions
(offspring) are selected according to their fitness
function
The most suitable one will got more chances and
they have to reproduce
Repeated until some condition is satisfied.
MODULES DESCRIPTION
Authentication module
-Became authenticated person to request and
process the request.
MODULE DESCRIPTION
File upload module
-Admin upload all Multimedia files.
-Determine file path
- stored in the Cloud Server.
MODULE DESCRIPTION
Service requestor module
-User request a multimedia file to the Resource
Manager
-It assign the request to cloud server
APPLICATION
Cloud Service Oriented Applications
-Organized as object and they communicate
between the servers and collaborate over the network
Online Multimedia Tools and Application
-multiple media components are combined and
work together
CONCLUSION
In cloud paradigm the effective resource utilization is
required for achieving user satisfaction
Maximizing the profit for cloud service providers.
FUTURE ENHANCEMENT
As a future work we extend the behavioral
characterization of proximity malware to account for
strategic malware detection evasion with game theory
is a challenging task.
User utilizes the source with no limitation.
It accept certain range of request and once the server
free allows N number of request
REFERENCES
Yuming Jiang, Andrew Perkis, “Multi-service Load
Balancing in a Heterogeneous Network with Vertical
Handover,” International Journal of Advanced Research in
Computer and Communication Engineering, vol. 3, Issue.
7, pp. 7359–7362, July. 2014.
C. C. Lin, H. H. Chin, and D. J. Deng, "Dynamic Multi-
Service Load Balancing in Cloud-based Multimedia
System," IEEE System Journal, Vol. 8, Issue 1, pp. 225-
234, 2014.