BY
G.ANBUMANI
SANDRA JOHNSON
J.AMUTHA
OUTLINE
 Introduction
 Objectives
 Literature survey
 Proposed system
 Design document
 Module Description
 Applica...
INTRODUCTION
Cloud computing is a type of computing that relies
on sharing computing resources to handle
applications.
L...
OBJECTIVES
 To distribute the cloud data for more users at the same
time
 Client can get the data without any interrupti...
LITERATURE REVIEW
S.No Paper Title Publicatio
n details
Proposed
work
Merits Demerits
1 Dynamic
Multi-Service
Load Balanci...
PROPOSED SYSTEM
 Huge number of clients request for different
Multimedia services through internet .
 To implement a cen...
PROPOSED SYSTEM
 The resource manager of CMS stores the global
service task load information collected from server
cluste...
GENETIC ALGORITHM
 Solution to a problem solved by genetic algorithms, is
evolved
 Algorithm is started with a set of so...
GENETIC ALGORITHM
 Solutions which are selected to form new solutions
(offspring) are selected according to their fitness...
DESIGN DOCUMENT
BLOCK DIAGRAM
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 Ser...
MODULE DESCRIPTION
 Service requestor module
-User request a multimedia file to the Resource
Manager
-It assign the reque...
APPLICATION
 Cloud Service Oriented Applications
-Organized as object and they communicate
between the servers and collab...
CONCLUSION
 In cloud paradigm the effective resource utilization is
required for achieving user satisfaction
 Maximizing...
FUTURE ENHANCEMENT
 As a future work we extend the behavioral
characterization of proximity malware to account for
strate...
REFERENCES
 Yuming Jiang, Andrew Perkis, “Multi-service Load
Balancing in a Heterogeneous Network with Vertical
Handover,...
Preserving load balance in multiservice cloud storage
of 19

Preserving load balance in multiservice cloud storage

centralized Cloud-based Multimedia System(CMS) and we proposed a genetic algorithm for concerned dynamic load balancing problem in CMS
Published on: Mar 4, 2016
Published in: Technology      
Source: www.slideshare.net


Transcripts - Preserving load balance in multiservice cloud storage

  • 1. BY G.ANBUMANI SANDRA JOHNSON J.AMUTHA
  • 2. OUTLINE  Introduction  Objectives  Literature survey  Proposed system  Design document  Module Description  Application  Conclusion  Future Enhancement
  • 3. 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
  • 4. 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
  • 5. LITERATURE REVIEW S.No Paper Title Publicatio n details Proposed work Merits 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
  • 6. 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.
  • 7. 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
  • 8. 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.
  • 9. 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.
  • 10. DESIGN DOCUMENT
  • 11. BLOCK DIAGRAM
  • 12. MODULES DESCRIPTION  Authentication module -Became authenticated person to request and process the request.
  • 13. MODULE DESCRIPTION  File upload module -Admin upload all Multimedia files. -Determine file path - stored in the Cloud Server.
  • 14. MODULE DESCRIPTION  Service requestor module -User request a multimedia file to the Resource Manager -It assign the request to cloud server
  • 15. 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
  • 16. CONCLUSION  In cloud paradigm the effective resource utilization is required for achieving user satisfaction  Maximizing the profit for cloud service providers.
  • 17. 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
  • 18. 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.

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