1. Presented by:
Manoj kumar s
Pradeep naik

2.  Cloud computing is Internet-based computing, whereby
shared resources, software, and information are provided
to computers and other devices on demand, like the electricity
grid.
 Cloud computing describes both a platform and a type of
application. A cloud computing platform dynamically
provisions, configures, reconfigures, and deprovisions servers
as needed.

3.  The main objective of the project is to improve the downloading of large amount
of data stored in Amazon S3 to multiple EC2 nodes, by presenting two most
efficient algorithms. The two algorithm will increase the through put by following
ways:
 They can construct an overlay network on clouds without network topology
information.
 They can optimize the total throughput between compute nodes dynamically.
 They can increase the download throughput from cloud storage by letting
nodes cooperate with each other, resembling work stealing techniques.

4.  Existing System
 Proposed System

5.  Traditionally, HPC applications have been run on distributed parallel computers
such as super computers and large cluster computers.
 Especially data intensive HPC applications, such as BLAST, require very large
computational and storage resources For example, the ATLAS experiment.
 While clouds are currently mainly used for personal and commercial use (e.g. for
web applications), their large number of storage and computational resources, high
accessibility, reliability and simple cost model make them very attractive for HPC
applications as well.

6.  One or more spanning trees constructed based on the network topology and
network monitoring data in order to maximize available bandwidth and avoid
bottleneck links.
 However, delivering optimal performance becomes difficult once the available
bandwidth changes dynamically.

7.  In this paper, we focus on Amazon EC2/S3 (the most commonly used cloud
platform today) and propose two high performance multicast algorithms. These
algorithms make it possible to efficiently transfer large amounts of data stored in
Amazon S3 to multiple Amazon EC2 nodes.

8.  Processor : Pentium-III
 Speed : 1.1GHz
 RAM : 512MB
 Hard Disk : 40GB
 General : Keyboard, Monitor , Mouse
 Operating System : Windows XP
 Software : jdk 1.5, Servlets
 Back End : Oracle / Mysql
 Server : Tomcat server / Weblogic server
Software specification :
Hardware specification :

9. Algorithms:
 Steal algorithm
 Non-Steal algorithm
Modules Used:
The project is divided into 2 major modules
 Server Module
 Client Module

10. Client Clouds Server
Register & Login
Get Access key &
secret Key
Upload Files
Store user credentials
and files
Download Files
Context Level DFD
Data Flow Diagram

11. Secret key
Access Key
Login
Services
Create
Bucket Refresh
bucket List Delete Bucket File upload
File list
Files in Bucket
Network
Credentials
Service selection
Select
Select Select
Select
Select
Show
Level One DFDLevel One DFD

12. Secret key
Access Key
Login Services
Create
Bucket
Stored Files
Server
Clients
Network
Credentials
select
Accept Files From User
Retrieve files from Bucket
Download
Upload
Level Two DFDLevel Two DFD

13. Secret key
Access Key
Login
Network
Credentials
Bucket
Server
File Sharing
Client1 Client2 Client3
Accept files from Client
Stored files
Retrieve files from Bucket
List
List
ListDownload
Download
Download
Show Show
Non-Steal AlgorithmNon-Steal Algorithm

14. Secret key
Access Key
Login
Network
Credentials
Bucket
Server
File Sharing
Client1 Client2 Client3
Accept files from Client
Stored files
Retrieve files from Bucket
List
List
List
Download
Download
Download
Show Show
Request/Response Request/Response
Request/Response
Steal AlgorithmSteal Algorithm

15. Register/login
Get access key
and
secret key
Upload files
Download files
Client Server
Client Side
Use Diagram for Client SideUse Diagram for Client Side

16. Server
Server side
Store user
credentials
Generate access
and secret key
Send keys to user
Accept files
from user
Store files
in the bucket
Retrieve files from
Bucket and send
to users
Server Side use case

17. Server Amazon S3
Get_connection()
Connection established
Create bucket()
Bucket created
Upload files
File uploaded
Sequence diagram:Sequence diagram: Services provided by Amazon S3Services provided by Amazon S3

18. client server Amazon
S3
get Connection
Request File List
Get file list from bucket
Send file List
Download file List
Download file from S3
File downloaded

19. CClient 1 Client 2 Client 3
Request to Download Files
Request to Download Files
Downloading files
Send Files
Send Files
Work Stealing mechanism between Clients usingWork Stealing mechanism between Clients using
Steal algorithmSteal algorithm

20. Home
Register/Login
Generating access key
and secret key
Send keys to user
Store files into bucket
Retrieve files from bucket
Divide and send files to user

21. Main_console
Server
Server_socket
Awt_components
Init_components()
Init_iostream()
Getawsconnections()
Start_Server()
Action_performed()
Server
Server_socket
Awt_components
Init_components()
Init_iostream()
Start_Server()
Action_performed()
Client

22. Start
Fetch files from the Bucket
Divide the files into n equal parts
Send filenames to nodes
Send file contents to nodes
Stop

23. We have presented two high performance multicast algorithms. These algorithms
make it possible to transfer large amounts of data stored in S3 to multiple EC2
nodes efficiently.
Future Enhancement :
 Merge the two phases into one phase so as to overlap the S3 to EC2 and intra-
EC2 transfers to allow early dissemination of already fetched data.
 Use multiple connections from each EC2 node to S3 for satisfying each node’s
total available download throughput. The resulting multicast performance should be
improved even further.

24.
[1] Dynamic Load-Balanced Multicast for Data-Intensive Applications on Clouds
Tatsuhiro Chiba, Mathijs den Burger, Thilo Kielmann, and Satoshi Matsuoka. 2010
10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
[2] T. Chiba, T. Endo, and S. Matsuoka, “High-performance mpi broadcast
algorithm for grid environments utilizing multi-lane NICs,” in 7th IEEE
International Symposium on Cluster Computing and the Grid (CCGrid), 2007, pp.
487–494.
[3] Amazon Web Services, http://aws.amazon.com/.
Bibliography