![油
[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.
487494.
[3] Amazon Web Services, http://aws.amazon.com/.
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- 1. Presented by: Manoj kumar s Pradeep naik
- 2. Cloud computing is油Internet-based油computing,油whereby油 shared油resources,油software,油and油information油are油provided油 to油computers油and油other油devices油on油demand,油like油the油electricity油 grid.油 Cloud油 computing油 describes油 both油 a油 platform油 and油 a油 type油 of油 application.油 A油 cloud油 computing油 platform油 dynamically油 provisions,油configures,油reconfigures,油and油deprovisions油servers油 as油needed.
- 3. The油main油objective油of油the油project油油is油to油improve油the油downloading油of油large油amount油 of油data油stored油in油Amazon油S3油to油multiple油EC2油nodes,油by油presenting油two油most油 efficient油油algorithms.油The油two油algorithm油will油increase油the油through油put油by油following油 ways: They油can油construct油an油overlay油network油on油clouds油without油network油topology油 information. They油can油optimize油the油total油throughput油between油compute油nodes油dynamically. They油can油increase油the油download油throughput油from油cloud油storage油by油letting油 nodes油cooperate油with油each油other,油resembling油work油stealing油techniques.
- 4. Existing System Proposed System
- 5. Traditionally,油 HPC油 applications油 have油 been油 run油 on油 distributed油 parallel油 computers油 such油as油super油computers油and油large油cluster油computers.油 Especially油 data油 intensive油 HPC油 applications,油 such油 as油 BLAST,油 require油 very油 large油 computational油and油storage油resources油For油example,油the油ATLAS油experiment. While油clouds油are油currently油mainly油used油for油personal油and油commercial油use油(e.g.油for油 web油applications),油their油large油number油of油storage油and油computational油resources,油high油 accessibility,油reliability油and油simple油cost油model油make油them油very油attractive油for油HPC油 applications油as油well. 油油油油
- 6. One油or油more油spanning油trees油constructed油based油on油the油network油topology油and油 network油monitoring油data油in油order油to油maximize油available油bandwidth油and油avoid油 bottleneck油links. 油However,油delivering油optimal油performance油becomes difficult once the available bandwidth changes dynamically.
- 7. In油 this油 paper,油 we油 focus油 on油 Amazon油 EC2/S3油 (the油 most油 commonly油 used油 cloud油 platform油 today)油 and油 propose油 two油 high油 performance油 multicast油 algorithms.油 These油 algorithms油make油it油possible油to油efficiently油transfer油large油amounts油of油data油stored油in油 Amazon油S3油to油multiple油Amazon油EC2油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
- 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 nodes total available download throughput. The resulting multicast performance should be improved even further.
- 24. 油 [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. 487494. [3] Amazon Web Services, http://aws.amazon.com/. Bibliography