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On the Varieties of Clouds for Data Intensive Computing

Robert L. Grossman University of Illinois at Chicago And Open Data Group. Yunhong Gu University of Illinois at Chicago. On the Varieties of Clouds for Data Intensive Computing. 董耀文 1098308101 碩資工一甲 @ Antslab. Outline. What is Cloud ? Types of Clouds

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On the Varieties of Clouds for Data Intensive Computing

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  1. Robert L. Grossman University of Illinois at Chicago And Open Data Group YunhongGu University of Illinois at Chicago On the Varieties of Clouds for Data Intensive Computing 董耀文 1098308101 碩資工一甲 @ Antslab

  2. Outline • What is Cloud ? • Types of Clouds • Clouds provide on-demand computing capacity • Experimental Studies • Research Questions

  3. What is Cloud?

  4. What is Cloud? • An infrastructure. • At scale and reliability of a data center. • Provides resources or services. • Google • Hadoop • Amazon’s EC2

  5. Types of Clouds

  6. Types of Clouds • Architecural Model • Loosely coupled commodity computers. • Computing instances on demand. • Amazon’s EC2 • US $0.10 /1hr • 1.0~1.2GHz 2007 Opteron or Xeon processor • 1.7 GB memory • 160GB disk • Moderate I/O performance

  7. Types of Clouds • Tightly Coupled • Loosely coupled

  8. Types of Clouds • Architecural Model • Computing capacity on demand • Google’s MapReduce • TeraSort use1800 machines. • 2GHz Xeon process • 4GB memory • 2 * 160GB IDE disks • TeraSort • Sort 100-byte records. ( 1TB data ) • Required ~= 891s

  9. Types of Clouds • Architecural Model • Open source • Eucalyptus (Elastic Utility Computing Architecture for Linking Your Programs To Useful Systems) • University of California, Santa Barbara • Linux & Xen • Hadoop • HadoopMapReduce • HDFS • HBase

  10. Types of Clouds • Programming Model • On-demand computing support any computing model compatible with loosely coupled clusters. • Amazon EC2 • MapReduce : < key, value > • Map : map each < key, value >pair into a new pair of < key,value > • Reduce : merges values with the same key • Sector/Sphere : User Defined Function(UDF)

  11. Types of Clouds • Management Model • Internal vsHosted • Private vs Shared • Combinations(Hybrid)

  12. Types of Clouds • Payment Model • Pay as you go. • Buy. • make arrangements with a third party to pay for the exclusive use of cloud resources for a specified period of time.

  13. Types of Clouds • What’s New? • New scale. • Hadoop • Google • New simplicity clouds provide. • Amazon’s EC2,S3 • AMI(Amazon Machine Image)

  14. Clouds provide on-demand computing capacity • Google Cloud • GFS (Google File System) • MapReduce • BigTable

  15. Clouds provide on-demand computing capacity • MapReduce m(Bear) <key,value> m(River)

  16. Clouds provide on-demand computing capacity

  17. Clouds provide on-demand computing capacity • UDT(UDP-based Data Transfer) • Designed for extremely high speed networks. • Concurrent UDT flows share the available bandwidth fairly. • Resides completely at the application level. • User defined congestion control algorithms. • Easier to traverse the firewall.

  18. Experimental Studies

  19. Experimental Studies • 10 Gb/s networks. • 30 DELL 1435 computer • 4G memory • 1TB disk • 2.0GHz dual-core ADM Opteron 2212 • 1Gb/s NIC

  20. Experimental Studies hadoop sector

  21. Experimental Studies • CreditStone • credit card transactions. • flags some of the transactions.

  22. Research Questions • Quite easy to use. • Develop appropriate network protocols, architectures and middleware for wide area clouds. • How different clouds can interoperate. • Develop standards and standards based architectures for cloud services. • Alternate storage • Compute • Table services

  23. THANKS

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