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Cloud vs grid

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Cloud vs grid

  1. 1. CLOUD COMPUTING VS GRID COMPUTING PRESENTER : OMID SOHRABI 1
  2. 2. MAIN ARTICLE2
  3. 3. INTRODUCTION3 “computation may someday be organized as a public utility” John McCarthy Computing pioneer developed the Lisp programming language family
  4. 4. INTRODUCTION (CONTINUE)4 TeraGrid is an open scientific discovery infrastructure combining leadership class resources at eleven partner sites to create an integrated, persistent computational resource
  5. 5. DEFINITION OF CLOUD COMPUTING  There is little consensus on how to define the Cloud  A large-scale distributed computing paradigm that is driven by economies of scale, in which a pool of abstracted, virtualized, dynamically-scalable, managed computing power, storage, platforms, and services are delivered on demand to external customers over the Internet. Ian Foster  Cloud computing is using the internet to access someone else's software running on someone else's hardware in someone else's data center. Lewis Cunningham 5
  6. 6. DEFINITION OF CLOUD COMPUTING  There is little consensus on how to define the Cloud  A large-scale distributed computing paradigm that is driven by economies of scale, in which a pool of abstracted, virtualized, dynamically-scalable, managed computing power, storage, platforms, and services are delivered on demand to external customers over the Internet. Ian Foster  Cloud computing is using the internet to access someone else's software running on someone else's hardware in someone else's data center. Lewis Cunningham 6
  7. 7. Clouds: key points of the definition  Differences related to traditional distributed paradigms:  Massively scalable  Can be encapsulated as an abstract entity that delivers different levels of service  Driven by economies of scale  Services can be dynamically configured (via virtualization or other approaches) and delivered on demand 7
  8. 8. Clouds: reasons for interest  Rapid decrease in hw cost, increase in computing power and storage capacity (multi-cores etc)  Exponentially growing data size  Widespread adoption of Services Computing and Web 2.0 apps 8
  9. 9. Clouds: relation with other paradigms9 A Web 2.0 site may allow users to interact and collaborate with each other in a social media dialogue as creators of user-generated content in a virtual community, in contrast to Web sites where people are limited to the passive viewing of content. Examples of Web 2.0 include social networking sites, blogs, wikis, folksonomies, video sharing sites, hosted services, Web applications
  10. 10. GRID COMPUTING  Grid Computing enables resource sharing and coordinated problem solving in virtual organizations(VO) where each VO can consist of either physically distributed institutions or logically related projects/groups.  Builds a uniform computing environment from diverse resources by defining standard network protocols and providing middleware to mediate access to a wide range of heterogeneous resources (egGlobusToolkit). 10
  11. 11. GRID COMPUTING (continue)11
  12. 12. How technologists perceive the Cloud  “The interesting thing about Cloud Computing is that we’ve redefined Cloud Computing to include everything that we already do. . . . I don’t understand what we would do differently in the light of Cloud Computing other than change the wording of some of our ads.” 12 Larry Ellison (Oracle CEO) Wall Street Journal, September 26, 2008
  13. 13. How technologists perceive the Cloud  “A lot of people are jumping on the [cloud] bandwagon, but I have not heard two people say the same thing about it. There are multiple definitions out there of “the cloud.” 13 Andy Isherwood (HP VP of sales) ZDnetNews, December 11, 2008
  14. 14. How technologists perceive the Cloud  “It’s stupidity. It’s worse than stupidity: it’s a marketing hype campaign. Somebody is saying this is inevitable —and whenever you hear somebody saying that, it’s very likely to be a set of businesses campaigning to make it true.” 14 Richard Stallman (Advocator of Free Software) The Guardian, September 29, 2008
  15. 15. Is Cloud a new name for Grids?  YES: the vision is the same reduce the cost of computing increase reliability increase flexibility (transitioning from self-operation to third party) 15 The answer is complicated… IT reinvents itself every five years
  16. 16. Is Cloud a new name for Grids?  NO: things are different than 10 years ago New needs to analyze massive data, increased demand for computing Billions of dollars being spent by Amazon, Google,Microsoft to create real commercial large-scale systems with hundreds of thousands of computers – www.top500.org shows computers with 100,000+ cores Only need a credit card to get on-demand access to infinite computers 16
  17. 17. Is Cloud a new name for Grids?  Nevertheless YES: same problems but different details Problems are the same in clouds and grids How to manage large facilities How to discover, request, and use resources How to implement and execute parallel Computations 17
  18. 18. Clouds: side-by-side comparison with Grids  Business model  Architecture  Resource Management  Programming model  Application model  Security model 18
  19. 19. Cloud vs Grids - Business model  Traditional: one-time payment for unlimited use of software  Clouds: pay the provider on a consumption basis, computing and storage (like electricity, gas etc)  Grids: assigned a number of service units 19
  20. 20. Cloud vs Grids - Architecture20 communication and authentication protocols discovery, negotiation, monitoring, accounting and payment of sharing operations on individual resources interactions across collections of resources, directory services
  21. 21. Cloud vs Grids - Architecture21 resources that have been abstracted/encapsulated collection of specialized tools, middleware and services on top of the unified resources to provide a development and/or deployment platform
  22. 22. Cloud vs Grids - Architecture SPI Model  Cloud Software as a Service (SaaS)  Cloud Platform as a Service (PaaS)  Cloud Infrastructure as a Service (IaaS) 22
  23. 23. Cloud vs Grids - Architecture SPI MODEL (IaaS)  The capability provided to the consumer is to provision processing, storage, networks, and other fundamental computing resources.  Consumer is able to deploy and run arbitrary software, which can include operating systems and applications.  The consumer does not manage or control the underlying cloud infrastructure but has control over operating systems, storage, deployed applications, and possibly limited control of select networking components (e.g., host firewalls).  Typical examples are Amazon EC2 Service and S3 23
  24. 24. Cloud vs Grids - Architecture SPI MODEL (IaaS) 24
  25. 25. Cloud vs Grids - Architecture SPI MODEL (PaaS)  The capability provided to the consumer is to deploy onto the cloud infrastructure consumer created or acquired applications created using programming languages and tools supported by the provider.  The consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, or storage, but has control over the deployed applications and possibly application hosting environment configurations. 25
  26. 26. Cloud vs Grids - Architecture SPI MODEL (SaaS)  The capability provided to the consumer is to use the provider’s applications running on a cloud infrastructure.  delivers special purpose software that is remotely accessible. E.g,: Google Maps, Live Mesh from Microsoft etc  The consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, storage, or even individual application capabilities, with the possible exception of limited userspecific application configuration settings. 26
  27. 27. Cloud vs Grids – Resource Management  Compute model  Data model  Virtualization  Monitoring 27
  28. 28. Cloud vs Grids – Resource Management COMPUTE MODEL  Grids: batch-scheduled (queueing systems)  Clouds: resources shared by all users at the same time in contrast to dedicated resources in queueing systems  Maybe one of the major challenges in clouds: QoS! 28
  29. 29. Cloud vs Grids – Resource Management DATA MODEL  Data locality: to achieve good scalability data must be distributed over many computers  Clouds: use map-reduce mechanism like in Google to maintain data locality  In Grids, data storage usually relies on a shared file systems (e.g. NFS, GPFS, PVFS, Luster), where data locality cannot be easily applied 29
  30. 30. Cloud vs Grids – Resource Management Virtualization  Abstraction and encapsulation  Clouds: rely heavily on virtualization  Supports cost-effective use of cloud’s physical resources  Grids: do not rely on virtualization as much as clouds. due to policy and having each individual organization maintain full control of their resources  However, there are efforts in Grids to use virtualization as well, such as Nimbus 30
  31. 31. Cloud vs Grids – Resource Management Monitoring  Virtualization poses challenges to fine-grained control over monitoring  Service-oriented view means resources below service API are not visible  Monitoring may not be as important because of abstractions  Grid trust model allows users via their identity delegation to access and browse resources at different sites  Resources not highly abstracted & virtualized 31
  32. 32. Cloud vs Grids – Programming Model CLOUD  most use the map-reduce programming model. Implementation: Hadoop that uses Pig as a declarative programming language GRID  Complicated by issues like multiple administrative domains, resource heterogeneity, etc  heavy use of workflow tools to be able to manage large sets of tasks and data. others: MPICH-G2, WSRF, GridRPC… 32
  33. 33. Cloud vs Grids – Application Model CLOUD  Traditionally can support same apps as grid except HPC (due to low latency needs) but this is changing  Interactive, loosely-coupled, transaction-oriented apps GRID  Batch-oriented apps  Support High-Performance Computing (HPC) through High Throughput Computing (HTC)  Support workflows of loosely-coupled applications 33
  34. 34. Cloud vs Grids – Security Model  Clouds currently more homogeneous and single provider so security simpler  Still an important concern for cloud users  Email address & credit card gets you an account  Grids Built on assumptions of heterogeneous and dynamic resources and multiple admin domains  Stricter procedure to acquire an account 34
  35. 35. CONCLUSION35
  36. 36. CONCLUSION (continue)36
  37. 37. REFRENCES  Geelan, Jeremy. "Twenty-one experts define cloud computing." Cloud Computing Journal 4 (2009): 1-5  Foster, Ian, et al. "Cloud computing and grid computing 360-degree compared." Grid Computing Environments Workshop, 2008. GCE'08. Ieee, 2008.  Sharma, Prabha. "Grid Computing Vs. Cloud Computing." International Journal of Information and Computation Technology. 2013 ISSN: 0974-2239  Lewis Cunningham, Cloud Computing with Amazon and Oracle, 2008.  www.teragrid.org 37
  38. 38. THANKS FOR YOUR ATTENTION 38

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