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Paul Watson Digital Institute & School of Computing Science, Newcastle University, UK

Cloud Computing for Social Inclusion . Paul Watson Digital Institute & School of Computing Science, Newcastle University, UK. Funders: RCUK Digital Economy Programme (SiDE), Microsoft, Red Hat, EU (Venus-C). Social Exclusion. T he result of related factors

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Paul Watson Digital Institute & School of Computing Science, Newcastle University, UK

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  1. Cloud Computing for Social Inclusion Paul Watson Digital Institute & School of Computing Science, Newcastle University, UK Funders: RCUK Digital Economy Programme (SiDE), Microsoft, Red Hat, EU (Venus-C)

  2. Social Exclusion The result of related factors that prevent individuals or groups from participating fully in the economic, social & political life of society

  3. €15M Digital Economy Research “Hub” • Funded by the UK Research Councils • 2009-2014 • based at Newcastle & Dundee Universities

  4. Plan • How can Digital Technologies transform the lives of excluded people? • How can Cloud Computing transform Science?

  5. Accelerometer Video http://www.youtube.com/watch?v=hlmsrJOheS8&list=UUiYv8UGLm8KEIM0J4G-lbIw&index=5&feature=plcp

  6. Analysis Sleep Activity Stability Grip … … Information for Users Clinician’s Report Methodology section for papers

  7. Analysis Sleep Activity Stability Grip … … Cloud Information for Users Clinician’s Report Methodology section for papers

  8. Cloud Computing • Opportunity to revolutionise IT (and Science) • On-demand resources • Pay-as-you–go

  9. Cloud Computing • Opportunity to revolutionise IT (and Science) • On-demand resources • Pay-as-you–go • But Major Barriers • Building Cloud-based systems • Security

  10. Cloud Computing • Opportunity to revolutionise IT (and Science) • On-demand resources • Pay-as-you–go • But Major Barriers • Building Cloud-based systems • Security • Our work to address this:

  11. Building on Cloud Infrastructure App 1 App n .... Cloud Infrastructure: Storage & Compute

  12. Problems Science requires apps to be: scalable, reliable, secure App 1 App n .... This requires: expertise time, money, Cloud Infrastructure: Storage & Compute

  13. Cloud Catch 22 Most Projects & Organisations that could benefit most from the cloud lack the IT skills to do so

  14. App 1 App n .... Cloud Platform App 1 App n .... Cloud Infrastructure: Storage & Compute Cloud Infrastructure: Storage & Compute

  15. .... App App Analysis Services API Security Provenance/ Audit Social Networking Workflow Enactment Metadata <expt>9127</expt> <smiles>CHC3</smiles> Processing Cloud Infrastructure: Amazon, Azure, Private Clouds Storage

  16. e-Science Central Video http://www.youtube.com/watch?v=3rW2-W3cL0U

  17. applications • UK National X-ray photoelectron spectroscopy service • speech to text applications • Supporting computer games for rehabilitating stroke victims • machine learning • neuroscience

  18. Scaling Response Time: 460K workflow executions 4.4M service calls 200 Nodes 5yrs  10 hours

  19. Cloud Security Challenges Patient Data Accelerometer Data Results Smith 378456729 Anonymize Analyze p = 30% q = 27.4 r = 34 d0 s1 d2 s3 d4

  20. Public XOR Private Clouds Application Secure Other e-Science Central e-Science Central e-Science Central Amazon Azure Private Cloud

  21. Problem Patient Data Accelerometer Data • Can’t exploit multiple clouds in one workflow Results Smith 378456729 Anonymize Analyze p = 30% q = 27.4 r = 34 d0 s1 d2 s3 d4

  22. Method(P. Watson, A Multi-Level Security Model for Partitioning Workflows over Federated Clouds IEEE CloudCom 2011) • Assign Security Level to each Workflow Block • Check conforms to Bell-LaPadula • Assign Security Level to each Cloud • Determine possible allocations of blocks to clouds • Determine candidate workflow partitioning • Add inter-cloud data transfers • Filter • Apply Cost Model to Rank candidate solutions http://www.cs.ncl.ac.uk/publications/trs/papers/1271.pdf

  23. Bell LaPadula for Workflows d2 d0 s1 No Read Up No Write Down

  24. 1. Assign Security Level to each Workflow Block Patient Data Heart Rate Data Results Smith 378456729 Anonymize Analyze p = 30% q = 27.4 r = 34 d0 s1 d2 s3 d4 Location:10000 Clearance:10

  25. 3. Assign Security Level to each Cloud Public Private C1 C0 Location: 1 0

  26. Extend Bell-LaPadula so a block cannot be deployed on a cloud with a lower security level d2 d0 s1 pa pb pc

  27. 5. Determine candidate workflow allocations

  28. 6. Add Inter-Cloud Transfers

  29. 6. Add Inter-Cloud Transfers

  30. 7. Filter copy d2 onto pb copy d0 onto pa

  31. Valid Workflows

  32. 8. Apply Cost Model to Rank candidate solutions Data Costs

  33. 8. Apply Cost Model to Rank candidate solutions CPU Costs

  34. 8. Apply Cost Model to Rank candidate solutions Transfer Costs

  35. 8. Apply Cost Model to Rank candidate solutions

  36. 8. Apply Cost Model to Rank candidate solutions: Example 1

  37. Workflow Costs #1 1 4 5 3 6 2

  38. 8. Apply Cost Model to Rank candidate solutions: Example 2.

  39. Workflow Costs #2 1 2 6 5 3 4

  40. A Systematic Approach to Cloud Federation Security, Dependability, Performance Requirements Application Policy Manager e-Science Central e-Science Central e-Science Central Amazon Azure Private Cloud

  41. How can people remain healthy and in their own homes for longer? Professor Patrick Olivier

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