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

Paul WatsonDigital Institute & School of Computing Science, Newcastle University, UK

Cloud Computing for Social Inclusion

Funders: RCUK Digital Economy Programme (SiDE), Microsoft, Red Hat, EU (Venus-C)

The result of related factors that prevent individuals or groups

from participating fully in the economic, social & political life

of society

Social Exclusion

• €15M Digital Economy Research “Hub”– Funded by the UK Research Councils– 2009-2014

• based at Newcastle & Dundee Universities

Plan

• How can Digital Technologies transform the lives of excluded people?

• How can Cloud Computing transform Science?

ActivitiesAccessibility Connected

Home & Community

Transport CreativeIndustries

Perspectives

Technology

Society

Business

Users

Design

ActivitiesAccessibility Connected

Home & Community

Transport CreativeIndustries

Perspectives

Technology

Society

Business

Users

Design

Accelerometer Video

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

Clinician’sReport

Information for

Users

Methodology section for

papers

Analysis

Sleep Activity Stability Grip … …

Clinician’sReport

Information for

Users

Methodology section for

papers

Analysis

Sleep Activity Stability Grip … …

Cloud

Cloud Computing• Opportunity to revolutionise IT (and Science)

– On-demand resources– Pay-as-you–go

Cloud Computing• Opportunity to revolutionise IT (and Science)

– On-demand resources– Pay-as-you–go

• But Major Barriers– Building Cloud-based systems– Security

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:

Cloud Infrastructure:Storage & Compute

App 1

....

App n

Building on Cloud Infrastructure

Problems

Cloud Infrastructure:Storage & Compute

App 1

....

App n

Science requires apps to be:scalable,

reliable, secure

This requires: expertise

time, money,

Cloud Catch 22

Most Projects &Organisations

that could benefitmost fromthe cloud

lack the IT skillsto do so

Cloud Infrastructure: Storage & Compute

Cloud Platform

App 1 .... App n

Cloud Infrastructure:Storage & Compute

App 1

....

App n

App ....

Workflow Enactment

API

Social Networking

Security

Processing Storage

App

Analysis Services

Cloud Infrastructure: Amazon, Azure, Private Clouds

Provenance/Audit

Metadata<expt>9127</expt><smiles>CHC3</smiles>

e-Science Central Video

http://www.youtube.com/watch?v=3rW2-W3cL0U

applications

• UK National X-ray photoelectron spectroscopy service

• speech to text applications• Supporting computer games for rehabilitating

stroke victims• machine learning• neuroscience

Scaling Response Time:460K workflow executions4.4M service calls200 Nodes5yrs 10 hours

Cloud Security Challenges

A. Smith378456729

Anonymize Analyzep = 30%q = 27.4r = 34

d0 s1 d2 s3 d4

Patient DataAccelerometer

Data Results

e-Science Central

Amazon

e-Science Central

Azure

e-Science Central

Private Cloud

Application

Public XOR Private Clouds

Other

Secure

Problem

• Can’t exploit multiple clouds in one workflow

A. Smith378456729

Anonymize Analyzep = 30%q = 27.4r = 34

d0 s1 d2 s3 d4

Patient DataAccelerometer

Data Results

Method(P. Watson, A Multi-Level Security Model for Partitioning Workflows over Federated Clouds IEEE CloudCom 2011)

1. Assign Security Level to each Workflow Block2. Check conforms to Bell-LaPadula3. Assign Security Level to each Cloud4. Determine possible allocations of blocks to clouds5. Determine candidate workflow partitioning6. Add inter-cloud data transfers7. Filter8. Apply Cost Model to Rank candidate solutions

http://www.cs.ncl.ac.uk/publications/trs/papers/1271.pdf

Bell LaPadula for Workflows

No Read UpNo Write Down

d0 s1 d2

1. Assign Security Level to each Workflow Block

A. Smith378456729

Anonymize Analyzep = 30%q = 27.4r = 34

d0 s1 d2 s3 d4

Patient Data

Heart Rate Data Results

Location: 1 0 0 0 0

Clearance: 1 0

3. Assign Security Level to each Cloud

Private Public

C1 C0

Location: 1 0

Extend Bell-LaPadula so a block cannot be deployed on a cloud with a lower security level

pa

d0 s1 d2

pb pc

5. Determine candidate workflow allocations

6. Add Inter-Cloud Transfers

6. Add Inter-Cloud Transfers

7. Filter

copyd0

ontopa

copyd2

ontopb

Valid Workflows

8. Apply Cost Model to Rank candidate solutions

Data Costs

8. Apply Cost Model to Rank candidate solutions

CPU Costs

8. Apply Cost Model to Rank candidate solutions

Transfer Costs

8. Apply Cost Model to Rank candidate solutions

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

Workflow Costs #13 4 6 5 2 1

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

Workflow Costs #21 2 5 6 3 4

e-Science Central

Amazon

e-Science Central

Azure

e-Science Central

Private Cloud

Application

Policy Manager

Security, Dependability, PerformanceRequirements

A Systematic Approach to Cloud Federation

Professor Patrick Olivier

How can people remain healthy and in their own homes for longer?

Ambient Kitchen Video

http://www.youtube.com/watch?v=nRAbAlqC_oY&list=UUiYv8UGLm8KEIM0J4G-lbIw&index=6&feature=plcp

Activity Recognition

PromptingPrompts

POMDP…

Events

Activities

Complex Event Processing

• SiDE aims to realise the potential of digital technology to make an impact on social exclusionwww.side.ac.uk

• How can we realise the potential of clouds?– overcome barriers: application development & security

• e-Science Central aims to do this– Ease of Use, Security, Scalability– Exploiting Federated Clouds