SOFSEM 2013 :=
The Challenges in ICT:
Debunking the Hype
Keith G Jeffery
Science and Technology Facilities Council
Harwell Oxford
Rutherford Appleton Laboratory, OX11 0QX
UK
e-mail: keith.jeffery@stfc.ac.uk
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SOFSEM 2013 :=
The Challenges in ICT:
Debunking the Hype
Or the
nebulous
concept of
CLOUD
Computing
©STFC/Keith G Jeffery
Keith G Jeffery
Science and Technology Facilities Council
Harwell Oxford
Rutherford Appleton Laboratory, OX11 0QX
UK
e-mail: keith.jeffery@stfc.ac.uk
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STRUCTURE
Introduction – Who?
The Pervasiveness of ICT
A Short History of ICT
CLOUD Computing
Challenges
Conclusion
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Rutherford Appleton
Laboratory
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Brief Biography
• Degree and PhD in
Geology
• Led teams working
on information
systems
• (R&D and services)
• Director IT
• 1100 servers, 360,000
users, 8Pb/year
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Associations
=: SOFSEM :=
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EC CLOUDs Expert Group
Report 1: Work 2010,
Event January 2011
Published January 2011
http://cordis.europa.eu/fp7/ict/ssai/docs/cloud-report-final.pdf
Report 2: Work 2011,
Event May 2012
Published December 2012
http://cordis.europa.eu/fp7/ict/ssai/home_en.html
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So?
This background gives you some idea of ‘where
I’m coming from’
– Advanced research problems requiring ICT solutions
– Research practical (yet leading edge)
• But depends on ‘blue sky’
– International working – consultancy, reviewing, expert
– Strategic thinking for / using blue sky research to plan
roadmaps for ICT R&D
– Design authority for large industrial-scale projects
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So?
This background gives you some idea of ‘where I’m coming from’
– Advanced research problems requiring ICT solutions
– Research practical (yet leading edge)
• But depends on ‘blue sky’
– International working – consultancy, reviewing, expert
– Strategic thinking for / using blue sky research to plan roadmaps for ICT R&D
– Design authority for large industrial-scale projects
And what I am going to talk about is the ICT of
the future that we shall all be using and/or
developing
And the research challenges we have to
overcome to make it happen
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STRUCTURE
Introduction – Who?
The Pervasiveness of ICT
A Short History of ICT
CLOUD Computing
Challenges
Conclusion
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Internet Users by Region
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The ASIA Timebomb
ASIA has largest
population, largest
number of users but
relatively low
penetration
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Mobile Internet
• Global mobile data traffic in 2011 (597 petabytes per
month);
• Global mobile data traffic grew 2.3-fold in 2011,
more than doubling for the fourth year in a row;
• The number of mobile-connected devices
exceeded the world's population in 2012.
• There will be over 10 billion mobile-connected
devices in 2016;
• The average mobile network connection speed (189
kbps in 2011) will exceed 2.9 megabits per second
(Mbps) in 2016.
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Mobile Traffic Growth
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Mobile Traffic Sources
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Non-user devices
•The vast majority of computers – 98% - do not
have traditional keyboard, mouse, screen
– They are in cars, planes, washing machines, mobile
phones
•The most-used operating system is NOT
Windows (or Unix / Linux)
– Symbian in mobile phones  iOS  Android
– or specialised operating systems (e.g. Contiki) in
embedded systems
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Social Context
•The number of computers will vastly outnumber humans on the planet very soon;
•Everything will be computerised;
– Sensor networks
• Home, healthcare, environment, industrial
processes, transport systems….
– Control systems
• Industrial, transport, home (central heating)…
Just think what a neutron bomb in the
atmosphere could do
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So…
•This is the ‘internet of things’ or ‘future internet’
•We need to :
– Manage the huge numbers, sizes
– Integrate the different kinds of systems
– Into one environment leading to human decision-making
• whether managing a business, shopping, media choice, social
interaction
•But there is a problem…in last 20 years
– Data storage density increased
~10**18
– Processor power increased
~10**15
– BUT broadband capacity increased ~10**4
•This has implications for Information Systems Engineering!
•In fact the requirement and limitations challenge the very basis of
traditional computer science / ICT
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Issues
Elastic scalability
costs, green
Trust & security & privacy
confidence
Manageability
else many administrators
Accessability
different modes of use
Useability
natural – fits with user model of the world
Representativity
of the real world
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STRUCTURE
Introduction – Who?
The Pervasiveness of ICT
A Short History of ICT
CLOUD Computing
Challenges
Conclusion
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Era 1
User request, programmer, punched cards, low-level program, mainframe
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Era2
User interacts with in-house-written software in high level language on
mainframe or mini. Network proprietary.
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Era3
User interacts with off-the-shelf software on PC which interacts with inhouse-written or purchased software on mainframe. Client-server to 3-tier.
Network is (becoming) internet
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Era4
User interacts with pre-written software on mobile device which interacts with
pre-written software on mainframe. Network is internet WiFi, 3G, 4G… and
using WWW
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CLUSTERs & GRIDs
Having virtualised the way the user interconnects to the application
on the mainframe (Client-Server or 3-tier)
the next logical step is to virtualise the mainframe
CLUSTER
•Racked mainframe
in-house
•Homogeneity
•Dynamically
reassigned
resources
GRID
•Distributed racked
mainframes
•Heterogeneity
•Dynamically
reassigned resources
•Mobile Code
Which leads us towards CLOUD Computing
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Software
Just to mention there has been a parallel evolution in:
• Programming languages
• Machine code, assembler, autocode, 3G (imperative), functional,
4G (declarative), scripting, mobile
• Data modelling and management
• Lists, hierarchies, networks (E-R), graphs (EER, ORM)
• Software and systems design
• Including human factors, adopting new modalities (mouse, gesture,
speech, brain-connected)
• Systems development methods (CASE to IDE)
• HIPO, Jackson, SSADM, PRINCE (waterfall to spiral)
• Object-orientation (aspect orientation)
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STRUCTURE
Introduction – Who?
The Pervasiveness of ICT
A Short History of ICT
CLOUD Computing
Challenges
Conclusion
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Definition
cloud (klaʊd) an elastic execution
environment of resources involving multiple
stakeholders and providing a metered service
at multiple granularities for a specified level
of quality (of service).
From report EC Cloud Computing Expert Group January 2011
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Cynicism
2010 we
recognized that all
our processes were
far too complex
so we put
them in
the cloud
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CLOUDs in use
• Social networking
•
E.g. Facebook
• Email systems
•
E.g. Gmail
• Office systems
•
E.g. Google Docs
• Shared storage
•
E.g. Google Drive
©STFC/Keith G Jeffery
But also
1.Software / system
development away
from production
systems
2.Experimental
techniques (like a
sandbox)
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Gartner Hypecycle
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Gartner Hypecycle
Opportunity gap
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Cloud Computing
•Very old idea
•Use of cloud to depict a
computing service or
network
The premise:
Most compute centres utilise only 10%
of capacity but need 100% for rare
peaks of demand
•virtualisation
•Now used for a new
concept
•Confused with
–
–
–
–
GRIDs
Autonomic computing
Utility Computing
Service-Oriented Architecture
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Cloud Computing
Hardware
•A very large number of processors
– Clustered in racks as blades
•In one major computer centre
– May be replicated for business continuity
•With massive online storage
– RAID for resilience
•And excellent communications links
Economies of
scale – both
purchasing
and operation
Energy
economies in
location
Staffing
economies in
location
– For access
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Cloud Computing
Customer View
•Low cost of entry for customers
•Device and location independence
•Capacity at reasonable cost (performance, space)
•Cloud Operator manages resource sharing balancing different
peak loads
•Elastically scalable as demand rises (or falls) from user
•Security due to data centralisation and software centralisation
•Sustainable and environmentally friendly – concentrated power
• it is a service and the user does not know or care
from where, by whom, and how it is provided
• as long as the SLA (service level agreement) QoS
(quality of service) is satisfied
• it is a ‘computing utility’ (IaaS, PaaS, SaaS….’XaaS’)
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Cloud Computing
Ownership
• Private Cloud: in-house cluster run
using CLOUD middleware;
• Public Cloud: outsourced computing to
commercial provider – proprietary;
• Hybrid Cloud: linked Private and Public
CLOUDs
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Cloud Computing
Offerings
Acknowledgements
to U Southampton
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Cloud Computing
How does it work
• Multitenancy: Cloud resources (hardware)
shared dynamically between customers;
• Each customer application in its own virtual
machine
• Isolation for security, privacy
• Allows scheduling with respect to shared resources
• Application in one VM multithreaded with user
data / profiles etc in other VMs
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Cloud Computing
What is it?
•Is cluster computing
– with the advantages that brings
•With GRIDs features
– Scheduling / resource allocation
– self-*
•ASP (Application Service Provider)
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Cloud Computing
•Obtains from GRIDs work:
– resource sharing/scheduling
– virtualisation of hardware and low-level software (under
middleware)
– resilience
– trust, security, privacy
– (more or less) self-*
Utility computing
Autonomic computing
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Cloud Computing
Obtains from software/systems
engineering:
Service-Oriented Architecture
with implications of interfaces,
metadata, composition
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Cloud Computing
But the real novelty is…
• Pay-As-You-Go (only for what you need);
• Accounting for ICT used by
departments in an organisation;
• Private cloud
• Public cloud
• CAPEX to OPEX
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Cloud Computing
•Private Cloud Software :
•Private/Hybrid Cloud software:
Eucalyptus
Open Nebula,
Open Stack
•Commercial examples of Public Clouds:
•
Amazon
EC2 Elastic Compute Cloud
•
Google
(Engine for Apps; Connect for Office)
•
Microsoft Azure
•
IBM
SmartCLOUD
•(note all needed massive resource for infrequent use so
could sell of excess capacity)
•Note Thomas J Watson in late fifties:
“total number of computers required in the world is five”
• are we reaching this goal?
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Cloud Problems
•Inefficient to move data to the cloud
•Remember earlier comments about networking
bandwidth
•Hard to realise the technology - elasticity
•Despite SLA/QoS guarantees some concerns:
•Performance
•Security/trust/privacy
•Especially transnational
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Cloud Studies
Above the Clouds: A Berkeley View of
Cloud Computing
http://www.eecs.berkeley.edu/Pubs/Tech
Rpts/2009/EECS-2009-28.pdf
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Cloud Quotes
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.
Larry Ellison, quoted in the Wall Street Journal, September 26,
2008
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.
Richard Stallman, quoted in The Guardian, September 29, 2008
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Hype?
• Architectural model: outsourcing – to large
datacentres - has been around as long as
computing
• Business Model: So has ‘pay as you go’
• The difference now is
•
•
Autonomicity for management (including elastic
scalability)
SOA (Service Oriented Architecture)
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Characterisation
PaaS
IaaS
SaaS
Elasticity
Reliability
Virtualisation
Public
FEATURES
…
Cost
Reduction
Cloud
Systems
…
COMPARES TO
…
LOCALITY
Remote
Distributed
STAKEHOLDERS
Service-oriented
Architecture
Users
Internet of
Services
©STFC/Keith G Jeffery
Hybrid
MODES
Local
BENEFITS
Ease of use
Private
TYPES
Adopters
Resellers
…
Grid
Providers
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Terminology
Types of Clouds
– IaaS; PaaS; SaaS
Deployment Types (Usage)
– Private, Public and Hybrid Clouds
– Community Cloud and Special Purpose Clouds
Cloud Environment Roles
– Cloud Providers: offer cloud systems
– Cloud Resellers or Aggregators: aggregate platforms from cloud providers
– Cloud Adopters or Software / Services Vendors: use cloud platforms to
enhance their services
– Cloud Consumers or Users: make direct use of the cloud capabilities
– Cloud Tool Providers: provide supporting tools for using / improving cloud
environments
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Characteristics
Non-Functional
Economic
Technological
relate to qualities
of cloud systems,
rather than
technological
aspects. These
include:
key driver behind
(commerical) cloud
systems. Typical
interest rests on:
Arise from
realising nonfunctional /
economic
concerns.
Particular issues:
Elasticity
Reliability
Quality of service
Agility and
adaptability
• Availability
•
•
•
•
©STFC/Keith G Jeffery
• Cost reduction
• Pay per use
• Improved time to
market
• Return of
investment
• CAPEX to OPEX
• “Going green”
The Challenges in ICT: Debunking the Hype
• Virtualisation
• Multi-tenancy
• Security, privacy
and compliance
• Data
management
• APIs and / or
programming
enhancements
• Metering
• Tools in general
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Related Areas
Internet of Services
– Cloud systems are “enablers” for Internet of Services
Internet of Things
– No direct relationship
– Clouds may extend capabilities of the IoT
The Grid
– Strong conceptual overlap
– Services may move from grid to cloud
Service Oriented Architectures
– Clouds principally architecture-agnostic
– Service offerings should follow the SOA model
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State of the Art
Commercial Efforts
Research & Academic Efforts
•
•
•
•
•
Manageability and Self-*
Data Management
Privacy & Security
Federation & Interoperability
Virtualisation, Elasticity and
Adaptability
• APIs, Programming Models &
Resource Control
Technical Gaps
©STFC/Keith G Jeffery
• Legislation, Government &
Policies
• Economic Concerns
Non-Technical
Gaps
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Economic Aspects
Cost Reduction
Pay per Use
Improved Time to Market
Return on Investment
CAPEX to OPEX
Going Green
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Legislation, Governance,
Policies
No standards – vendor lock in
Legality of operating / using CLOUDs
– International jurisdiction
– Privacy and personal data
Security of operating / using CLOUDs
– International jurisdiction
– Security and investigatory powers
No free market in services across CLOUDs
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Opportunities
Enhanced Technical
Capabilities
Reference Implementations
Easier Toolsets
Policies & Governmental
Issues
Clear Legalistic Solutions
Global Cloud Ecosystems
major contributions to
Increased Interoperability
Tools & Service Market
Cloud Knowledge &
Business Expertise
Clouds Provisioning &
Usage
Higher Trust in Clouds
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Analysis
Cloud computing will play a relevant role in (at least) the next 10
years
Current status insufficient for future business needs
 Europe can contribute in particular with
– R&D in the technological and non-technological areas
– Legislatory & governmental support
– Business & economical expertise
 Relevant business opportunities
–
–
–
–
IaaS Cloud Provisioning
PaaS Cloud Provisioning
Cloud Adopters and Service Vendors (Enhanced Service (SaaS) Provisioning)
Cloud Consultancy
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Research Issues
Business opportunities not currently realisable
Existing knowledge from preceding research and development can
be harvested
Technical
Non-Technical
• Scale and elastic
• Economic aspects
scalability
• Legalistic issues
• Trust, security and privacy
• Data handling
• Programming models and
resource control
• Systems development and
management
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Target
Private CLOUD
(inhouse, cluster)
interface
Common Service Environment with metadata
and dynamic systems development and composition capability
interface
Public CLOUD
©STFC/Keith G Jeffery
interface
Public CLOUD
interface
Other Private
CLOUD
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What Stops us..
• I have listed a whole lot of CLOUD
specific problems already such as:
•
•
•
•
Interoperability / vendor lock-in
Security, privacy
Quality of service / service level agreements
Legislation
• But CLOUDs throws into sharp relief
many underlying computer science /
informatics problems
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STRUCTURE
Introduction – Who?
The Pervasiveness of ICT
A Short History of ICT
CLOUD Computing
Challenges
Conclusion
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Research
Challenges: 1
Metadata
•the need for metadata related to services,
data/information/knowledge, agents;
•what is data, what is metadata?
•kinds of metadata and their use;
•representation and structure - syntax;
•semantics (meaning);
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The Vision: The Models
Complete cohort of users
User Model
interaction with data, processing, persons
Processing Model
representing the world
providing what the user
requires
Data Model
representing ICT
Resource Model
Complete ICT environment
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The Vision: Metadata for
ENGAGE Data Model
Linked
open data
DISCOVERY
(DC, eGMS…)
Generate
CONTEXT
(CERIF)
Formal
Information
Systems
©STFC/Keith G Jeffery
Point to
DETAIL
(SUBJECT OR TOPIC
SPECIFIC)
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Research
Challenges: 2
Management of state
•detection of state across millions of
individual nodes;
•maintenance of state across many
nodes;
– transactions and locking;
– roll-back and compensation;
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Management of
State
•ACID, 2PC, Locking, Rollback or compensation:
– As number of tables increases
– And the number of instructions to be executed increases
– And the latency (due to distribution) increases
•It becomes impossible to represent the real world
with:
– Integrity
– Consistency
– Accuracy
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Research
Challenges: 3 (1)
Data representativity
•data structures representing real-world interrelationships;
– data attribute value encoding (character set, media
encoding), types, lengths;
– data attribute value language;
– fully connected graphs – the death of the hierarchy;
– the time-machine: temporal duration of the interrelationships;
– certainty, probability of the inter-relationships
– Incomplete and inconsistent information
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Research
Challenges: 3 (2)
Data representativity
•Interoperation
– reconciliation of different data structures
representing a similar real-world domain;
•data location / locality and replication
– for business continuity;
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Data
Representativity:
Interoperation
•Homogeneous view over heterogeneous
sources
– Character set, language, syntax, semantics
•Schema reconciliation
– Structural mapping – graph theory
– Lexical mapping – domain ontologies
– Need richer metadata
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Research
Challenges: 4
Data quality, veracity and permanency
•detection of quality against metadata
parameters e.g. precision, accuracy;
•provenance;
•temporal recording;
•data curation across media and policy
evolution;
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Research
Challenges: 5
Trust, security and privacy
•policies declared, enforced and
monitored through restrictive metadata;
•policy reconciliation for interoperation;
•Legalistics
•Rights
•Responsibilities
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Research
Challenges: 6
Management of service levels and quality
of service
•policies declared, enforced and
monitored through restrictive metadata;
•service level negotiation (e.g. lower
price for lower performance);
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Research
Challenges: 7
Systems design, development, maintenance and
decommissioning
•based on strong separation of:
– services (processes),
– data, information and knowledge
•assuming self-(re-)composition, self-managing
and adjusting, self-maintaining properties ;
•assuming mobile code properties
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A final challenge?
• Is the von Neumann architecture still valid?
• Should we not optimise communications over other
priorities?
• Remember the transputer
• Do we need to write programs?
• Should we not just compose (dynamically – software
’robots’) from services as components (like other
branches of engineering)?
• Will social / legal changes ever catch up with
technology?
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STRUCTURE
Introduction – Who?
The Pervasiveness of ICT
A Short History of ICT
CLOUD Computing
Challenges
Conclusion
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Conclusion
Being ever optimistic, I believe these
challenges will be met.
But has some machine passed the Turing
test and nobody noticed?
(2012 was the year commemorating Alan
Turing birth centenary)
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Prof. Keith G Jeffery
CEng, CITP, FBCS, FGS, HFICS
Director, International IT Strategy
STFC Rutherford Appleton Laboratory
keith.jeffery@stfc.ac.uk
Acknowledgements to Lutz Schubert, HLRS, Stuttgart;
rapporteur EC CLOUDs expert Group
©STFC/Keith G Jeffery
The Challenges in ICT: Debunking the Hype
20130127
76