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UMR 5205
Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012
Digital EcosystemsA (Rather) New Vision of IT
Lionel Brunie
National Institute of Applied Sciences (INSA)LIRIS Laboratory/DRIM Team – UMR CNRS 5205
Lyon, France
http://liris.cnrs.fr/lionel.brunie
Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012
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Contents of the Course
Definition and Characteristics Distributed Systems Models Autonomic Systems Digital Ecosystems
Cyberspace and Digital Ecosystem(s) Use case – Emerging Applications Multi-scale Ego-centric Ubiquitous Digital Ecosystem Security and Privacy Issues
Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012
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Digital Ecosystem
Definition and Characteristics
Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012
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Digital Ecosystems…A very versatile metaphor!
IT industry, Economy, Business
SOA, Software Engineering
Networks and Information Systems
For us: Distributed Collaborative Systems
Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012
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Basic Models of Distributed Systems
Client-Server (typically, the Web)
Peer-to-Peer (typically Bittorent and file sharing systems)
Grid (typically, the CERN LCG)
Mobile agents
Variants → Course on large scale computing
Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012
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The New Frontier
Traditional models fail to model and implement highly dynamic loosely supervised distributed systems
Alternative models autonomic computing → focus on autonomy and coordination cloud computing → re-centralize everything pervasive/ubiquitous computing → focus on user context Internet of Things → focus on interoperability digital ecosystems → an holistic vision
Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012
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Autonomic Computing and Digital Ecosystems:
towards collaborative systems
Autonomic Computing [Horn, 2001; Parashar and Hariri, 2005]
analogy with the nervous system – notion of equilibrium
observation: emerging systems and applications are dynamic
survivability of the system the system can adapt to environment changes (incl. attacks, faults, disruptions…)
basic operation loop of an autonomic system: Monitor-Decide-Adapt
sense / monitor the environment (context discovery), and analyze the context
plan a knowledge-based adaptation of the system (decision making)execute the change
context- and self-awareness
Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012
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Architecture of an autonomic agent
From Parashar and Hariri, 2005
KE: Knowledge Engine
M&A: Monitoring and Analysis
Cardinals: performance, configuration, protection, security
L/G: local and global control loops
S: stable stateA: adapted stateE: execute action
Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012
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Autonomic Computing and Digital Ecosystems:
towards collaborative systems
Autonomic Computing [Horn, 2001; Parashar and Hariri, 2005] (cont’d): characteristics/properties of a generic autonomic system
Self Configuring
Self Optimizing
Self-Healing
Self Protecting
Context Aware
Open
Anticipatory
Proactive
Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012
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Autonomic Computing and Digital Ecosystems:
towards collaborative systems
Digital Ecosystems (Distributed Collaborative Systems) [Boley et al., 2007; Damiani and his group @ Milan]
“A digital ecosystem can be defined as an open, loosely
coupled, domain clustered, demand-driven, self-organizing
agent environment, where each agent of each species is
proactive and responsive regarding its own benefit/profit but
is also responsible to its system.” (Boley and Chang, 2007)
Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012
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Autonomic Computing and Digital Ecosystems:
towards collaborative systems
Digital Ecosystems: Main Characteristics Loose coupling - Personal Engagement
Equilibrium – Interdependence - Balance
Local Interactions Global Behavior
Self-organization – Autonomy - No Central or Distributed
Control
Adaptation to the Environment – Dynamicity – Evolutionary
System
Collective (Swarm) Intelligence – Structured Relationship -
Responsibility
Openness - Multiplicity of Ecosystems (cf. human social life)
Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012
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Autonomic Computing and Digital Ecosystems:
towards collaborative systems
Digital Ecosystems: Main Characteristics (cont’d)
Cooperation – Collective/Swarm Intelligencecf. bees, ants, dolphins…swarm is a set of agents that can interact and that share a common
interest collective problem solving
Communication System Semantics
DE => need of shared explicit formal semantics (formal languages)
Link with some characteristics of the semantic Web
A new way of designing/thinking distributed systems and applications
Related to autonomic computing
Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012
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Is the “Cyberspace” a (set of) Digital Ecosystem(s)?
(can this concept helps us to understand our digital world?)
Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012
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Dream your (future) life in an (emerging) digital world
You are always connected to the cyberspace, you can access your data everywhere
No more money, no more theatre tickets, no more boarding card, no more printed newspaper, no more books, no more music CDs (but still administrative papers, don’t dream too much)
Your car (sometimes) drives for you
You live in a (fairly? rather?) smart home
You participate in multiple digital social networks (incl. online games)
Your browser is proactive
There are digital services everywhere – The city is “smart”
ICT is at last pervasive: digital services adapt their behavior to you and your environment (e.g., location, preferences, profile, activity...)
Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012
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Is it a Dream or the Reality ?
You are always connected to the cyber space, you can access your data everywhere
→ mobile Internet (3G/4G), clouds (reality)
No more money, no more theatre tickets, no more boarding card, no more printed newspaper, no more books, no more music CDs
→ smartphone, NFC, RFID tags (reality)
Your car (sometimes) drives for you
→ Intelligent Transportation Systems (ITS) (partial –
active development)
You live in a (a fairly? Rather?) smart home
→ Internet of Things (IoT) @home (not yet a reality)
Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012
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Is it a Dream or the Reality ?
You participate in multiple digital social networks (incl. online games) → It is not the future, but the everyday life (reality)
Your browser is proactive → Recommendation systems (more and more true –
still active development (e.g., FP7 EEXCESS
project)
There are digital services everywhere → IoT, O2O, M2M, H2M (more and more true in
manufacturing, not true for citizens)
ICT is at last pervasive: digital services adapt their behavior to you and your environment (e.g., location)
→ context-aware services, location-based service, ambient intelligence, ambient social networks… (more and more true – still active
development)
Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012
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Congratulations!
You are (at the center of) a
multi-scale ubiquitous ego-centric digital ecosystem
Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012
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Multi-scale Ego-centric Ubiquitous Digital Ecosystem
Ego-centric focus on the user’s interactions with her/his environment(s) personalization – context-awareness
Ubiquitous mobility simultaneous interactions with multiple ecosystems
Multi-scale comprise entities (typically, services) of totally different nature, origin
and operational characteristics from an embedded “thing” to a public cloud integration of data, information, knowledge from all sources huge mass of information
Digital Ecosystem see above
Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012
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Back to the “Visions” (Part 1 of the Course)
Seamless “weaved into the fabric of everyday life”
“Graceful integration”
Transparency of the “cyber infrastructure” (“vanish in the background”)
User-centric
Conclusion: hard to imagine in 1991 – realistic as an objective for the next decade
Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012
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OK, it is not a dreambut…
Is it a nightmare ?
Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012
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Multi-scale Ego-centric Ubiquitous Digital Ecosystem:Security and Privacy Issues
You are the hub and the source of information (supposed to be) sensitive personal information
Data exchanges, dissemination of information between multiple ecosystems with various security and privacy characteristics
un-alignment of security/privacy policies sensitive information leakage
You do not control, worse do not actually know, the environment Uncertainty Dynamicity Unpredictability Absence of trust, Anonymity
Big Brother can watch you, now! Your everyday life is seamlessly weaved into the cyberspace fabric: you are traced The cyberspace does not forget: traces cannot be deleted The storage and processing capacities are almost unlimited: your traces are/can be mined
See course on these issues
Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012
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Conclusion
New technologies enable / need / argue for new models, new designs
Whatever the model, some basic features Autonomy Collaboration User-Centricity Integration Context-Awareness Mobility
Digital ecosystems provide a holistic vision of emerging digital environments
Some still largely open issues, esp. regarding interoperability The cyberspace as a digital ecosystem is the Babel Tower
A fantastic, however in some way dreadful set of opportunities for new applications