1. UMR 5205 Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012 Digital Ecosystems A (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

2. Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012 2 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

3. Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012 3 Digital Ecosystem Definition and Characteristics

4. Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012 4 Digital Ecosystems… A very versatile metaphor! IT industry, Economy, Business SOA, Software Engineering Networks and Information Systems For us: Distributed Collaborative Systems

5. Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012 5 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

6. Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012 6 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

7. Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012 7 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

8. Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012 8 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 state A: adapted state E: execute action

9. Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012 9 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

10. Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012 10 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)

11. Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012 11 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)

12. Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012 12 Autonomic Computing and Digital Ecosystems: towards collaborative systems Digital Ecosystems: Main Characteristics (cont’d)  Cooperation – Collective/Swarm Intelligence  cf. 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

13. Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012 13 Is the “Cyberspace” a (set of) Digital Ecosystem(s)? (can this concept helps us to understand our digital world?)

14. Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012 14 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...)

15. Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012 15 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)

16. Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012 16 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)

17. Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012 17 Congratulations! You are (at the center of) a multi-scale ubiquitous ego-centric digital ecosystem

18. Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012 18 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

19. Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012 19 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

20. Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012 20 OK, it is not a dream but… Is it a nightmare ?

21. Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012 21 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

22. Master Course, Lyon, January 2015 - Digital Ecosystems - 30/10/2012 22 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