Industry Training: 04 Awareness Applications


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Industry Training: 04 Awareness Applications

  1. 1. Awareness in Autonomic Systems Applications & Research Projects
  2. 2. Outline • Proprioceptive systems – EPiCS • Swarm robotics – SYMBRION – ASCENS – CoCoRo • Data management – SAPERE – RECOGNITION
  4. 4. Proprioceptive Systems • Collect and maintain information about their state and progress • Enable self-awareness by reasoning about their behavior • Enable self-expression by effectively and autonomously adapting their behavior to changing conditions
  5. 5. EPiCS • Aims to derive novel design and operation methods and tools from the proprioception, self-awareness and self-expression principles of studied systems • Intends to integrate multidisciplinary research from several areas: – concepts and foundations for self-aware and self- expressive systems – hardware/software platform technologies for autonomic compute nodes – self-aware network architectures and middleware layers • Develops new hardware and software platforms
  6. 6. EPiCS Approach • Integrate multidisciplinary research from several areas: – concepts and foundations for self-aware and self- expressive systems – hardware/software platform technologies for autonomic compute nodes – self-aware network architectures and middleware layers • Foundational and technological research validated by the requirements of three challenging application domains: – heterogeneous compute clusters for financial modelling – distributed smart cameras for person detection and tracking – hypermusic on an interactive mobile media system
  7. 7. EPiCS Videos • How six independent mobile devices synchronise to each other: • CamSim – a distributed smart camera network simulator For more:
  8. 8. EPiCS Consortium
  9. 9. SWARM ROBOTICS Applications
  10. 10. Swarm Robotics • Imagine a swarm of robots that need to solve a certain task, e.g. – Cleaning a devastated area – Exploring Mars • In difficult environments with holes, hills, obstacles, . . . the robots have to cooperate – Transport an object together – Form organisms to cope better with environment
  11. 11. Swarm Robotics • Robots are aware of the task they are supposed to perform and monitor their performance in the environment • Robots should be able to adapt to maximize their performance • Adaptations take place on an individual level as well as on a collective level: – Individuals adjust their behavior – Collective behavior emerges (e.g. organisms are formed by multiple robots)
  12. 12. SYMBRION Symbiotic Evolutionary Robot Organisms • Hundreds of small cubic robots are built and deployed in an environment • Robots sense each other and the environment and are capable of aggregating into “multi-cellular” organisms • Aggregation and disaggregation is self-driven, depending on the circumstances: different environments, different tasks • Questions addressed: – Can we build such robots and program the basic behaviors needed for appropriate (dis)aggregation? – Can we provide adaptive mechanisms that enable newly “born” organisms learn to operate (sense, move, act, …)?
  13. 13. SYMBRION Scenario
  14. 14. SYMBRION Approach
  15. 15. SYMBRION Current Results • Different controllers have been developed for robots • Evolutionary approaches are able to adapt the controllers based upon fitness • Different organisms are formed as required by the environment • Some initial versions of hardware have been developed and are currently being deployed
  16. 16. SYMBRION Comsoritum
  17. 17. ASCENS Autonomous service component ensembles • Self-aware, self-adaptive, and self-expressive autonomous components • Components run in an environment and are called ensembles • Systems are very difficult to develop, deploy, and manage • Goal of ASCENS: – Develop an approach that combines traditional SE approaches based on formal methods with the flexibility of resources promised by autonomic, adaptive, and self-aware systems • Case studies: – Robotics, cloud computing, and energy saving e-mobility
  18. 18. Ensembles • Autonomic systems: typically distributed computing systems whose components act autonomously and can adapt to environment changes. • Ensembles have the following characteristics: – Large numbers of nodes – Heterogeneous – Operating in open and non- deterministic environments – Complex interactions between nodes and with humans or other systems – Dynamic adaptation to changes in the environment
  19. 19. ASCENS Approach
  20. 20. ASCENS Consortium
  21. 21. CoCoRo Collective Cognitive Robotics • Aims at creating an autonomous swarm of interacting, cognitive underwater vehicles • Tasks to be performed by the swarm: – Ecological monitoring – Searching – Maintaining – Exploring – Harvesting resources
  22. 22. CoCoRo Scenario
  23. 23. CoCoRo Approach • Draw inspiration from nature to generate behavior: – Cognition generating algorithms: • Social insect trophallaxis • Social insect communication • Slime mold • ANN – Collective movement: • Bird movement • Fish school behavior
  24. 24. CoCoRo Consortium
  25. 25. DATA MANAGEMENT Applications
  26. 26. Data management • More and more content is being generated • Content needs to be effectively managed in order to avoid user form being swamped • Task is to: – Manage existing content – Acquire new content
  27. 27. SAPERE Self-aware Pervasive Service Ecosystems • Computers for handling data and providing services are integrated into an “ecosystem” • System is extended with – methods for data and situation identification – decentralized algorithms for spatial self-organization, self- composition, and self-management • Thus, we obtain automated deployment and execution of services and for the management of contextual data items
  28. 28. SAPERE Scenario • Pervasive computing – Sensor rich and always connected smart phones – Sensor networks and information tags – Localization and activity recognition – Internet of things and the real‐time Web • Innovative pervasive services arising – Situation‐aware adaptation – Interactive reality – Pervasive collective intelligence and pervasive participation • Open co‐production scenario, very dynamic, diverse needs and diverse services, continuously evolving
  29. 29. SAPERE Architecture • Open production model • Smooth data/services distinction – live semantic annotations (LSA) • Interactions – Sorts of bio‐chemical reactions among components – In a spatial substrate • Eco‐laws – Rule all interactions – Discovery + orchestration seamlessly merged • Built over a pervasive network world
  30. 30. SAPERE Infrastructure and applications • Infrastructure – A very lightweight infrastructure – Ruling all interactions (from discovery to data exchange and synchronization) by embedding the concept of eco‐laws – To most extent, acting as a recommendation and planning engine – Possibly inspired by tuple space coordination models – Yet made it more “fluid” and suitable for a pervasive computing continuum substrate not a network but a continuum of tuple spaces • Applications – The “Ecosystem of Display” as a general and impactful testbed – To put at work and demonstrate the SAPERE findings – Active and dynamic information sharing in urban scenarios – Active participation of citizens to the working of the urban infrastructure
  31. 31. SAPERE Consortium
  32. 32. RECOGNITION Relevance and Cognition for Self‐Awareness in a Content‐Centric Internet • Project draws inspiration from human cognitive processes to achieve self-awareness • Try to replicate core cognitive processes in computer systems: – e.g. inference, beliefs, similarity, and trust – embed them in ICT • Application domain: internet content – Manage and acquire content in an effective manner by means of self-aware computing systems
  33. 33. RECOGNITION Motivation Technological Trends • Participatory generation of content – Prosumers, diversity, expanding edges – Long tail, swamping, scale! • Content in the environment – Linkage of the physical and virtual worlds – Embedding content and knowledge • Acquiring knowledge through social mechanisms – Blogging, social networking, recommendation, RSS feeds… • How content reaches users will continue to change…
  34. 34. Supporting technological trends • Intention: Paradigm to support ICT functions – Enabling content centricity • Better fitting of users to content and vice-versa – Synchronize content with human activity and needs • Place, time, situation, relevance, context, social search – Autonomic management • Of content, its acquisition and resource utilization
  35. 35. RECOGNITION Approach Human Awareness Behaviour • Capture & exploit key behaviours of the most intelligent living species – Human capability is phenomenal in navigating complex & diverse stimuli – Filter & suppress information in “noisy” situations with ambient stimuli – Extract knowledge in presence of uncertainty – Exercise rapid value judgment for prioritisation – Engage a and multi‐scale social context multi learning
  36. 36. RECOGNITION Consortium
  37. 37. Acknowledgment The slides in this presentation were produced with contributions from all participants of the Awareness Slides Factory.