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Industry Training: 04 Awareness Applications
This document summarizes several research projects related to autonomic and self-aware systems. It discusses proprioceptive systems like EPiCS which aim to develop self-aware and self-expressive computing systems. It also discusses swarm robotics projects like SYMBRION that develop robotic swarms capable of self-organization. Data management projects like SAPERE and RECOGNITION seek to develop self-aware techniques for acquiring and managing large amounts of data and content.
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Industry Training: 04 Awareness Applications
- 1. Awareness in Autonomic Systems Applications& Research Projects
- 2. Outline • Proprioceptive systems –EPiCS • Swarm robotics – SYMBRION – ASCENS – CoCoRo • Data management – SAPERE – RECOGNITION
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- 4. Proprioceptive Systems • Collectand 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. EPiCS www.epics-project.eu • Aims toderive 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. EPiCS Approach • Integratemultidisciplinary 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. EPiCS Videos • Howsix independent mobile devices synchronise to each other: http://vimeo.com/67205605 • CamSim – a distributed smart camera network simulator http://vimeo.com/70176909 For more: http://vimeo.com/channels/epics/
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- 10. Swarm Robotics • Imaginea 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. Swarm Robotics • Robotsare 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. SYMBRION www.symbrion.eu Symbiotic Evolutionary RobotOrganisms • 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, …)?
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- 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
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- 17. ASCENS www.ascens-ist.eu Autonomous service componentensembles • 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. 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
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- 21. CoCoRo cocoro.uni-graz.at 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
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- 23. CoCoRo Approach • Drawinspiration from nature to generate behavior: – Cognition generating algorithms: • Social insect trophallaxis • Social insect communication • Slime mold • ANN – Collective movement: • Bird movement • Fish school behavior
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- 26. Data management • Moreand 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. SAPERE www.sapere-project.eu Self-aware Pervasive ServiceEcosystems • 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. SAPERE Scenario • Pervasivecomputing – 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. SAPERE Architecture • Openproduction 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. SAPERE Infrastructure andapplications • 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
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- 32. RECOGNITION www.recognition-project.eu Relevance and Cognitionfor 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. 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. 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. RECOGNITION Approach Human AwarenessBehaviour • 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
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- 37. Acknowledgment The slides inthis presentation were produced with contributions from all participants of the Awareness Slides Factory.