Download - Industry Training: 04 Awareness Applications
Awareness in Autonomic Systems
Applications &
Research Projects
Outline
• Proprioceptive systems– EPiCS
• Swarm robotics– SYMBRION
– ASCENS
– CoCoRo
• Data management– SAPERE
– RECOGNITION
PROPRIOCEPTIVE SYSTEMS
Applications
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
EPiCSwww.epics-project.eu
• 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
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
EPiCS Videos
• How six independent mobile devices synchronise to each other:http://vimeo.com/67205605
• CamSim – a distributed smart camera network simulatorhttp://vimeo.com/70176909
For more: http://vimeo.com/channels/epics/
EPiCS Consortium
SWARM ROBOTICS
Applications
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
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)
SYMBRIONwww.symbrion.eu
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, …)?
SYMBRION Scenario
http://www.youtube.com/watch?v=SkvpEfAPXn4
SYMBRION Approach
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
SYMBRION Comsoritum
ASCENS www.ascens-ist.eu
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
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 betweennodes and with humans or other systems
– Dynamic adaptation to changes in the environment
ASCENS Approach
ASCENS Consortium
CoCoRococoro.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
CoCoRo Scenario
http://www.youtube.com/watch?v=OStLml7pHZY
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
CoCoRo Consortium
DATA MANAGEMENT
Applications
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
SAPEREwww.sapere-project.eu
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
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
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
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
SAPERE Consortium
RECOGNITIONwww.recognition-project.eu
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
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…
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
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
RECOGNITION Consortium
Acknowledgment
The slides in this presentation were produced with contributions from all participants of the Awareness Slides Factory.