Internet Connected Objects forInternet Connected Objects for Reconfigurable Eco‐systems
3rd ETSI M2M Workshop23‐25 October 2012Mandelieu, France
Outline
MotivationScope and conceptsTechnical issuesTechnical approachApplicabilityiCore and M2M communicationProject detailsDemonstration
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iCore motivationThe “7 trillion devices for 7 billion people” paradigm, yields that the handling of the amount of objects that will be part of the Internet of Things (IoT) requires suitable architecture andInternet of Things (IoT) requires suitable architecture and technological foundations
Internet‐connected objects, sensors and other types of smart devices need a suitable communication infrastructure
RealitalRealital
Yes Maybe
ReDigital
nsingGPS
Yes Maybe
ReDigital
nsingGPS
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SensingGPSSensingGPS
iCore scope and concept
Open cognitive framework for the IoT addressing 3 levels
Users/stakeholdersperspectivesp p
Composite Virtual Objects (CVOs):
Virtual Objects (VOs):
Objects (CVOs):Cognitive mash‐ups of multiple VOs
Virtual Objects (VOs):Virtual representations of real‐world objects
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iCore technical issues
Interoperability through VO/CVOs
Seamless and interoperable connectivityh t d i / t
Reliability Novel servicesReliability Novel servicesReliability Novel servicesReliability Novel services
among heterogeneous devices/systems
Abstraction of complexity
Reusability of objects outside the scope inReusability of objects outside the scope in which they were originally deployed
Reliability and availability of services
Application domain or use case agnosticcognitive (self) management
B i i t ti f th i f lti lBusiness integration of the views of multiple stakeholders in the composition of services iCore
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iCore boundaries
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Note: the implementation of iCore mechanisms will require the use of technologies and concepts that are not investigated as part of iCore
iCore technical approachThe iCore proposed solution is a cognitive framework for the IoT comprising three levels of functionality, reusable for various and diverse applications
Virtual Objects (VOs): virtual representations of devices or digital objects j ( ) p g j(e.g. sensors, actuators, smartphones, music players, etc) associated to everyday objects or people (e.g. a table, a room, an elderly, etc) that hide the underlying technological heterogeneity.
Composite Virtual Objects (CVOs): mash‐ups of semantically interoperable VOs, delivering services in accordance with the user/stakeholder requirements.
Users / Stakeholders functional blocks: convey the respective requirements and are capable of detecting users/stakeholders behaviour, inferring intentions and eventually acting on behalf of users/stakeholders. Capabilities for governing these entities are also included.
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iCore technical approachCognitive entities at all levels provide the means for self‐management (configuration, healing, optimization, protection) and learning
capable of perceiving and reasoning on their context (e.g., based on event filtering, pattern recognition, machine learning), and conducting associated knowledge‐based decision‐making.
Essential security functionality, spans all levels of the frameworkownership and privacy of datacontrolling actual access to objects
Integration and validation through application in various use cases, such as smart home (ambient assisted living), smart office (easy meeting), smart city (smart transportation), smart business (supply chain management).
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iCore technical approach
Architecture reference model
Alignment with EU IoT activities,Overall cognitive process optimization,iCore security Architecture reference model
Alignment with EU IoT activities,Overall cognitive process optimization,iCore security
Context awareness,cognitive processtechnologies
Usercontextregistries
Service logicfactory
User level cognitiveprocesses
Context awareness,cognitive processtechnologies
Usercontextregistries
Service logicfactory
User level cognitiveprocesses
Complex event prosessing, servicecomposition technologiesCognitive
management and controlframework CVO CVO level cognitive
Complex event prosessing, servicecomposition technologiesCognitive
management and controlframework CVO CVO level cognitive
User and application fabric
Semantic technologiesfor maintaining the handle to Virtual Objects
CVOCVOC O
registriesCVO level cognitive
processes
Semantic technologiesfor maintaining the handle to Virtual Objects
CVOCVOC O
registriesCVO level cognitive
processes
CVO fabric
j
VOVO
VO
VO VO registries
VO level cognitiveprocesses
j
VOVO
VO
VO VO registries
VO level cognitiveprocesses
VO fabric
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iCore technical approach
User interacts with the The Service logic derives a environment (e.g. issues a command/enters a room) and triggers the user level
mechanisms.
The Service logic factory acquires additional context and profile information .
set of application requirements that are issued towards the CVO management fabric
Development, installation and automatic deployment of
applications
The CVO factory acquires information on available VOs and CVOs (discovery)
A new CVO is composed, which deploys,
activates/instantiates and configures necessary
components (VOs and CVOs)
Application
VO Registry
VO Registry
VO Registry
CVO Registry
CVO Registry
CVO Registry
Installation , registration and automatic configuration of
virtual objects
Installation , registration and automatic configuration of
CVOs
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iCore applicabilityThe iCore framework must be defined as independent of application domains and use casesTo show the applicability of framework four Future Internet application pp y ppareas have been selected for demonstration
Use Case How Before AfterSmart home (ambient assisted living)
Virtual objects to interact with each other in a cognitive way. Reusability of virtual objects will enable
The patient lifestyle is not that good. Will be measured.
Better monitoring of patients
Use Case How Before AfterSmart home (ambient assisted living)
Virtual objects to interact with each other in a cognitive way. Reusability of virtual objects will enable
The patient lifestyle is not that good. Will be measured.
Better monitoring of patients
jcollaboration across sectors, which will reduce the costs of services.
Smart office (meeting support/ easy meeting)
Seamless and faster configuration of user’s
Unproductive schedules, worst
Increased productivity
jcollaboration across sectors, which will reduce the costs of services.
Smart office (meeting support/ easy meeting)
Seamless and faster configuration of user’s
Unproductive schedules, worst
Increased productivitysupport/ easy meeting) g
wireless devices allowing them to connect to network they are “visiting”
,productivity will be measured
Smart city (transportation)
Personalization of car feature based on user preferences and recorded profile
Low performance and time consuming transportation will be measured
Better and increased performance in the itineraries
support/ easy meeting) gwireless devices allowing them to connect to network they are “visiting”
,productivity will be measured
Smart city (transportation)
Personalization of car feature based on user preferences and recorded profile
Low performance and time consuming transportation will be measured
Better and increased performance in the itineraries
Smart business (supply chain management)
Through the reusability of virtual object, various stakeholders collaborate with each other and reduce the costs of the services and increase efficiency of the entire supply chain
Effectiveness of the supply chain was not good enough. Will be measured
Improved supply chain management and performance
Smart business (supply chain management)
Through the reusability of virtual object, various stakeholders collaborate with each other and reduce the costs of the services and increase efficiency of the entire supply chain
Effectiveness of the supply chain was not good enough. Will be measured
Improved supply chain management and performance
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entire supply chainentire supply chain
iCore and M2M communication iCore can enable the seamless and interoperable connectivity amongst heterogeneousM2M devices and systemsiCore through the VOs can offer the required by any M2M system abstraction of the underlying network structure and complexityiCore can help confronting M2M scalability issues in terms of number of Connected Objects through the reusability of objects outside their initial context/domain by many different types of stakeholderscontext/domain by many different types of stakeholdersiCore cognitive management framework can/may contribute to M2M management requirements (fault management, configuration management)iCore will address security and privacy issues and this know how may beiCore will address security and privacy issues and this know‐how may be exploited by M2M systemsiCore can/may contribute to M2M use cases
iCore Smart home (ambient assisted living) ‐> M2M eHealth use caseiCore Smart home (ambient assisted living) > M2M eHealth use caseiCore Smart city (transportation) ‐> M2M automotive and city automation use caseiCore Smart home and Smart office ‐> M2M connected consumer use case
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iCore work packagesh k l f k k ( )The work plan consists of 9 Work Packages (WP)
Duration: 36 months (10/2011 – 09/2014)13
iCore ConsortiumThe consortium consists of 21The consortium consists of 21 partners
8 ICT manufacturers, telecom operators, software vendors, system integrators, software service/end users, namely Siemens, Thales, Alcatel‐Lucent, Fiat, Atos Origin, Software AG, gNTT and Telecom Italia.5 SMEs are part of the consortium: Ambient systems, ZIGPOS Innotec21 SSS andZIGPOS, Innotec21, SSS and M3S.4 internationally recognized research centres, namely Create net EC JRC TNO VTTCreate‐net, EC JRC, TNO, VTT.4 universities: University of Surrey, University of Piraeus, Technical University of Delft d U i i f G
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and University of Genova.
iCore demonstrationBasic story line:
Sara is an elderly lady living at home. She has opted for an assisted living service. All necessary equipment is installed in Sara's home.service. All necessary equipment is installed in Sara s home.At the corresponding medical center a member of staff provides requirements through an appropriate interface. Cognitive functionalities take into account provided requests and policiesCognitive functionalities take into account provided requests and policies and dynamically create a CVO as a mash‐up all of necessary objects to fulfill the requested application. The derived solution (CVO composition) is recorded so that the next timeThe derived solution (CVO composition) is recorded so that the next time a similar request is issued by the medical center knowledge on past CVO instantiations enables the direct deployment of the known CVO.
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iCore demonstration
Implementation Overview
16High Level Architecture Overview
iCore demonstration
VO RegistryProvides information on available VOs.I l t d RDF G h D t b ith thImplemented as RDF Graph Database with the use of the Sesame framework. Allows SPARQL queries.Accessible via RESTful Web Service (WS).
VO Registry Graphical User Interface
VO (Registry ) Information
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iCore demonstration
CVO RegistryInformation on successfully deployed CVOs/applications
Request parameters (functions, policies) Situation parameters (time and geographical area of the request available VOs)
CVO compositionarea of the request, available VOs)
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iCore demonstration
Situation and Request Acquisition and Matching Identifies the closest reference situation and corresponding request for the newly acquired situation and request.request for the newly acquired situation and request.Comparison of incoming application request x to recorded ones yn
Both request and situation parametersConsideration of approximate functions (e.g. audio and video capture)pp ( g p )Selection of the the most similar yi (satisfaction‐rate based similarity metric S)with similarity S(x, yi):
yesRe‐use the CVO created
S(x,yi) > Sthresh?
no
yes for the past application request yi
Overhead at early stages of the
ReusabilityP f G istages of the
systemPerformance GainContext Awareness
Trigger Decision Making process
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gge ec s o a g p ocess
iCore demonstration
Situation and Request Acquisition and Matching
time of request
Area of interest and corresponding available VOs
Request parameters: functions & policies
Situation and Request Acquisition and Matching – User Interface
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iCore demonstration
Situation and Request Acquisition and MatchingDetermination of suitability of previously created CVOs through correlations between VOs functions and requestedthrough correlations between VOs functions and requested functions in a matrix:
“image” can be fully satisfied by “video”, but “video” can only partially be satisfied by “image”
Machine learning:train the matrix to reflect new correlations online
image video ...
i 1 1image 1 1 ...
video 0.5 1 ...
: : : ...
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: : : ...
iCore demonstrationkDecision Making
Given a set of requested functionsa set of requested functionsUser/stakeholder policiesa set of available VOs and the set of functions offered by each VOby each VOa set of utility parameters for each VO functiona set of cost parameters for each VO function
f h f la set of weights for utility parametersa set of weights for costs parametersthe functions correlation matrix for functions
find the optimal mash‐up of VOs to fulfill the requested functions.
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iCore demonstrationDecision MakingDecision Making
Process1. Acquisition of situation and request parameters from
Sit ti d R t A i iti d M t hiSituation and Request Acquisition and Matching2. Retrieval of records of available VOs from the VO registry3. Decision for the optimal CVO composition is based on
the maximisation of an objective function, which takes into account all aforementioned information
All interactions utilize RESTful WSILOG CPLEX 12.2 is used for the optimization process 1
2
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iCore demonstrationdInstantiated CVO
Mash‐up of various available VOs created and instantiated as a result of the cognitive functionalities
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Internet Connected Objects forInternet Connected Objects for Reconfigurable Eco‐systems
iCore Website http://www iot icore eu/iCore Website, http://www.iot‐icore.eu/
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