toward open smart iot systems

Toward open smart IoT Systems Khalil Drira, LAASCNRS, Toulouse, - PowerPoint PPT Presentation

Toward open smart IoT Systems Khalil Drira, LAASCNRS, Toulouse, France Workshop Blockchain and IoT opportunities for the SMEs, Turino, April 18, 2018 The evolution of IoT Shipped items Plants action are tracked on a tap to water the

  1. Toward open smart IoT Systems Khalil Drira, LAAS‐CNRS, Toulouse, France Workshop Blockchain and IoT opportunities for the SMEs, Turino, April 18, 2018

  2. The evolution of IoT Shipped items Plants action are tracked on a tap to water the web. themselves. Track the world Let Things in real time talk to each others Communication Semantic interoperability reasoning Data interoperability Let Things become Take the control Bring the world on smart of the world line Alarm rings earlier Monitor and Develop Monument in case of traffic or control home web sites. bad weather. appliances. 2

  3. IoT: Definition By M. Sabzinejad Farash, et al. An efficient user authentication and key agreement scheme for heterogeneous wireless sensor network tailored for the Internet of Things environment . Ad Hoc Networks 36: 152‐176 (2016) The concept of Internet of Things is that every object in the Internet infrastructure is interconnected into a global dynamic expanding network . 3

  4. M2M: Definition ITEA2 Project USENET 2007‐2010 M2M (Machine-to-Machine) communication: The ability of machines (sensors, devices, servers, appliances, etc.) to communicate with each other without human interventions. 4

  5. IoT vs M2M: 3 visions M2M as an industrial environment • M2M: based on industrial protocols, closed solutions. IoT M2M • IoT: common usage applications, open solutions for mass. M2M as a subset of IoT IoT • M2M: connects devices, electronic sensors, RFID tags. M2M • IoT: connects general things, animals, peoples. We adopt this vision M2M as the kernel of IoT IoT • M2M: communication platform for IoT applications. M2M • IoT: is implemented by M2M technology. 5

  6. IoT/M2M main challenges M2M Communications A Systems Approach. David Boswarthick, Omar Elloumi, Olivier Hersen (Wiley April 2012) IoT Network Vertical Misalignment Fragmentation Power Security Management vendor‐specific Devices behavior solutions, no differs from Increasing Weakness in Inefficient interoperability, humans: collapse Complexity devices, battery life‐ semantic gap. of internet infra. privacy, fraud, cycles, lack of Large number cyber attacks. clean energy. of devices, Unmanageable, 6 high costs

  7. IoT/M2M main R&D directions Power Vertical Increasing Network Security Fragmentation Management Complexity Misalignment ‐ Common services Energy Saving & ‐ Autonomic Authentication, ‐Softwarized & & horizontal Harvesting: Management Authorization, Virtualized architectures Accounting Networks: SDN, Device‐level, Scalability & ‐ Semantic NFV, LPWAN virtualization Protocols‐level, Interoperability: (LoRa, NB‐IoT), ‐Dynamic Privacy Application/Proc ‐Sliced Networks Communication, deployment & ess/Mission‐level (5G) Data levels discovery ‐Data filtering ‐Model‐based design & mgt 7 7 ‐ Data Analytics & ML

  8. Standards landscape for IoT/M2M 143 organizations around the world are involved in IoT/M2M standardization according to the Global Standards Collaboration M2MTask Force. Buildings Consumer Energy IoT/M2M IoT/M2M Industrial HealthCare Retail Security Transportation 8

  9. IoT/M2M high level Reference Architecture Source:‐clusters/technologies/m2m Application Network M2M Device Domain Domain Domain 9

  10. Standards for Wide Area Networks Standards for Wide Area Networks (3GPP; LPWAN: LoRa, NB‐IOT) Target: protect networks against negative effects of M2M traffic (huge number of devices, non‐human new traffic …)‐clusters/technologies/m2m Network Domain 10

  11. Standards for IoT/M2M Area Networks Standards for Local Area Networks (ZigBee, Bluetooth, PLC, etc.) Target: foster use of LAN technology by supporting a diverse ecosystem of service providers and device manufacturers.‐clusters/technologies/m2m M2M Device Domain 11

  12. Standards for vertical industries Standards for vertical Industrial applications Target: enable interoperable, cost‐efficient Solutions. Application Domain 12‐clusters/technologies/m2m

  13. Standards for IoT/M2M service capabilities Standards for IoT/M2M Service Standards for IoT/M2M Service capabilities: capabilities: Target: end‐to end enablement across Target: end‐to end enablement across servers, gateways, and devices. servers, gateways, and devices. Standardized service interfaces. Standardized service interfaces.‐clusters/technologies/m2m Application Network M2M Device Domain Domain Domain 13

  14. The international standardization initiatives 1 st standard in Founded in 2011 2015, V2 2016 ETSI M2M WG founded in 2007 1 st standard in 2009 14

  15. oneM2M liaisons 15

  16. Enabling IoT/M2M cross‐domain interoperability Semantic gap breaks IoT horizontality Interoperability in IoT standards: 01010101 01010101 101 0101 • Resources description and discovery are 01010101 based on keywords (labels). • Applications use their own vocabulary (beforehand agreement between designers). • Limited interworking to some use cases Data Intelligence (based on specific formats). Description Keywords Taxonomy Towards a common vocabulary for IoT Ontology Binary Text • Managing devices with high degree of autonomy . • The need for semantic to describe specific domains. IoT Standards interoperability • Easily discover, interpret and share data is based on keywords between vertical applications. 16

  17. Semantic Web vs. Semantic IoT • Semantic Web : – Relatively static content . – e.g. Semantic Wikipedia (dbpedia), annotated pages, etc. • Semantic IoT : – Highly dynamic environment . – Data annotations can change frequently over time/space. – e.g. fleet tracking, patient monitoring, etc. 17

  18. Semantic IoT vs Semantic Web • Semantic IoT has more requirements and constraints than semantic web. • It requires continuous: • monitoring , • pre‐processing , • filtering , • aggregation , • annotation , and • integration . 18

  19. Semantic IoT goals • Effective data interoperability between devices and applications without any prior agreement. • Generic interworking and automated management of resources. • Semantic discovery and data querying . • Semantic matching and binding of devices and applications. • Semantic reasoning to infer new knowledge from a set of asserted facts. • Better monitoring and understanding of the surrounding environment . • Make smart decisions and dynamically adapt to 19 environment changes.

  20. Reference Ontologies for IoT Base ontology IOT‐lite oneM2M 2016 W3C, 2015 map to serve SSN IoT SAREF ontology W3C 2005 ESTI 2013,2015 Int. J. of Dist. Sys. &Techno, 4(3), 07‐09 2013 reuse IoT‐O Spitfire IEEE Comm. Mag, Comm. 20 FP7, 2010‐2013 Stand. Supplement 12/2015

  21. IoT‐O: LAAS’ ontology for IoT/M2M 21 IEEE Communications Magazine Volume: 53, Issue: 12, Dec 2015

  22. Mastering IoT complexity by semantic reasoning The autonomic management aproach Autonomic Manager [Kephart’03] Plan Analyze Knowledge Monitor Execute Managed Element Challenges for Autonomic Mgt in IoT: • Generic solutions for autonomic management of IoT systems . • Ontology for semantic reasoning : self‐ configuration of devices 22

  23. Standards and Reference platforms 23

  24. Main driving projects USENET: Ubiquitous M2M Service Networks 2007-2010 A2NETS: Autonomic services in M2M Networks 2010-2014 24

  25. Related Recent PhD thesis MM MK RH MB AK AH HA NK SK KF CE FA IL IB 25 DESCRIPTION Service Provisioning Phase DISCOVERY Typed Contributions by DEPLOYMENT MANAGEMENT Monitoring Analysis Decision Exec of reconf Validation Z/GG ADL/ GG/ PN GG OWL Contribution Objectives Design support UML OWL OWL /GG /GG Exec & dev support OS DDS WS ETP OWL GI GG Simulation GG structural Reconf type behavioral Tools Experiments Frameworks/ Architectures Models

  26. Related Recent outputs Starting Projects Starting Projects Ongoing&continu. Ongoing&continu. WS‐ IMAP Tenemo PIA/M2M DGA ADREAM SYNERGY Syst of Syst DIAMOND Theories & Methods IDEX/CLOU RTRA/CYPHY CIFREs Usenet AMIC‐TCP Multi‐scale S D Models Grants A2NETS MOSAIC ROSACE IMAGINE UML/SysML Transversal Axis Transversal Axis Semantic & Ontologies E-health Graphs & Adaptive G. Grammars Connected Vehicles Protocols & Services Smart Metering Deployment & Smart Grids Dynamic Planning Architectures Dynamic Manufacturing Context Networks Distributed Monitoring Algorithms and Emergency Management Systems & Analysis Applications Learning PF for FoF Learning PF for FoF Tools & FW Tools & FW GMTE OM2M V1.0 OM2M V0.8 & Living Labs & Living Labs FrameSelf FACUS Experimental Platforms Experimental Platforms

  27. Enabling IoT cross‐domain interoperability OM2M: horizontal IoT service platform ( ECLIPSE Open Source project: 27

  28. Deployments, Experiments, Hackathons Smart building @ LAAS Eclipse OM2M V1 V2 Startup hosted by IoT Valley Toulouse Hackaton @UT DALLAS 28


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