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Managing Massive data of the IoT through cooperative semantic nodes
Managing Massive data of the IoT through cooperative semantic nodes
Managing Massive data of the IoT through cooperative semantic nodes
Managing Massive data of the IoT through cooperative semantic nodes
Managing Massive data of the IoT through cooperative semantic nodes
Managing Massive data of the IoT through cooperative semantic nodes
Managing Massive data of the IoT through cooperative semantic nodes
Managing Massive data of the IoT through cooperative semantic nodes
Managing Massive data of the IoT through cooperative semantic nodes
Managing Massive data of the IoT through cooperative semantic nodes
Managing Massive data of the IoT through cooperative semantic nodes
Managing Massive data of the IoT through cooperative semantic nodes
Managing Massive data of the IoT through cooperative semantic nodes
Managing Massive data of the IoT through cooperative semantic nodes
Managing Massive data of the IoT through cooperative semantic nodes
Managing Massive data of the IoT through cooperative semantic nodes
Managing Massive data of the IoT through cooperative semantic nodes
Managing Massive data of the IoT through cooperative semantic nodes
Managing Massive data of the IoT through cooperative semantic nodes
Managing Massive data of the IoT through cooperative semantic nodes
Managing Massive data of the IoT through cooperative semantic nodes
Managing Massive data of the IoT through cooperative semantic nodes
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Managing Massive data of the IoT through cooperative semantic nodes

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The presentation of the talk I have given at the IEEE ICSC 2012 conference.

The presentation of the talk I have given at the IEEE ICSC 2012 conference.

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  • 1. Managing Massive data of the IoT through cooperativesemantic nodesBenoit Christophe – Bell Labs Researchbenoit.christophe@alcatel-lucent.com 1 COPYRIGHT © 2011 ALCATEL-LUCENT. ALL RIGHTS RESERVED.
  • 2. The Internet of ThingsVision and definitions• Extending the Internet to physical entities of interest (EoI)• A step towards a better automation of user’s tasks (i.e. making user’s life easier) Entities of Interest• Three layers cake (my own perception) Access, Observe, - EoIs are the entities being of interest for Measure, Actuate some users Connected devices (RFID, sensors, actuators, smart phones) - Devices (sensors, actuators, etc.) measure, trigger or actuate on EoIs - Services and applications combine Combine & Digest devices to offer meaningful information Services & Applications to a user about the EoIs it is interested in Goal: to ease the process of associating EoIs and devices 2 COPYRIGHT © 2011 ALCATEL-LUCENT. ALL RIGHTS RESERVED.
  • 3. The Internet of ThingsHard facts and forecasts Source: http://gigaom.com/cloud/internet-of-things-will-have-24-billion-devices-by-2020/connecteddevices2020/ 3 COPYRIGHT © 2011 ALCATEL-LUCENT. ALL RIGHTS RESERVED.
  • 4. The Internet of ThingsHeterogeneous information produced on a 24/7 basis Source: http://www.rfglobalnet.com/doc.mvc/The-Internet-Of-Things-Connecting-Everything-0001 Image: http://embedded-computing.com/current-trends-cyber-attacks-mobile-embedded-systems 4 COPYRIGHT © 2011 ALCATEL-LUCENT. ALL RIGHTS RESERVED.
  • 5. The Internet of ThingsRise of Web platforms for connected devices• Plethora of services or data offered through the Web• The “things” become exposed as services on the Web 5 COPYRIGHT © 2011 ALCATEL-LUCENT. ALL RIGHTS RESERVED.
  • 6. The Internet of ThingsAssociated problems• How to find relevant information about an EoI within this giant lake of generated unstructured data?• How to combine devices or services to automate realization of complex tasks?• Assuming the above, how do we ensure scalability of our search processes? 6 COPYRIGHT © 2011 ALCATEL-LUCENT. ALL RIGHTS RESERVED.
  • 7. The Internet of ThingsState of affairs• Lassila [1] proposed to use Semantic Web technologies to improve interoperability between devices in order to better automate user’s tasks. - Many researches [2,3,4,5] in this field tried to describe “things” or “services” semantically, adopting this vision - Many European projects (e.g. Sensei, IoT-A) try defining ontological models to represent their resources - W3C Semantic Sensors Network Incubator Group (SSN-XG) has developed an ontology for describing sensors• However, adding semantic and reasoning process decreases scalability. Even worst, considering an indoor environment with IoT resources prone to high mobility makes it hard (impossible?) to maintain a KB in a reasonable time 7 COPYRIGHT © 2011 ALCATEL-LUCENT. ALL RIGHTS RESERVED.
  • 8. The Internet of ThingsWhat we believe regarding IoT in indoor environments• Beyond using Semantic Web to describe IoT resources: - Consider location as an important criteria when searching for IoT resources - E.g. when searching for a printer, you probably want to find one near you - Design a distributed network of nodes - Where each node is bound to one constituent of a Building (a room, a corridor, etc.) - Where each node knows its neighborhood - Where each node contains few but meaningful semantic descriptions of resources - I.e. a node is bound to a room of a building. Such node contains only the semantic descriptions of the IoT resources that are in or in the vicinity of the room - Where each node has local reasoning capabilities: e.g. searching its KB, sharing descriptions of its IoT resources with its neighbors, and forwarding incoming requests to its neighbors - E.g. description of a phone in node “room A” is sent to node “room B” if “room A” and “room B” are close to each other - E.g.2. an incoming request that reaches node “room A” is forwarded to node “room B” in case of no answer 8 COPYRIGHT © 2011 ALCATEL-LUCENT. ALL RIGHTS RESERVED.
  • 9. How do we realize our proposalModeling indoor environment• Create an ontology to model what compose a Building (Floor, Corridor, Room, etc.)• Create the properties allowing a constituent of a Building to describe how it is linked to another constituent (e.g. Room A givesAccessTo RoomB) 9 COPYRIGHT © 2011 ALCATEL-LUCENT. ALL RIGHTS RESERVED.
  • 10. How do we realize our proposalA federated [6] network of cooperating semantic nodes• Semantic nodes know their neighborhood, store and exchange descriptions and forward incoming requests Top node of the federation (in-degree = 0) N1 Associated to a Place such as « University Building A » « 2nd Floor » N2 Non source node (in-degree = 1) N3 N4 N5 « CS lab. » « Chemistry lab. » N6 N7 N8 Management link (e.g. N1 manages N2) First cascading process: each node sends its location to its « manager ». Such data implements the location model and the Place concept. Second cascading process: top node sends complete location to all nodes 10 COPYRIGHT © 2011 ALCATEL-LUCENT. ALL RIGHTS RESERVED.
  • 11. How do we realize our proposalSharing knowledge – use of SWRL• Use SWRL to exchange semantic descriptions of IoT resources between nodes - SWRL [7] are conjunctive rules designed on top of an OWL ontology - SWRL specification contains built-ins allowing operations on integer, dates, etc. - A subset of SWRL rules are DL-safe (so, decidable) - SWRL allows defining customized built-ins• Benefits of using SRWL to define rules throwing knowledge exchange - A place owner can define its own sharing rules - Different places can apply a different policy to share knowledge - Adding a rule does not require to recompile the whole code of a node - Newly developed built-ins only need to be referenced in the rules 11 COPYRIGHT © 2011 ALCATEL-LUCENT. ALL RIGHTS RESERVED.
  • 12. How do we realize our proposalSharing knowledge – use of SWRL (2)• Example of rules that we used to test our approach - When a resource has reached (resp. left) a place P, notify all accessible places about this fact - Example of use: enable a node receiving an incoming request to answer “I do not have corresponding object but my neighbor has it” - When it has been learnt that any mobile resource reaches a place P2 after having reached a place P1 and if a resource has just joined P1 notify P2 that a resource will join. - Example of use: P2 anticipates the work required when a resource joins, loading its semantic description by advance 12 COPYRIGHT © 2011 ALCATEL-LUCENT. ALL RIGHTS RESERVED.
  • 13. How do we realize our proposalSharing knowledge – Overall process• Consider a node willing to share knowledge with a set of peers - Apply Dijkstra algorithm on the « graph » associated to the federation of nodes to find the path to follow from the source to the destination - Create a message routed from the source to the destination and containing knowledge to share (RDF triples or a pointer to a semantic description file) - Implementation uses RDF triple stores to store information about EoIs and devices - Consequently, implementation of the message is based on SPARQL1.1 syntax (allowing to update triples stores) 13 COPYRIGHT © 2011 ALCATEL-LUCENT. ALL RIGHTS RESERVED.
  • 14. How do we realize our proposalOverall picture • When a described entity is addedDescribed entities - Parse the triples of its description - Update local triple store Semantic profiles - Rebuilt KB (so re-run rules) {t1,t2,…,tn} - With results of the sharing knowledge rules RDF API - Build path for each neighbor to be updated{t1,t2,…,tn} All nec. triples - Generate SPARQL1.1 message KB Manager - Send message {r1,r2,…,rk} TS{r1,r2,…,rk} Msg1: L= {N3,N2} C= {r1,r2,rk} Result Msg2: L= {N3,N4,N5,N6} C= {r4,r7} Dispatcher … N3 N4 Indoor Location N instance N2 5 N1 N {r1,r2,rk} TS 6 TS {r4,r7} 14 COPYRIGHT © 2011 ALCATEL-LUCENT. ALL RIGHTS RESERVED.
  • 15. Experimentation• 26 modeled « places » bound to our premises• Several sets of different sizes - Containing semantic profiles of devices and EoIs (using models presented in earlier works [8,9]) - Set sizes ranging from 1 to 100000 RDF triples 15 COPYRIGHT © 2011 ALCATEL-LUCENT. ALL RIGHTS RESERVED.
  • 16. Experimentation (2)• Semantic node concept implemented as a Web application (running in a Tomcat server) - Fully implemented in Java - Use of OWLDB (further replaced by Sesame) to store triples - Use of the OWL API + HermiT reasoner to process semantic decriptions of entities - Use of JGraphT library to compute paths between different nodes• Computers (2.23GHtz, 2GB RAM) installed in the modelled “places”, each one running a Tomcat server with one instance of semantic node 16 COPYRIGHT © 2011 ALCATEL-LUCENT. ALL RIGHTS RESERVED.
  • 17. Experimentation (3)• 2 types of measures - Evaluating the time taken to update triple stores - Evaluating the time taken to query a triple store - Both follow an exponential curve, validating the fact that searching or maintaining a unique KB would be impossible. 17 COPYRIGHT © 2011 ALCATEL-LUCENT. ALL RIGHTS RESERVED.
  • 18. Conclusions• Use of a federated network of cooperative semantic nodes - Each one with a triple store, storing meaningful information• Double cascading process to let all nodes be aware of their neighbors• Sharing knowledge process - Based on SWRL rules - Using SPARQL1.1 to update triple stores• First measures shown - Sharing the results compiled by one node follows an exponential curve (function of the number of results to share) - Querying a triple store also follows an exponential curve (function of the number of triples contained by the store) 18 COPYRIGHT © 2011 ALCATEL-LUCENT. ALL RIGHTS RESERVED.
  • 19. References1. O. Lassila, “Applying semantic web in mobile and ubiquitous computing: Will policy-awareness help”, 4th International Semantic Web Conference, 2005.2. R. Masuoka, B. Parsia, and Y. Labrou, “Task computing - the semantic web meets pervasive computing”, 2nd International Semantic Web Conference (ISWC2003), 2003.3. O. Lassila and M. Adler, “Semantic gadgets: Ubiquitous computing meets the semantic web”, in Spinning the Semantic Web, 2003.4. A. Katasonov, O. Kaykova, O. Khriyenko, S. Nikitin, and V. Y. Terziyan, “Smart semantic middleware for the internet of things” in ICINCO-ICSO, 2008.5. D. Pfisterer, K. Rmer, D. Bimschas, O. Kleine, R. Mietz, C. Truong, H. Hasemann, A. Krller, M. Pagel, M. Hauswirth, M. Karnstedt, M. Leggieri, A. Passant, and R. Richardson, “Spitfire: toward a semantic web of things” IEEE Communications Magazine, 2011.6. D. Heimbigner and D. McLeod, “A federated architecture for information management”, ACM Trans. Inf. Syst. 1985.7. SWRL A Semantic Web Rule Language combining OWL and RuleML, http://www.w3.org/Submission/SWRL/8. B. Christophe, V. Verdot, and V. Toubiana, “Searching the web of things”, in Semantic Computing (ICSC), 2011.9. B. Christophe, “Semantic profiles to model the web of things”, in Semantics Knowledge and Grid (SKG), 2011. 19 COPYRIGHT © 2011 ALCATEL-LUCENT. ALL RIGHTS RESERVED.
  • 20. ThanksBenoit ChristopheBell Labs ResearchAlcatel-Lucent Bell Labs Francebenoit.christophe@alcatel-lucent.com 20 COPYRIGHT © 2011 ALCATEL-LUCENT. ALL RIGHTS RESERVED.

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