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Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
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Functional Composition of Sensor Web APIs

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  • 1. Functional CompositionRuben Verborgh et al. of Sensor Web APIs
  • 2. ?What makes people SMART
  • 3. Collaboration.
  • 4. ?What makes sensors SMART
  • 5. Collaboration.
  • 6. Smart collaborationsrun themselves. manual sensor composition intelligence comes from humans automatic sensor composition intelligence comes from the system
  • 7. My research is aboutintelligent Web APIs. Ruben Verborgh, PhD Student Ghent University / iMinds My dream: intelligent agents browsing the Web for us Bridging between people and things bringing things to the Web
  • 8. Functional composition of sensor Web APIs { Capturing functionality Creating compositions Evaluating feasibility
  • 9. Functional composition of sensor Web APIs { Capturing functionality Creating compositions Evaluating feasibility
  • 10. Why describe functionality?
  • 11. Only functionalitytells the whole story.
  • 12. How to capture the functionalityof these sensors? GPS device determines current location temperature sensor reads current temperature pressure sensor reads current air pressure
  • 13. We model sensorsas Web APIs. Web APIs = HTTP APIs = REST APIs as opposed to “Big” Web services resource-oriented Sensor measurements are resources location temperature air pressure
  • 14. We capture the functionalityof Web APIs with RESTdesc. RESTdesc describes the functionality of hypermedia-driven APIs with Notation3 (an RDF superset).
  • 15. RESTdesc can describea temperature sensor. ! ""#$%&$(")"%*+,%-.%()/0(%1%&$(2 """"""""""%*+34)/5&"#34)/5&6 7 89 ! "":+(%;0%$/"<//.+-%/<=>)-%"?@A,?2 """"""""""""<//.+(%;0%$/BCD"#$%&$(2 """"""""""""<//.+(%$."E"<//.+F=G"#/%-.%()/0(%"H6 "" ""#34)/5&"%*+<)$,%-.%()/0(%"#/%-.%()/0(%6 76
  • 16. RESTdesc can describea temperature sensor. ! ""#$%&$(")"%*+,%-.%()/0(%1%&$(2 """"""""""%*+34)/5&"#34)/5&6 7 89 ! "":+(%;0%$/"<//.+-%/<=>)-%"?@A,?2 """"""""""""<//.+(%;0%$/BCD"#$%&$(2 """"""""""""<//.+(%$."E"<//.+F=G"#/%-.%()/0(%"H6 "" ""#34)/5&"%*+<)$,%-.%()/0(%"#/%-.%()/0(%6 76
  • 17. RESTdesc can describea temperature sensor. ! ""#$%&$(")"%*+,%-.%()/0(%1%&$(2 """"""""""%*+34)/5&"#34)/5&6 7 89 ! ""8+(%90%$/"://.+-%/:;<)-%"=>?,=2 """"""""""""://.+(%90%$/@AB"#$%&$(2 """"""""""""://.+(%$."C"://.+D;E"#/%-.%()/0(%"F6 "" ""#34)/5&"%*+<)$,%-.%()/0(%"#/%-.%()/0(%6 76
  • 18. RESTdesc can describea temperature sensor. ! ""#$%&$(")"%*+,%-.%()/0(%1%&$(2 """"""""""%*+34)/5&"#34)/5&6 7 89 ! "":+(%;0%$/"<//.+-%/<=>)-%"?@A,?2 """"""""""""<//.+(%;0%$/BCD"#$%&$(2 """"""""""""<//.+(%$."E"<//.+F=G"#/%-.%()/0(%"H6 "" ""#34)/5&"%*+:)$,%-.%()/0(%"#/%-.%()/0(%6 76
  • 19. RESTdesc provides simplefunctional descriptions. Hypermedia-driven no inputs or outputs, just links Capture functionality relationship between resources Rule-based logic implication
  • 20. Functional composition of sensor Web APIs { Capturing functionality Creating compositions Evaluating feasibility
  • 21. Why compose Web APIs? To answer a query by combining multiple APIs. Queries can be complex, APIs not necessarily known in advance.
  • 22. “Reserve a table in a nearby restaurant. If weather allows, I want to sit outside.”
  • 23. What APIs do we haveat our disposition? Suppose we have many APIs, including: Location API Temperature API Pressure API Restaurant API
  • 24. What would a candidate solution lookoflike? Web a Functional Composition Sensor T I L R G P “Reserve a table in Location APIbining the Location, Temperature, Pressure, and Restauran a nearby restaurant. Temperature API dependencies, we can reach the Goal from the Initial state If weather allows, Pressure API I want to sit outside.” Restaurant API
  • 25. RESTdesc descriptions enableautomated composition. RESTdesc descriptions are rules Rules support inference Rules can be chained
  • 26. Does this compositionsatisfy the goal?{ } Since descriptions are rules, =>{ } success is defined as entailment.
  • 27. If success is entailment,the proof is the composition.{ } => The proof of the entailment{ }{ } contains the used rules, =>{ } thus the needed API requests.
  • 28. A semantic Web reasoner can create the composition. Functional Composition of Sensor Web a { } => { } { } { } => => { } T { } I L R G P “Reserve a table in { => } Location APIbiningnearby restaurant. { } Temperature API a the Location, Temperature, Pressure, and Restauran Pressure API dependencies, we can reach the Goal from the Initial state If weather allows, I want to sit outside.” Restaurant API
  • 29. RESTdesc composing behavesas a good Semantic Web citizen. works with generic semantic reasoners RESTdesc descriptions are rules no specific knowledge needed ontologies fill gaps domain-independent
  • 30. Functional composition of sensor Web APIs { Capturing functionality Creating compositions Evaluating feasibility
  • 31. Does it scale?
  • 32. Reasoner-based methodsare often thought of as slow. partly perception limit reasoner experience partly the method translation into reasoner domain
  • 33. We tested composition chainsfor performance. n APIs with 1/2/3 dependencies to test chaining speed 32 APIs in presence of n dummies to test discrimination speed
  • 34. RESTdesc composition is so fastthat it works on Web scale. chain of 512 APIs with 1 dependency in 0.4 seconds chain of 512 APIs with 3 dependencies in 1.6 seconds chain of 32 APIs with 512 dummies in 0,01 seconds
  • 35. Efficient implementationson Arduino boards. simple sensors as Web APIs described with RESTdesc central composer
  • 36. RESTdesc is an automated solutionfor sensor Web API composition. Describe REST Web APIs Use Semantic Web logic Compose with generic reasoners
  • 37. RESTdesc automatically composes sensor Web APIs. Curious? Let’s get in touch! Visit restdesc.org and connect to @RubenVerborgh on Twitter.

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