A Biological Internet: Building Eywa from a Social Web of Things with a Little Fog, Stream processing and Linked Data

Keynote at the Web Science Summer School 2017

Transcript

1. EUGENE SIOW
2. Eywa is like a huge biological internet; the trees being computer servers that store information and sensors being neural-connected flora and fauna JAMES CAMERON’S
4. “The Internet of Things is currently beset by product silos.” W3C Web of Things Interest Group
5. Siow, E., Tiropanis, T. and Hall, W. (2017) A Decentralised Social Web of Things.
6. Siow, E., Tiropanis, T. and Hall, W. (2017) A Decentralised Social Web of Things. Crowd Sourcing Web 2.0/Mobile Chatbots Messaging Client Neural Representation Collaborative Editing Strong AI Algorithmic Rule-based Learned Friend/Follow Trustless Networks Edge Prediction Policy Game Theory
8. Fog Computing utilises the space between the “Ground” and “Cloud” Irrigation Application Soil Moisture Analytics Lightweight Computer Hub Data Stream Environmental Sensors National Disaster Monitoring Application Weather Data State Inclement Weather Planning Application Distributed Queries
9. Building ”Pillars” to support EYWAS Fog RDF Stream Processing Personal IoT Repository Faster Queries, Stream Processing eugenesiow.github.io/iot
10. Buil-Aranda, C., Hogan, A.: SPARQL Web-Querying Infrastructure: Ready for Action? ISWC 2013 Semantic Sensor Ontology Smart City Ontology GeoNames Ontology
11. { timestamp : 1467673132, temperature : { max: 22.0, min: 15.0, current: 17.0, error: { percentage: 5.0 } } } { timestamp : 1467673132, temperature : 32.0, wind_speed : 10.5, pressure : 1016 } UNIQUE DEVICES dweet.io FLAT SCHEMATA COMPLEX SCHEMATA { timestamp : 1467673132, temperature : 32.0, humidity : 10.5, pressure : 1016, light: 120.0, } 1 2 3 4
12. produces produces located produces has value unit time Siow, E., Tiropanis, T. and Hall, W. (2016) SPARQL-to-SQL on internet of things databases and streams. ISWC2016: The 15th International Semantic Web Conference
13. produces produces located produces has value time unit has value time unit has value time unit Siow, E., Tiropanis, T. and Hall, W. (2016) SPARQL-to-SQL on internet of things databases and streams. ISWC2016: The 15th International Semantic Web Conference
14. produces located unit 13.0 93.0 10.5 2016-01-01 06:00:00 Siow, E., Tiropanis, T. and Hall, W. (2016) SPARQL-to-SQL on internet of things databases and streams. ISWC2016: The 15th International Semantic Web Conference
15. produces located unit 13.0 93.0 10.5 2016-01-01 06:00:00 Siow, E., Tiropanis, T. and Hall, W. (2016) SPARQL-to-SQL on internet of things databases and streams. ISWC2016: The 15th International Semantic Web Conference
16. produces located unit 13.0 93.0 10.5 2016-01-01 06:00:00 has value has value has value Siow, E., Tiropanis, T. and Hall, W. (2016) SPARQL-to-SQL on internet of things databases and streams. ISWC2016: The 15th International Semantic Web Conference
17. produces located unit 13.0 93.0 10.5 2016-01-01 06:00:00 has value has value has value Siow, E., Tiropanis, T. and Hall, W. (2016) SPARQL-to-SQL on internet of things databases and streams. ISWC2016: The 15th International Semantic Web Conference
18. produces loc unit 13.0 93.0 2016-01-01 06:00:00 has value has va a has value has unit { } Siow, E., Tiropanis, T. and Hall, W. (2016) SPARQL-to-SQL on internet of things databases and streams. ISWC2016: The 15th International Semantic Web Conference a has value has unit BGP
19. 13.0 has value a has value has unit { } a has value has unit Siow, E., Tiropanis, T. and Hall, W. (2016) SPARQL-to-SQL on internet of things databases and streams. ISWC2016: The 15th International Semantic Web Conference BGP
20. a has value has unit { } a has value has unit BGP Siow, E., Tiropanis, T. and Hall, W. (2016) SPARQL-to-SQL on internet of things databases and streams. ISWC2016: The 15th International Semantic Web Conference
21. a has value has unit { } Siow, E., Tiropanis, T. and Hall, W. (2016) SPARQL-to-SQL on internet of things databases and streams. ISWC2016: The 15th International Semantic Web Conference
22. has value produces located unit has value has value a has value has unit BGP a has value has unit
23. predicate
24. ~20,000 Stations 100 – 300k triples Wind, Rainfall, etc. 10 SRBench Queries Zhang, Y, et al. (2012) "SRBench: a streaming RDF/SPARQL benchmark.”The 11th International Semantic Web Conference. Siow, E., Tiropanis, T., Hall, W. (2016). "Interoperable and Efficient: Linked Data for the Internet of Things." The 3rd International Conference on Internet Science. 3 months, 1 home ~30k triples Motion, energy, environment 4 Analytics Queries GraphDB (OWLIM) Ontop Our Approach (S2S) TDB Morph
25. x15 x68 x112 x9 x1352 x453
26. Get the rainfall observed in a particular hour from all stations Q01 with an optional clause on unit of measure x5 x3 x13 x4k x2 x4 x4 x5k
27. Detect if a hurricane has been observed Get the average wind speed at the stations where the air temperature is >32 Join between wind observation and temperature observation subtrees time-consuming in low resource environment (Raspberry Pi) Detect if a station is observing a blizzard x3 x6 x6 x88 x3 x3
28. Get the stations with extremely low visibility Detect stations that are recently broken Get the daily minimal and maximal air temperature observed by the sensor at a given location x2 x14 x4 x6 x6 x5 x2
29. Get the daily average wind force and direction observed by the sensor at a given location Get the locations where a heavy snowfall has been observed Our Approach (s2s) is shown to be faster on all queries in the Distributed Meteorological System with SRBench Join between wind force and wind direction observation subtrees is time-consuming in low resource environment (Raspberry Pi) x3 x3k x2 x7
30. Temperature aggregated by hour on a specified day Minimum and maximum temperature each day for a particular month x7 x29 x3 x9
31. Energy Usage Per Room By Day Diagnose unattended appliances consuming energy with no motion in room Our Approach (s2s) is shown, once again, to be faster on all queries for Smart Home Analytics Involves motion and meter data (much larger set), with space-time aggregations and joins between motion and meter tables/subgraphs. Involves meter data (larger set), with space-time aggregations. x69 x13 x4
32. sparql2stream Same engine and mappings but translates to EPL instead of SQL 2 Stream Window SPARQL query specifying stream window size 1 Stream Sockets Supports multiple platforms and streams with ZeroMQ 3 Real-time analytics 4
33. a has value has unit { } Event Processing Language
34. 1 2 3 4 5 7 8 9 10 294 261 306 277k 3243k 5245 426 280k 98 Le-Phuoc, D., et al. (2011) "A native and adaptive approach for unified processing of linked streams and linked data.” The 10th International Semantic Web Conference. Performance Improvement For IoT Data Over 196 2 1 167 xImprovement Query
35. >99% <1ms latency increasing from 1 to 1000 rows/ms 33.5million rows, projected ~2.5 billion triples! <1ms 10-100ms 1 2 5 10 100 1000 99% 100% Rate in rows/ms Percentage Latency in ms Bands
36. Siow, E., Tiropanis, T. and Hall, W. (2016) PIOTRe: Personal Internet of Things Repository: The 15th International Semantic Web Conference P&D github.com/eugenesiow/piotre sparql2stream sparql2sql github.com/eugenesiow/sparql2sql Apps sparql2stream sparql2sql Metadata
37. Siow, E., Tiropanis, T. and Hall, W. (2017) A Fog Computing Framework for RDF Stream Processing. Sensors Node Data Stream Broker Subscribe(URI_1) Client Publish ([Query_p1,Q_p2]) Push (Select_Stream), Access Control, Bandwidth Control Query Broadcast, Nodes manage distributed processing No single point of failure. Any RPi can serve as a broker. ‘Best effort’ for source nodes ResultSet
38. “It’s really hard to stimulate your brain with no [sensation of] light. It’s blanking me. I can feel my brain just not wanting to do anything.” Adam Bloom, sensory deprivation subject in BBC documentary “Total Isolation” (2008) “"Who's Eywa? Only their deity! Their goddess, made up of all living things. Everything they know!” Norm explaining Eywa to Jake in Avatar (2009)
39. @eugene_siow “It's a long road, it's a long and narrow way. If I can't work up to you, you'll surely have to work down to me someday.” Narrow Way by Bob Dylan EUGENE SIOW THANASSIS TIROPANIS WENDY HALL