Smart Spaces Semantic Interoperability and Complex Event Processing

Transcription

1 Smart Spaces Semantic Interoperability and Complex Event Processing Seppo Törmä Distributed Systems Group Department of Computer Science and Engineering School of Science, Aalto University

2 Contents Research background Smart spaces Terminology and definitions Examples Enablers and goals Interoperability Volatility and interoperability Exising interoperability solutions DIEM approach Semantic information broker Protocols RDF and flexible merging of data Event-based systems Loose coupling Complex events and SPARQL

3 Distributed Systems Group Heikki Saikkonen, professor, software technology Esko Nuutila, researcher, distributed systems Seppo Törmä, researcher, distributed systems Ville Karavirta, post doc, service adapters Abdullah Haris, Ph.D. student, efficient subscription matching Jyrki Oraskari, Ph.D. student, learning in event-based systems Nam Vu Hoang, Ph.D. student, distributed transactional BIM Juho Makkonen, project researcher, Kassi social exchange service Antti Virolainen, project researcher, Kassi social exchange service Sampo Toiva, M.Sc. student, event-based social networking (ASI) Emmi Suhonen, M.Sc. student, motivational issues in Kassi Zuheb Hussain, M.Sc. student, mobile clients for event-based services

4 Distributed Systems Group Digital services Service interoperability and composition Loose coupling between services Non-intrusive interoperation with service adapters Distributed event-based systems Content-based publish/subscribe Efficient, incremental subscription matching Complex event processing Smart space applications Semantic interoperability Semantic representions (RDF) Semantic query languages (SPARQL) Distributed models Transactional changes Workflow management DRUM Distributed transactional BIMs ServiceCloud Service interoperability OtaSizzle Ubiquitous social media DIEM Device interoperability EIT SSAL Complex event processing in smart spaces

5 Terminology Smart space Definition: A built environment with embedded services for mobile users Merge physical and digital worlds Synonyms: Smart environment, Intelligent environment Related concepts Ambient intelligence Ubiquitous computing Pervasive computing Internet of Things Special focus Users activities Useful, interesting applications

6 Examples Home Offices and meeting rooms Vehicles - cars, busses, trains, Gyms, sport facilities Shops, restaurants, shopping malls Train stations, seaports, airports Hospitals, art museums, market squares Entertainment complexes - movies, tivolis, game arcades

7 Enablers Key technological enablers Wireless connectivity Device minituarization Resulting trends Increasing number of computing devices 1000 devices/person by 2015 Influenced by advanced interaction technologies Video and audio sensing Display technology Speech and gesture recognition Gaze tracking

8 Goals Enhance user s experience Adaptiation sense and learn user preferences Interact in a manner that is natural to humans Connect different domains User is in interaction with functionalities from many domains; for example, at home with Building automation (lightning, ventilation, heating) Home entertainment (audio and video players) Home appliances (fridges, washing machines) ICT devices (mobile phones, computers) Maximize energy efficiency Provide safe and secure environment

9 Volatility Smart spaces are volatile systems Distributed systems with frequent and unpredictable changes in users, devices, and software components device and communication failures changes in bandwidth creation and deletion of associations Physical mobility is seen as appearance and disappearance of devices from a smart space Volatility leads to the need of spontaneous interoperation preconfiguration is not possible as a general solution

10 Interoperability Generally: The ability of diverse systems to work together (inter-operate) Technically: The ability of two or more systems to exchange information and to use the information that has been exchanged Levels Technical communication protocol, message syntax Semantic interpret the information exchanged meaningfully can refer to same entities can refer to same real-world properties and relations Simplicity, flexible interaction, common languages

11 Existing interoperability solutions Generic interoperation insufficient to smart spaces as such CORBA Web Services (WSDL, SOAP, UDDI) Semantic Web (RDF, SPARQL, ) Specific for smart spaces UPnP Universal Plug and Play (ICT & entertainment at home) DLNA Digital Living Network Alliance (entertainment) NoTA Nokia Terminal Architecture OSGi A dynamic component model for JVM Amigo Ambient Intelligence for the Networked Home obix Open Building Information exchange Why not in widespead use? Domain-specific, closed, complex, low level? May require coordinated development from multiple parties

12 DIEM approach Semantic representations Graph-based data RDF Complex event processing Subscriptions to complex situations Dynamic SPARQL queries Connect existing services through adapters Respecting the legacy solutions Open, standard-compliant, and cross-domain Focus on semantics rather than protocols

13 Semantic information broker

14 SSAP - Smart Space Access Protocol RDF CRUD operations

15 Applications and services

16 RDF Resource Description Framework Family of W3C Recommendations Nothing fancy but flexible and standardized Lots of practical problems solved Data represented as a graph consists of arcs represented as triplets arcs can be interpreted as simple statements subject, predicate, object Graph is flexible and easily extensible structure new properties and relations can be added to existing nodes entities, and their properties and relations can come from different sources

17 Merging of data Entities are identified with a URI (or actually an IRI) The properties and relations concerning same URI can be merged into same node Types, properties, and relations are defined in an ontology If terms used in different sources are based on a same ontology, they can be interpreted as same Ontologies can support the definition of relationships between terms type, subclassof subpropertyof, inversefunctionalproperty

18 Example: Two data sources in RDF

19 Example: Merging data into one graph

20 Example: Meeting interoperability

21 RDF in practice Fragments of an RDF graph can be easily exchanged There are multiple serializations for RDF RDF/XML, Turtle, N3, Locally RDF graphs are manipulated in RDF stores Sesame, Jena, rdflib, NEO4J, There are different ways to specify ontologies RDFS RDF Schema (very basic constructs) OWL Web Ontology Language (based on description logics) There are some widely used special ontologies available for time, location, social relations, calendar information Broad, all-encompassing ontologies are less useful A little semantics goes a long way Jim Hendler

22 Event-based systems Publish/subscribe interaction style Consumers subscribe to the information they want to have and get notified when information comes available or changes Content-based subscriptions are dynamic queries to the information of the producers Information production, subscription matching, and notification can be distributed to multiple nodes (event processing network)

23 Event-based systems Taxonomy of interaction styles Does the producer or consumer initiate the information transfer Is the receiving component directly or indirectly addressed? Addressing Consumer Initiator Producer Direct Request/reply Callback Indirect Anonymous request/reply Event-based Does indirect addressing require some kind of middleware functionality?

24 Loose coupling Publish/subscribe provides a decoupling of consumers and producers in the following dimensions: Anonymous (Space decoupling). Consumers and producers do not need to know of each other. In particular, the consumer does not make any assumption about the location of the producer. Asynchronous (Time decoupling). Consumers and producers do not have to be simultaneously present during the interaction. The publication of the information may have happened long before consumer becomes active signs in or regains the network connectivity and is notified about the event. Non-blocking (Synchronization decoupling). Producers do not block when publishing events and consumers do not block when notified about an event. That is, the production and consumption of events do not happen in their main flow of control.

25 Example: Request/reply location access Request/reply example as a REST call Request: userxxx Reply: {"latitude": , "longitude": } Assumptions Location of service: Method call interface: getlocation?user=<string> Format of reply: a JSON object as a string with fields latitude having value in and longitude having value in Availability of at the time of call Sufficiently low response time of Any of these assumptions can fail The fewer assumptions are made between parties, the more flexible and robust the interaction style is

26 Example: Event-based location access Content-based subscription: SELECT?lat?long { userxxx haslocation?location.?location latitude?lat.?location longitude?long. } The consumer makes a subscription, a dynamic query distributed to all producers is notified whenever the result of the query changes Much weaker assumptions about the producers location, availability, or response time particular method call or reply formats There can be multiple producers or the producer may change over the time

27 Complex events Notify me if two of my friends are together in my vicinity SELECT?a?b?la { me location?lm me knows?a. me knows?b.?a location?la.?b location?lb. FILTER (near(?la,?lb, 5) and near(?lm,?la, 200)) } How to evaluate such queries efficiently?

28 Incremental subscription matching Queries can be translated into an incremental matching network The SSAP events can be inserted to the network events are propagated if they pass all the filters with insert the variables in the queries are bound to the proper parts of the triples when remove, the bindings are deleted Algorithmic variations RETE, TREAT, LEAPS Under construction!

29 Summary Smart spaces need capability for spotaneous interoperation The research challenges are at the level of semantic interoperability Techniques from the Semantic Web can be used RDF, SPARQL, Ontologies Complex event processing Behavior driven by events from sensors or mobile devices Content-based publish/subscribe Complex situations and complex event patterns