Multi-level context adaptation in the Web of Things
Mehdi Terdjimi - SOC & TWEAK Team
LIRIS - Université Lyon 1
http://liris.cnrs.fr/~mterdjim/slides_presentation
At first, the Internet of Things
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source: http://nwavetec.com/technology/the-internet-of-things/ |
Then, the Web of Things
- Built upon the IoT
- Relies on Web technologies and standards
- Breaks through silos
Context in ubiquitous computing
- high impact to the application's behavior
- complex and highly dynamic
How to design generic context models...
- to include what is needed by the application ?
- to do the actual adaptation, specific to the application ?
The answer is...
Multi-level context models
Context of the work: ASAWoO
- Exposing physical objects through a web interface: avatar (Mrissa et al., 2014)
- Using context to deal with resource-constrained objects.
Challenges
- Interoperable context data sources
- Generic context models
- Scalability in view of the high numbers of clients
Motivations
- Semantic context models for the WoT (SotA)
- Adaptation at several abstraction levels
- Scalable adaptation engine (reasoning steps: modularization, distribution)
PLAN
- State of the art
- context modeling
- mobile/client reasoning
- Approach
- Implementation
- Evaluation
- Discussion, future work
State of the art: context modeling
Former definitions
- Location, identity of entities, changes to entities
(Schilit and Theimer, 1994)
- Physical and conceptual states of an entity
(Pascoe, 1998)
- Any information that can be used to characterize the situation of an entity
(Dey et al., 1999)
What about specific applications ?
State of the art: context modeling
Physical World
Time, Location, Activity
(Schilit et al., 1993), (Dey et al., 1999), (Schmidt, 2003), (Zimmermann et al., 2007)
User, Device, Geospatial, Environment
Query recommendation and auto-complete (Arias, 2008)
Location, Time, Activity, Posture, Privacy
Context-aware web browser (Coppola et al., 2010)
State of the art: context modeling
Communication
Device computing resources, Network (status, type), Distances
(Gold and Mascolo, 2001), (Mascolo et al., 2002)
Context-aware adaptive routing (Musolesi and Mascolo, 2009)
User, Location, Network policy, Network capacity, Status
(Wei et al., 2006)
Notion of static, dynamic network context (Raverdy et al., 2006)
State of the art: context modeling
Application architecture
Separation of the application core from the context information
(Gensel et al., 2008), (Chaari et al., 2005)
Device, Location, User, Social, Environment, Time, System, Application-specific
Aspect-oriented approach (Munnely et al., 2007)
Location, Device, Application, Time (group calendar), Community (group, users, roles), Process
Groupware systems (Kirsch-Pinheiro et al., 2004)
State of the art: context modeling
Social Computing
User sessions: click-trough & navigation, query reformulation & specialization (ranking)
(Cao et al., 2009), (Xiang et al., 2010)
Domain, User, Environment and Interaction
provides context sharing between agents in MAS (Brézillon, 2003)
User, Item, Environment, Observer
describes a situation in MAS (Bazire and Brézillon, 2005)
State of the art: Mobile/Client reasoning
Mobile reasoners
- KRHyper (Sinner and Kleemann, 2005), FOL
- Embedded EL+ Reasoner (Grimm et al., 2012)
- Mine-ME 2.0 (Ruta et al., 2014), ALCN
JavaScript reasoners
Approach
- 1. Semantic context model
based on the 4 abstractions levels and SotA dimensions
- 2. Generate graphs from context models
SPARQL querying on graphs
- 3. Reasoning steps separation & modularization
Distributed reasoning process
"Which communication protocols can be used?"
(Location: home, Security: Level_1, Time: Evening)
Implementation
Modularization of OWLReasoner steps
HyLAR (Hybrid Location-Agnostic Reasoning)
(Terdjimi et al., 2015)
- Server-side as Node / Express modules
- Client-side as AngularJS services
- Client queries sent by an agnostic angular service
Evaluation
3 configurations x 3 steps x 2 ontologies
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- Ontology loading
- Ontology parsing and classification
- SPARQL query processing
|
Evaluation results
Network delays
Classification [P2] and reasoning [P3] times
- Qx: time for the query to reach the server
- Rx: time for the response to reach the client
- Px: processing time
- Times expressed in ms
Discussion
Time calculation for M users sending N queries
Server-side:
P2server + M x N x (Q3 + P3server+ R3)
Client-side:
M x (Q0 + R0 + Q1 + R1) + P2client + N x P3client
Hybrid:
P2server + M x (Q0 + R0 + Q2 + R2) + N x P3client
Discussion
No optimal configuration
Parameters: Number of clients, number of queries per client, network status, ontology size
Perspectives
- Improve/replace OwlReasoner
to study the impact of more complex queries
- Semantic multi-level context model
to provide...
- Adaptive reasoning process
based on context states (= graphs)
- Rule engine
References
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(Schilit and Theimer, 1994) Schilit, B.N., Theimer, M.M.: Disseminating active map information to mobile hosts. Network, IEEE 8(5), 22-32 (1994)
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(Pascoe, 1998) Pascoe, J.: Adding generic contextual capabilities to wearable computers. In: Wearable Computers, 1998. Digest of Papers. Second International Symposium on. pp. 92-99. IEEE (1998)
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(Dey et al., 1999) Dey, A.K., Salber, D., Abowd, G.D., Futakawa, M.: The conference assistant: Combining context-awareness with wearable computing. In: Wearable Computers, 1999. Digest of Papers. The Third International Symposium on. pp. 21-28. IEEE (1999)
References
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(Schilit et al., 1993) Schilit, B.N., Adams, N., Gold, R., Tso, M.M., Want, R.: The parctab mobile computing system. In: Workstation Operating Systems, 1993. Proceedings., Fourth Workshop on. pp. 34-39. IEEE (1993)
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(Schmidt, 2003) Schmidt, A.: Ubiquitous computing-computing in context. Ph.D. thesis, Lancaster University (2003)
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(Zimmermann et al., 2007) Zimmermann, A., Lorenz, A., Oppermann, R.: An operational definition of context. In: Modeling and using context, pp. 558-571. Springer (2007)
References
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(Coppola et al., 2010) Coppola, P., Mea, V.D., Di Gaspero, L., Menegon, D., Mischis, D., Mizzaro, S., Scagnetto, I., Vassena, L.: The context-aware browser. IEEE Intelligent Systems 25(1), 38-47 (2010)
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(Arias, 2008) Arias, M.: Context-Based Personalization for Mobile Web Search. Context pp. 33- 39 (2008)
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(Gold and Mascolo, 2001) Gold, R., Mascolo, C.: Use of context-awareness in mobile peer-to-peer networks. In: Distributed Computing Systems, 2001. FTDCS 2001. Proceedings. The Eighth IEEE Workshop on Future Trends of. pp. 142-147. IEEE (2001)
References
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(Mascolo et al., 2002) Mascolo, C., Capra, L., Emmerich, W.: Mobile computing middleware. In: Advanced lectures on networking, pp. 20-58. Springer (2002)
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(Musolesi and Mascolo, 2009) Musolesi, M., Mascolo, C.: Car: context-aware adaptive routing for delay-tolerant mobile networks. Mobile Computing, IEEE Transactions on 8(2), 246-260 (2009)
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(Wei et al., 2006) Wei, Q., Farkas, K., Prehofer, C., Mendes, P., Plattner, B.: Context-aware handover using active network technology. Computer Networks 50(15), 2855-2872 (2006)
References
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(Gensel et al., 2008) Gensel, J., Villanova-Oliver, M., Kirsch-Pinheiro, M.: Modèles de contexte pour l'adaptation à l'utilisateur dans des systèmes d'information web collaboratifs. In: Workshop from "8èmes journées francophones". Sophia-Antipolis, France. pp. 5-16
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(Munnely et al., 2007) Munnelly, J., Fritsch, S., Clarke, S.: An aspect-oriented approach to the modularisation of context. In: Pervasive Computing and Communications, 2007. PerCom'07. Fifth Annual IEEE International Conference on. pp. 114-124. IEEE (2007)
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(Kirsch-Pinheiro et al., 2004) Kirsch-Pinheiro, M., Gensel, J., Martin, H.: Representing context for an adaptative awareness mechanism. In: Groupware: Design, Implementation, and Use, pp. 339-348. Springer (2004)
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(Mrissa et al., 2014) Mrissa, M., Médini, L., Jamont, J.P., Le Sommer, N., Laplace, J.: An avatar architecture for the web of things (2014)
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HyLAR: Hybrid Location-Agnostic Reasoning
Mehdi Terdjimi, Lionel Médini, Michael Mrissa
LIRIS - Université Lyon 1