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A Survey on Context-Aware Computing : Past, Present, and Future Center for E-Business Technology Seoul National University Seoul, Korea Sang-keun Lee Intelligent Database Systems Lab School of Computer Science & Engineering Seoul National University, Seoul, Korea
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Copyright 2008 by CEBT Motivation Context-Aware System
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Copyright 2008 by CEBT History of Context-Aware Computing: Context Definition Term ‘Context-aware’ appeared in Schilit and Theimer(1994) Authors describe context as location, identities of nearby people, objects, and changes to those objects Ryan et al. (1997) referred to context as the user’s location, environment, identity, time Day (1998) : the user’s emotional state, focus on attention, location, and orientation, date and time, as well as objects and people in the environment Dey and Abowd (2000) Any information that can be used to characterize the situation of entities that are considered relevant to the interaction between a user and an application, including the user and the application themselves
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Copyright 2008 by CEBT History of Context-Aware Computing: Application & System, Context Model Active Badge Location System (Wang et al., 1992) One of the first context-aware systems Forward phone calls to a telephone close to the user Couple of location-aware tour guides Abowd et al., 1997; Sumi et al., 1998; Cheverst et al.,2000 Providing information according to the user’s current location Watson Project (Budzik and Hammond, 2000) W3C, RDF available (2000) IntelliZap (Finkelstein, 2001) Context Toolkit (Dey and Abowd, 2001) p2p architecture + centralized discoverer, attribute-value tuple/XML - Context aggregation/interpretation, historical context data, Context Ownership (Privacy) Hydrogen (Hofer, 2002) local/remote context, Object Oriented Model, process higher-level context abstraction in application layer
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Copyright 2008 by CEBT History of Context-Aware Computing: Application & System, Context Model Gaia project (Roman’s) Extends operating system contepts to include context-awareness 4-ary predicates in DAML+OIL, context processing is based on first-order logic operation Graphical Context Model: ORM (Hendricksen, 2003) Context Managing Framework (Koripaa, 2003) Centralized server CoBrA- Context Broker Architecture (Chen, 2003) COBRA-Ont(Ontology Model), Inference Engine, historical context data, Broker federation – Avoiding bottleneck Context Knowledge base – You can assert, delete, modify, query the stored data(API) Flexibile policy language to control context access called Rei (privacy) 2004 W3C, OWL available
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Copyright 2008 by CEBT History of Context-Aware Computing: Application & System, Context Model Markup scheme model: Composite Capabilities/Preference Profile (CC/PP) (W3C, 2004) SOCAM(Service-Oriented Context-Aware Middleware) (Gu, 2004) Upper ontology, Domain-specific Ontology CASS (Fahy and Clarke, 2004) CORTEX (2004) Based on sentient object model – sensor fusion to manage uncertainty of sensor data Graphical Context Model: Context Modeling using UML (Sheng and Benatallah, 2004) CoCA (Ejigu, 2007) Enhanced CoCA (Ejigu, 2008) Using a hybrid context management model – Relational Database, Ontology Tools Heuristics for better performance
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Copyright 2008 by CEBT History of Context-Aware Computing: Sensor Definition Burnett (2003) and Gustavsen (2002) External and internal Hofer et al. (2002) Physical and logical Semantic Tech & Context - 7 Context that can be measured by hardware sensors, i.e,., locationa, light, sound, movement, touch, temperature or air pressure Context that can be captured by user interactions, i.e., the user’s goals, tasks, work context, emotional state Easier to sense
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Copyright 2008 by CEBT Practical Semantic Technology - 8
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Copyright 2008 by CEBT Practical Semantic Technology - 9
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Copyright 2008 by CEBT The History in Summary Specific Context Definition to General Context Definition Non-Flexible Context Models to Flexible and Extensible Context Model Domain-specific Applications to General Frameworks
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Copyright 2008 by CEBT Categories of Context Aware Applications Schilit (1994) Proximate Selection – A user interface technique where the located-objects that are nearby are emphasized or otherwise made easier to choose Automatic Contextual Reconfigurations – Reconfiguration is the process of adding new components, removing existing components or altering the connections between components Contextual Information and Commands – Queries on contextual information can produce different results according to the context in which they are issued Context-Triggered Actions – Context-triggered actions are simple IF-THEN rules used to specify how context-aware systems should adapt Sang-keun Lee Context-Aware / Personalized Contents Push Seamless Device Switching Automatic Device Configuration Decision Support/Suggestion Context Aware User Interface 11 Context-aware computing applications (Schilit, B.; Adams, N.; Want, R.) Mobile Computing Systems and Applications, 1994. Proceedings., Workshop onVolume, Issue, 8-9 Dec 1994 Page(s):85 - 90
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Copyright 2008 by CEBT An Example of Domain-dependent Applications: Cyberguide : A mobile context-aware tour guide (1997) Goal know where tourist is, and what she is looking for predict and answer question she may pose provide interaction with other people and environment
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Copyright 2008 by CEBT Design Principles – Architecture Chen (2004) presents three different approaches on how to acquire contextual information Direct sensor access – devices with sensors locally built in Middleware infrastructure – hiding low-level sensing details, more extensible Context Server – multiple clients access to remote data source Winograd (2001) Widgets – a software component that provides a public interface for a hardware sensor, hiding low-level details of sensing, managed by widget manager Networked services – more flexible, discovery techniques are used, not as efficient as a widget architecture but provides robustness Blackboard model – data centric view, simplicity of adding new context sources (easy configuration) Architecture Style Peer to Peer – Limitation of Memory Resource, CPU Performance – Only uses local built-in sensors Centralized Approach – Robustness Baldauf, M., Dustdar, S., and Rosenberg, F. 2007. A survey on context-aware systems. Int. J. Ad Hoc Ubiquitous Comput. 2, 4 (Jun. 2007), 263-277. DOI= http://dx.doi.org/10.1504/IJAHUC.2007.014070
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Copyright 2008 by CEBT Hydrogen (2002) Framework Architecture Three layer – Application layer – Management layer Providing and retrieving contexts and sharing context information with other devices using P2P communication – Adaptor Layer Separating context storing, sensing from other layers Responsible to get information from sensors Providing same context information to multiple applications All application have access to all context data by querying the ContextServer All layers are located on one device – Robust against network disconnections, Peer to Peer Object-oriented Context Model
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Copyright 2008 by CEBT SOCAM Architecture (2004) Context providers, Context interpreter, Context database, Context-aware services, and Service locating service Architectural Requirements A common context model that can be shared by all devices and services A set of services that perform context acquisition, context discovery, context interpretation and context dissemination Upper/Domain-specific Ontology 15 Acquire context from sources Context Providers Provides logic reasoning Context Interpreter Stores context ontologies Context Database Adapt the way they behave Context-aware Services provides a mechanism where Context Providers and the Context Interpreter can advertise their presence Service Locating Service
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Copyright 2008 by CEBT The Context Fabric (2004) Primarily concerned with privacy rather than with context sensing and processing provides an architecture for privacy-sensitive systems, as well as a set of privacy mechanisms that can be used by application developers Previous work on privacy has tended to focus on anonymity or on keeping information from hackers Confab’s focus is in empowering people with choice and informed consent, so that they can share the right information, with the right people and services, in the right situation
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Copyright 2008 by CEBT The CoCA Service Platform (2007) IDS Lab.17 Interface Manager Manages a UI and interface between the CoCA platform and other modules Data Source Responsible to provide necessary data to the core service (GCoM) Core Service Responsible to provide the core context aware service after reasoning on the components Supplementary Service Knowledge discovery & Collaboration service The Platform aims at acquiring and utilizing context information to provide appropriate services E.g) A cell phone is always set to vibrating mode when its holder is in the library It filters and sends useful contexts to the context repository It Keeps the rules in the rule repository It consists of domain dependent/independent ontology Reasoning -> Decision & Action Interpretation, Aggregation
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Copyright 2008 by CEBT The Enhanced CoCA Service Platform (2008) Enhanced version of CoCA Combine the best of the relational approach and ontology approach Selective feature of loading only relevant context data into the reasoner using heuristics
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Copyright 2008 by CEBT Summary: Existing systems and frameworks Baldauf, M., Dustdar, S., and Rosenberg, F. 2007. A survey on context-aware systems. Int. J. Ad Hoc Ubiquitous Comput. 2, 4 (Jun. 2007), 263-277. DOI= http://dx.doi.org/10.1504/IJAHUC.2007.014070
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Copyright 2008 by CEBT Criteria Henricksen, K., Indulska, J., McFadden, T. and Balasubramaniam, S. (2005). Middleware for distributed context-aware systems. In: Robert meersman and Zahir Tari et al International Symposium on Distributed Objects and Applications (DOA), Agia Napa, Cyprus, 31 October - 4 November, 2005.
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Copyright 2008 by CEBT Discussion Does a context-aware system bother users? MS Office Assistant Clippy Three Levels of Interactivity – Personalization The majority of users use the default setting of change a small subset of the possible features – Passive Context-awareness Presenting the updated context to the user Let the user specify how the application should change Ex) mobile phone prompts the user with information about the time zone change – Active Context-awareness Changing the content autonomously on the basis of measured sensor data Ex) Mobile phone that changes its time autonomously by new time zone The authors conclude that people are willing to give up partial control if the reward in usefulness is great enough How could we deal with the imperfect/probabilistic context data? Fuzzy Logic Context Data Abstraction What could be the Killer Application? What could we mine from the log data? Support Rules Peer to Peer vs. Centralized System L Barkhuus, A Dey, Is Context-Aware Computing Taking Control Away from the User? Three Levels of Interactivity Examined,2003
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Copyright 2008 by CEBT Layered Conceptual Framework with Core Components Foundation Layer: Sensors Data/Rule Mining Relational Database Network Foundation Layer: Sensors Data/Rule Mining Relational Database Network Semantic Technology Layer: Ontology Repository Inference Engine Semantic Technology Layer: Ontology Repository Inference Engine Service & Application Design Layer: Context-Aware Services: Context Acquisition Device Communication Data Management & Mining Data Management & Mining Context Ontology Modeling Context Fusion & Abstraction Rule based Action Triggering Ontology Data Storage & Management Low-level Data Modeling Context-Aware Personalized Contents Push Seamless Device Switching Automatic Device Configuration Decision Support & Suggestion Context Aware User Interface Ubiquitous Intelligent Seamless Domain-specific Context Data Modeling Rule Defining Service Algorithm Implementation Privacy & Security Policy Defining Privacy & Security Policy Defining Private Scalable
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Copyright 2008 by CEBT Conclusions We talked about Motivation History of Context-aware Computing Categories of Context-aware Applications Design Principle Examples of Context-aware Systems Criteria & Discussion What will be the future Context-aware System? A Context-aware system with – Better scalability and performance – Utilizing historical context data (Rule mining,...) – Better Security policies and privacy protection – Virtual and logical sensor support – Standard communication protocol and context model
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