A Survey on Context-Aware Systems Center for E-Business Technology Seoul National University Seoul, Korea Sangkeun Lee Intelligent Database Systems Lab School of Computer Science & Engineering Seoul National University, Seoul, Korea

Copyright  2008 by CEBT Current Situation  Advanced network & Computing technology  Wide spread of mobile devices  Rapidly growing number of services  Too much contents  Realizing context-aware systems is a key driver for solving these problems Introduction User GPS Navigator Cell phone Home Network PC Digital camera Voice recorder PDA User’s Context Service Content How can we provide the most appropriate service or content to users?

Copyright  2008 by CEBT Agenda  Introduction  Definitions Context & Context-Aware Systems  Characteristics of Context-aware Systems  Requirements of Context-Aware Systems  History of Context-Aware Systems Trend analysis : 1 st, 2 nd, 3 rd generation context-aware systems Summarize the characteristics of several representative context-aware systems  Comparison & Evaluation  Conclusion Introduction

Copyright  2008 by CEBT What is Context?  Schilit and Theimer define context in terms of location, identities of nearby people, objects, and the changes to those objects over time (1994)  Dey refers to context as the user’s emotional state, focus on attention, location, and orientation, date and time, as well as objects and people in the environment (1998)  Dey and Abowd (2001) define context as 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 Definitions

Copyright  2008 by CEBT What are Context-Aware Systems?  Hull et al. define context-aware computing as the ability of computing devices to detect and sense, interpret and respond to aspects of a user's local environment and the computing devices themselves (1997)  Brown refers to context-aware applications as applications that automatically provide information and/or take actions according to the user’s present context as detected by sensors (1998)  Dey and Abowd define context-aware systems as the systems that use context to provide relevant information and/or services to the user, where relevancy depends on the user’s task (2001) Definitions

Copyright  2008 by CEBT A General Context-Aware Service Process  Acquiring Context Information  Storing Context Information  Controlling Abstraction Level of Context Information  Utilizing Context Information for Services or Applications Characteristics of Context-aware Systems Acquiring Context Information Storing Context Information Controlling Abstraction Level of Context Information Utilizing Context Information for Services or Applications Physical Sensors Other Sources (Virtual Sensors) Context Models Context Aggregation Context Interpretation Context as Triggering Condition Context as Additional Information

Copyright  2008 by CEBT Context Acquiring  A Context-aware system is responsible for gathering context information of entities (e.g. people, devices, places, etc)  Physical Sensors Hardware components that converts physical context information into computable signals  Various physical sensors are available – GPS, Active Badge System, RFID – Temperature, Pressure, Humidity, Light, Ultrasonic Sensors – Microphones, Cameras Acquiring Context Information Storing Context Information Controlling Abstraction Level of Context Information Utilizing Context Information for Services or Applications Physical Sensors Other Sources (Virtual Sensors) Context Models Context Aggregation Context Interpretation Context as Triggering Condition Context as Additional Information Characteristics of Context-aware Systems

Copyright  2008 by CEBT Context Acquiring  Using physical sensors is not the only way of gathering context information of entities  Virtual Sensors Software components that retrieve context information various source – Getting weather information using a web service – Achieving user’s preference on music by analyzing user’s playlist – Acquiring user’s current status by getting user’s explicit submit Acquiring Context Information Storing Context Information Controlling Abstraction Level of Context Information Utilizing Context Information for Services or Applications Physical Sensors Other Sources (Virtual Sensors) Context Models Context Aggregation Context Interpretation Context as Triggering Condition Context as Additional Information Characteristics of Context-aware Systems

Copyright  2008 by CEBT Context Storing  Efficient storage and management of context information is crucial  Closely related to context models Criterias: Expressiveness, Flexibility, Generality, Computational Cost  Stored historical context data could be useful when achieving trend or predicting future context  Stored context data should be easily accessible Context ModelExamples Key-Value ModelSchilt’s Approach, Context Toolkit Logic-based ModelMcCarthy’s Approach Mark-up Scheme Model CC/PP, UAProf, CSCP, GPM Object-oriented Model Hydrogen Graphical ModelContext extension of ORM, Vector space model Ontology ModelSOCAM, CoBrA, CASS, CoCA Acquiring Context Information Storing Context Information Controlling Abstraction Level of Context Information Utilizing Context Information for Services or Applications Physical Sensors Other Sources (Virtual Sensors) Context Models Context Aggregation Context Interpretation Context as Triggering Condition Context as Additional Information Characteristics of Context-aware Systems

Copyright  2008 by CEBT Controlling Abstraction Level of Context Information  Context Aggregation To reduce the number of low-level context information for better performance E.g. Temperatures of previous 10 minutes -> Very Cold  Context Interpretation To grant high-level semantics to sensed context information (Context Interpretation) E.g. GPS signal -> City name  If separate context-abstraction and context-aware application, application doesn’t have to the know details of sensors but still can utilize context-data Acquiring Context Information Storing Context Information Controlling Abstraction Level of Context Information Utilizing Context Information for Enhanced Services or Applications Physical Sensors Other Sources (Virtual Sensors) Context Models Context Aggregation Context Interpretation Context as Triggering Condition Context as Additional Information Characteristics of Context-aware Systems

Copyright  2008 by CEBT Utilizing Context Information for Services & Applications  Context Information can be used for various types applications Context-Aware Personalization – Providing personalized contents or information to user based on the user’s current context Automatic Device Configuration – Automatically setting up device’s configuration according to user’s situation Context-aware User Interface – Automatically Optimize device’s user interface based on user’s preference or context Context-aware Suggestion – Suggests or recommend the most suitable action to users based on current situation Acquiring Context Information Storing Context Information Controlling Abstraction Level of Context Information Utilizing Context Information for Enhanced Services or Applications Physical Sensors Other Sources (Virtual Sensors) Context Models Context Aggregation Context Interpretation Context as Triggering Condition Context as Additional Information Characteristics of Context-aware Systems

Copyright  2008 by CEBT Utilizing Context Information for Services & Applications  Two ways of utilizing Context Information Context Information as Service Triggering Condition – E.g. If a user is hungry and thirsty, then trigger food delivery service Context Information as Additional Information for Enhanced Service – E.g. Providing tour-guide information based on user’s current location Acquiring Context Information Storing Context Information Controlling Abstraction Level of Context Information Utilizing Context Information for Enhanced Services or Applications Physical Sensors Other Sources (Virtual Sensors) Context Models Context Aggregation Context Interpretation Context as Triggering Condition Context as Additional Information Characteristics of Context-aware Systems

Copyright  2008 by CEBT Context-Aware System Architecture Style  A Context-Aware System can be implemented in many ways Device Sensors Context Device Sensors Context Device Sensors Context Device Sensors Context Device Sensors Context Device Sensors Central Context Server Context Device Sensors Device Sensors Stand-alone Architecture Distributed Architecture Characteristics of Context-aware Systems Centralized Architecture

Copyright  2008 by CEBT Context-Aware System Architecture Style  Stand-alone Architecture Simple architecture Directly accessing sensors to get context-data No context information sharing or communication among devices Device Sensors Context Stand-alone Architecture Characteristics of Context-aware Systems

Copyright  2008 by CEBT Context-Aware System Architecture Style  Distributed Architecture Context information can be stored in multiple locations No centralized server High degree of failure-tolerance Less congestion Problem Complex communication protocol required  Centralized Architecture All context information are managed in a centralized context server Low degree of failure-tolerance Congestion(Bottleneck) Problem Easier to Implement Device Sensors Context Device Sensors Context Device Sensors Context Device Sensors Context Device Sensors Central Context Server Context Device Sensors Device Sensors Distributed Architecture Centralized Architecture Characteristics of Context-aware Systems

Copyright  2008 by CEBT Requirements of Context-Aware Systems  To realize a practical and useful context-aware systems, we need to consider various aspects Requirements of Context-Aware Systems Description Domain Independency In many cases, it is required for context-aware systems to manage various types of sensors, devices, protocols and context data in different domains. The systems should not depend on specific domains and deal with heterogeneity. Support for Complex Services The complexity of context-aware services can vary from very simple ones to complex ones according to the number and the types of entities that participate in the services. A good context- aware system should be able to provide context-aware services with high complexity. Handling Dynamicity Many entities(e.g. device, people, sensors, etc) dynamically participate during the context-aware service process. Context-aware systems should be able to handle the dynamicity of entities. Failure Tolerance As many devices participate in context-aware services, there are high possibilities that some of them may be disconnected or fail. Context-aware system should have failure tolerance and proceed services even when some devices have problems. Performance & Scalability Context-aware services should be provided in real-time in most cases. Context-aware systems should be able to deal with a large amount of context-data with acceptable performance and scalability. Support for Historical Data Context-aware system should support for historical data such as historical context data and service log. Historical context data could be useful when achieving trend or predicting future context, and past context-aware service log could be used as feedback for enhancing future service quality. Privacy Protection Privacy protection is another requirement for context-aware systems. Context-aware systems gather information from users autonomously, so some users may feel uncomfortable that the system can use or open their information without any notice. Context-aware systems should allow users to define their own privacy policy and protect illegal accesses. Requirements of Context-aware Systems

Copyright  2008 by CEBT History of Context-Aware Systems  We review several existing context-aware systems and summarize the history of context-aware systems to analyze the trend  Categorize representative context-aware systems into three groups based on their characteristics 1 st generation context-aware systems – The Active Badge location System, Cyberguide 2 nd generation – Watson Project, Context Toolkit, Hydrogen, Aura, Gaia 3 rd generation – CoBrA, SOCAM, CASS, SOCAM, Confab, CORTEX, CoCA History of Context-aware Systems

Copyright  2008 by CEBT 1 st Generation Context-Aware Systems  Characteristics Period : 1990 ~ 2000 Location-aware system & Domain-specific application Limited types of context were used – Location & Time Focus on how to achieve location information – GPS/ Active Badge / IR / Ultrasonic  Example Systems The Active Badge Location System Cyber guide History of Context-aware Systems

Copyright  2008 by CEBT The Active Badge Location System  A location-aware system  Active Badge A tag that emits a unique ID for approximately a tenth of a second every 15 seconds a network of sensors placed around the host building picks up the signals from active badges A master station polls the sensors makes the sensed context data available to clients  Operations A command interpreter allows simple investigations to be performed on the system FIND (name), WITH (name), LOOK (location), NOTIFY (name), HISTORY (name)  Application Forwarding phone calls to nearest phone to the user Semantic Tech & Context - 19 History of Context-aware Systems 1 st Generation Context-Aware Systems

Copyright  2008 by CEBT Cyberguide  A domain-specific context-aware application  Limited context types Location and time  Context Acquiring Indoor Location : IR Sensor Outdoor Location : GPS Sensor  Functionality A mobile context-aware tour guide Providing information based on tourist’s current location and time Tour diary: keeping log of places tourist have visited Semantic Tech & Context - 20 History of Context-aware Systems 1 st Generation Context-Aware Systems

Copyright  2008 by CEBT Cyberguide Semantic Tech & Context - 21 History of Context-aware Systems 1 st Generation Context-Aware Systems

Copyright  2008 by CEBT 2 nd Generation Context-Aware Systems  Characteristics Period : 2000 ~ 2003 Earlier attempt to build context-aware frameworks for rapid prototyping various context- aware applications Support for various context types (More than location and time)  Example Systems Context Toolkit, Hydrogen, Gaia – Too simple context model (Context Toolkit, Hydrogen) – Resource discovery not supported (Context Toolkit) – Support only for specific types of context (Hydrogen) – Only use built-in sensors (Hydrogen) – Lack of privacy protection (Context Toolkit, Hydrogen, Gaia) – Lack of performance concern (Context Toolkit, Hydrogen, Gaia) History of Context-aware Systems

Copyright  2008 by CEBT Context Toolkit  Aim is to develop reusable solution to make development of context aware applications easier  Inspired by the success of GUI development kits  GUI Toolkits Hide underlying complexity Manage the details of interaction Provide reusable building blocks  A distributed architecture + central discoverer  Widgets [Context Widget] Hide the complexity of actual sensors used from application Abstract context information to suit the expected needs Provide reusable building blocks for context sensing  Aggregators Aggregate context information Hide even more complexity about the context  Interpreters Used to abstract or interpret low- level context information  Resource discovery not supported  Context Model Attribute – Value Model 23 2 nd Generation Context-Aware Systems History of Context-aware Systems Context Acquiring Context Abstraction

Copyright  2008 by CEBT Hydrogen  Context-awareness framework on mobile devices  A distributed layered architecture Application layer Management layer – Providing and retrieving contexts and sharing context information with other devices using P2P communication Adaptor Layer (Context Acquiring) – Separating context storing, sensing from other layers – Responsible to get information from sensors – Providing same context information to multiple applications All layers are located on one device All application have access to any context data by querying the Context Server  Context Sharing Via WLAN, Bluetooth  Context Model Object-oriented Context Model  Resource discovery is not required Only use built-in sensors History of Context-aware Systems 2 nd Generation Context-Aware Systems

Copyright  2008 by CEBT Gaia  A ubiquitous software platform encapsulates the heterogeneity of active spaces, and presents them as a programmable environment, instead of a collection of individual and disconnected heterogeneous devices Context-aware extension to traditional OS  Active Space an extension to physical space capable of sensing user actions and equipped with a large variety of devices will assist users with different tasks  A distributed architecture 25 History of Context-aware Systems 2 nd Generation Context-Aware Systems

Copyright  2008 by CEBT Gaia  Context Acquiring & Abstraction Context Provider : Acquires context information from sensors or external sources (e.g. stock price) Synthesizer Context Provider : Infer high-level context from low-level context First Order Logic – Context(Number of people, Room 2401, >, 4) ANDContext(Application, Powerpoint, is, Running) => Context(Social Activity, Room 2401, Is, Presentation)  Context Model 4-ary predicate Context(,,, )  Context Storing Context File System  Context Consumer Application service that consumes context information  Application Framework Semantic Tech & Context - 26 History of Context-aware Systems 2 nd Generation Context-Aware Systems

Copyright  2008 by CEBT 3 rd Generation Context-Aware Systems  Characteristics Period : 2003 ~ Ontology Context Model – Formal, expressive, flexible context model – Suitable for knowledge Sharing – CoBrA, SOCAM, CASS, CoCA Focus on privacy protection – Context Fabric Performance & scalability – Context Fabric, CoCA Support for easy implementation of context-aware application – CORTEX History of Context-aware Systems

Copyright  2008 by CEBT OWL (Web Ontology Language)  W3C announced the OWL (Web Ontology Language) in 2003  A semantic markup language  Designed for the Semantic Web  Formal, flexible and expressive  Has many predefined classes and properties  Suitable for knowledge sharing Semantic Tech & Context - 28 History of Context-aware Systems

Copyright  2008 by CEBT CoBrA  Architecture Style An agent-based context-aware syst em A centered resource-rich context br oker maintains and manages the sh ared context data  Context Model Uses OWL to model ontological con text & privacy policy  Privacy Protection Rei : Allows users to define privacy policy so that it can protect privacy of users  Context knowledge API - assert, del ete, modify, query context data 29 3 rd Generation Context-Aware Systems History of Context-aware Systems Context Knowledge Base Privacy Management Module Context Inference Engine Context Acquisition Module Context Storing Privacy Protection Context Abstraction & Reasoning Context Acquiring

Copyright  2008 by CEBT SOCAM  A centralized architecture  Context Model A common context model that can be shared by all devices and services Upper/Domain-specific Ontology : Reduce ontology processing cost  A set of services that perform context acquisition, context discovery, context interpretation and context dissemination 30 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 3 rd Generation Context-Aware Systems History of Context-aware Systems

Copyright  2008 by CEBT SOCAM 31 3 rd Generation Context-Aware Systems History of Context-aware Systems

Copyright  2008 by CEBT The Context Fabric  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  Share the right information, with the right people and services, in the right situation  Downside: It does not address traditional distributed systems requirements such as mobility, scalability, component failures and deployment/configurations  XML Context Tuple  Distributed Architecture 3 rd Generation Context-Aware Systems History of Context-aware Systems

Copyright  2008 by CEBT The CoCA Service Platform IDS Lab.33  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 3 rd Generation Context-Aware Systems History of Context-aware Systems

Copyright  2008 by CEBT The Enhanced CoCA Service Platform  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 3 rd Generation Context-Aware Systems History of Context-aware Systems

Copyright  2008 by CEBT Trend Analysis

Copyright  2008 by CEBT Comparison System Name Context Acquiring Context Model Context Repository Context Abstraction Resource Discovery Architecture Style

Copyright  2008 by CEBT Evaluation System Name Domain Independency Service Complexity Handing Dynamicity Failure Tolerance Performance & Scalability Support for Historical Data Privacy Protection

Copyright  2008 by CEBT Conclusions 결론 내리기