An Intelligent Broker Architecture for Context-Aware Systems A PhD. Dissertation Proposal in Computer Science at the University of Maryland Baltimore County January 2003 Presented by Sangkeun Lee IDS Lab.

Copyright  2008 by CEBT About this Paper  CoBrA Is one of well-known context-aware systems by Harry Chen Is an agent based architecture for supporting context-aware systems in smart spaces There are more than 14 papers related to CoBrA – Is the topic of Chen’s PhD thesis, and he’s achieved his PhD. Degree in Dec, 2004  This Paper Is a PhD. Dissertation Proposal Is a very early research related to CoBrA Describes a research plan to develop a broker-centric agent architecture May help us preparing our degree papers IDS Lab. Seminar - 2Center for E-Business Technology

Copyright  2008 by CEBT Contents  1 Introduction 1.1 What’s Context-Aware Computing? 1.2 Problems in Context-Aware Computing – Lack of Reusable Context-Aware Mechanisms – Limited Resources in Mobile Devices – Privacy Issues in Accessing User Information 1.3 Proposed Solution: Context Broker Architecture – Use Case – Research Contribution 1.4 Proposal Outline  2 Background 2.1 Reasons to Study Context 2.2 Definitions of Context 2.3 Aspects of Context-Aware Computing – Enhancing User Interfaces – Guiding the Adaptation of System Behavior – Enabling Smart Space Applications 2.4 How Do Applications Acquire Contexts? – Direct Access to Hardware Sensors – Facilitated by a Middle-ware Infrastructure – Acquiring Contexts from a Context Server 2.5 Context-Aware Computing Meets Semantic Web  3 Context Broker Architecture 3.1 Objectives 3.2 Modeling the Physical World in Domains 3.3 An Example System of the Context Broker Architecture 3.4 The Design of Domain Context Broker – Knowledge Base – Inference Engine – Context Acquisition Component – Broker Behavior  4 Summary and Research Plan 4.1 Initial Approach to Implementation – Modeling Ontology and Policy using OWL – Building the Inference Engine using Jess – Implementing the Broker Behavior using JADE 4.2 Feasibility Study 4.3 Milestones IDS Lab. Seminar - 3Center for E-Business Technology I will skip some of the contents that we’ve already discussed many times (e.g. What’s Context-aware computing?, Definitions of Context)

Copyright  2008 by CEBT Problems in Context-Aware Computing  Limited Resources in Mobile Devices Battery Power Constraints Information Storage Constraint Computing Power Constraint Communication Constraint – Agents may be lack of sufficient knowledge to communicate with context sources in the environment e.g. knowing which sensor can provide what information and how to communicate – Context sources may dynamically join and leave the environment without notifying the agents IDS Lab. Seminar - 4Center for E-Business Technology

Copyright  2008 by CEBT Problems in Context-Aware Computing (cont’d)  Privacy Issues in Accessing User Information People are worried about how computer systems use and share their personal information Agents often collect and share user information Agents also share user information  Lack of Reusable Context-Aware Mechanisms Many of existing context-aware systems are difficult and costly to build Because existing systems are tightly coupled with agent implementations, modifying the system often requires modifying the implementation of the agents. – Growing the number of agents could cause difficulties IDS Lab. Seminar - 5Center for E-Business Technology

Copyright  2008 by CEBT Background  Aspects of Context-Aware Computing Enhancing User Interfaces Guiding the Adaptation of System Behavior Enabling Smart Space Applications  How Do Applications Acquire Contexts? Contexts are acquired by directly accessing low-level context sensors Contexts are acquired from some kind of middle-ware infrastructures that in turn interact with low-level context sensors Contexts are acquired from servers that maintain situational knowledge about the environment IDS Lab. Seminar - 6Center for E-Business Technology

Copyright  2008 by CEBT Proposed Solution: Context Broker Architecture  The author proposes to develop a broker-centric agent architecture (i.e. COBRA) to provide runtime supports for context-aware systems in an Intelligent Meeting Rom environment  The core of the COBRA architecture: Domain Context Broker is responsible for Maintaining the context model of the domain, which includes domain contexts from the past and at the present Resolving inconsistencies and ambiguities of the domain contexts through information fusion Establishing privacy policies with users before sharing their personal information Providing knowledge sharing service for context-aware agents through agent communications IDS Lab. Seminar - 7Center for E-Business Technology

Copyright  2008 by CEBT Context-Aware Computing Meets Semantic Web  Semantic Web & Context-Aware System Semantic Web standards will enhance the communication and information sharing Semantic Web will become a major source of information for determining the context of users and thie associated daily activities – E.g. When a person enters a room, his location information (his presence in the room) is automatically updated in his personal web site. Immediately, context-aware agents in both remote and local environment can acquire the presence information about the person through the Web without needing any sensing or reasoning. IDS Lab. Seminar - 8Center for E-Business Technology

Copyright  2008 by CEBT Context Broker Architecture Semantic Web Pervasive Computing Software Agents CoBrA CoBrA not CORBA!

Copyright  2008 by CEBT COBRA Architecture  Objectives Acquiring context from heterogeneous sources – From sensors, Web, user profiles, behavior pattern Maintaining consistent contextual knowledge Enabling knowledge sharing among agents Protecting the privacy of users  Domain Context Broker Context sharing Protecting privacy IDS Lab. Seminar - 10Center for E-Business Technology

Copyright  2008 by CEBT The Design of Domain Context Broker IDS Lab. Seminar - 11Center for E-Business Technology

Copyright  2008 by CEBT Knowledge Base  Domain Ontology Context Model : fundamental concepts for representing contexts Information Source Model : sensors, user devices, web services, … Agent Profile Model : types or services that an agent offers, the reason for acquiring certain contexts etc. Information Privacy Model  Domain Heuristics Help the broker to resolve knowledge inconsistency caused by imperfect sensing Help the broker to build and maintain a shared model of context  User Privacy Policies What information can or can’t be shared, etc IDS Lab. Seminar - 12Center for E-Business Technology

Copyright  2008 by CEBT Inference Engine  Ontology Reasoning Module deduce facts that can be concluded from the knowledge in the Knowledge Base in conjunction with the models that are defined in the Domain Ontology  Context Reasoning Module Reasoning about situational conditions of an entities  Knowledge Maintenance Module Check logical implication – “If A is true, then B must be true” – “B is not true” – “A is true” – “B is true” – Inconsistent! Apply domain heuristics – “No one person can be in two different rooms at the same time” – “Bob is currently attending a meeting in RM 201” – “Bob is currently typing a paper on his computer in RM 102” – Inconsistent! IDS Lab. Seminar - 13Center for E-Business Technology

Copyright  2008 by CEBT Broker Behavior  Privacy Policy Negotiation IDS Lab. Seminar - 14Center for E-Business Technology

Copyright  2008 by CEBT Broker Behavior  Knowledge Sharing IDS Lab. Seminar - 15Center for E-Business Technology

Copyright  2008 by CEBT Use Case: An EasyMeeting Scenario The broker detects Alice’s presence B    Policy says, “can share with any agents in the room” A B The broker builds the context model Web Alice “beams” her policy to the broker B Policy says, “inform my personal agent of my location” A B.. isLocatedIn..

Copyright  2008 by CEBT Use Case: An EasyMeeting Scenario (cont’d) Her agent informs the broker of her role and intentions + The broker tells her location to her agent A The projector agent wants to help Alice The projector agent asks slide show info. B The projector agent sets up the slides The broker informs the subscribed agents B

Copyright  2008 by CEBT Summary and Research Plan  Initial Approach to Implementation Modeling Ontology and Policy using OWL Building the Inference Engine using Jess Implementing the Broker Behavior using JADE  Feasibility Study: Validating following hypothesizes By exploiting the Semantic Web infrastructure, context-aware agents can access a wider range of contexts By developing a hybrid context reasoning mechanism, we can help capability limited agents to maintain a coherent and consistent model of contexts in a dynamic environment By enabling agents to share a common model of contexts, we will allow agents to access contexts By defining a policy-driven mechanism to control how users’ personal contexts are used and shared, we can effective protect the privacy of users IDS Lab. Seminar - 18Center for E-Business Technology

Copyright  2008 by CEBT A Bird’s Eye View of CoBrA

Copyright  2008 by CEBT Discussion  Evaluation Clearly defines the problems to solve Provides a good conceptual design of the system shows us how we should plan for a research Well-written proposal paper However, more details are required – Will be presented  Ideas & Discussion Writing proposal seems very meaningful How can we show that a new context-aware system is better than existing ones? IDS Lab. Seminar - 20Center for E-Business Technology