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A Semantics-based Framework for Context-Aware Services Lessons Learned and Challenges

A Semantics-based Framework for Context-Aware Services Lessons Learned and Challenges. Theodore Patkos, Antonis Bikakis , Grigoris Antoniou, Maria Papadopouli, Dimitris Plexousakis Institute of Computer Science, FORTH, Greece.

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A Semantics-based Framework for Context-Aware Services Lessons Learned and Challenges

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  1. A Semantics-based Framework for Context-Aware ServicesLessons Learned and Challenges Theodore Patkos, Antonis Bikakis, Grigoris Antoniou, Maria Papadopouli, Dimitris Plexousakis Institute of Computer Science, FORTH, Greece 4th International Conference on Ubiquitous Intelligence and Computing (UIC-07)

  2. System Overview • The CG-platform is a framework • for developing advanced location-based and context-awareservices, • applying techniques and formalisms from the Semantic Web and Ubiquitous Computing domains. • The system is a Context Pedestrian Guiding application for supporting user experience in indoor environments through personalized, context-aware and context-adaptive services. Semantics-based Framework for Context-Aware Services - UIC 2007

  3. Talk Outline • Key Concepts • Context-Awareness • Mobile Ubiquitous Computing Systems • Semantic Web • System Presentation • System Architecture • Supported Services • Challenges • Distributed Planning • Dynamic Planning • Plan Sharing Semantics-based Framework for Context-Aware Services - UIC 2007

  4. CG Platform Architecture CG - Client CG - Server XML XML HTML/SVG Interactive Map UI Communication Module CG - Database Communication Module CG Database Server RDF & XML Parsers RQL/RDF RDF & XML Parsers CG RDF Schema Authentication Module RDF Cache ICS-FORTH RDFSuite Workflow Manager Semantics-based Framework for Context-Aware Services - UIC 2007

  5. CG RDF Schema Graph

  6. Server - Client Communication • XML message exchanges, adopting the notion of envelope. • Each message includes information about the act of communication itself that allows the identification of communicating parties, message type and intended action. • Message content can involve: • RQL data, which contain RQL queries to the database • RDF data, which contain (RDF descriptions of) updates to the database Semantics-based Framework for Context-Aware Services - UIC 2007

  7. Server - Client Communication • An example <cg-message> <sender>device18</sender> <receiver>CG-Server</receiver> <language>RQL</language> <content> SELECT Z, LastName, Room FROM {X}lname{LastName}, {Z}arrangement.initiatedBy{X}, {Z}locatedAt{Room}, {Z}from{Start}, {Z}to{End} WHERE Room LIKE {G100} AND Start >= 2006-03-21 AND End < 2006-03-22 </content> </cg-message> Semantics-based Framework for Context-Aware Services - UIC 2007

  8. UI Design • Action layer Dynamically displays context information from ontology • Map Layer Architectural design under different scales • Interactive Layers Service-driven • SVGs Javascript enabled • Java Applet Sophisticated procedures Semantics-based Framework for Context-Aware Services - UIC 2007

  9. Distributed Planning and Multi-agent Coordination – Challenges • The vision of Ubiquitous Computing implies seamless collaboration of numerous devices working together to achieve common objectives. • Even the more ordinary services of our platform, such as the management of a presentation in a meeting room may involve continuous cooperation between devices, as diverse as the room's audio/video equipment, the lighting dimmer, the lecturer's laptop etc. • More complicated services require more sophisticated models of teamwork between devices that differ in capabilities, characteristics and resource limitations. • Moreover, the expectancy of devices to participate in teamwork is not known beforehand and is dependent on parameters, such as resource availability, mobility, commitments etc Semantics-based Framework for Context-Aware Services - UIC 2007

  10. Distributed Planning and Multi-agent Coordination – Objectives • Coordination does not imply either cooperation or reciprocation. • The self-organization and autonomy of devices are important design goals. • To approach the problem of coordinating the actions of multiple agents in a ubiquitous distributed environment, agents engage in Cooperative Distributed Planning, where they are endowed with shared objectives and representations, with the purpose to jointly develop and execute a plan in a coherent and effective manner. Semantics-based Framework for Context-Aware Services - UIC 2007

  11. Distributed Planning and Multi-agent Coordination – Relevant Works • Generalized Partial Global Planning (GPGP) • Commitment-based approaches, i.e., Cooperative Problem Solving (CPS) • Extension of the Partial-order Causal Link Planning to explore the multi-agent plan coordination problem • Logic-based approaches, i.e., Coalition Logic • It is important to remember that despite the various strategies that have emerged over the years, it does not seem possible to devise a coordination strategy that works well under all circumstances. • Optimal coordination is desirable but rarely feasible, because it generally requires substantial computation and communication overhead. Semantics-based Framework for Context-Aware Services - UIC 2007

  12. Complex, Dynamic and Uncertain Environments – Challenges • The majority of services provided by our platform requires a certain degree of reasoning and plan management skills by the participating agents. • For instance, an agent wishing to print a document must deliberate on whether to use the slow inkjet printer located near the user or the faster high resolution laser printer of the adjacent room. • While trying to enhance our platform with more aspects of context, the complexity of the planning task becomes computationally intractable. • The simplifying assumptions of the classical planning problem, such as deterministic, atomic and simultaneous actions, omniscient agents, static and closed environments, must be relaxed or completely eliminated. Semantics-based Framework for Context-Aware Services - UIC 2007

  13. Complex, Dynamic and Uncertain Environments – Objectives • The ambient computing environment is an open and highly dynamic environment. • Mobile devices connect and disconnect to the network, contributing services with durations that vary according to their expected presence in the environment and the availability of their resources. • Actions, goals and sensor observations have a temporal dimension, whose duration may only be partially known in advance. • The assumption of complete world knowledge can no longer persist; agents do not know a priori all other entities that are present at a specific time instance nor can they communicate directly with all of them. Semantics-based Framework for Context-Aware Services - UIC 2007

  14. Complex, Dynamic and Uncertain Environments – Objectives • They have limited perception to acquire knowledge about the world they live in and have to generate plans preserving a level of uncertainty on both the state of the world, the available actions to achieve certain state of affairs and the outcome of those actions. • Even the fact of committing different agents to certain tasks cannot be guaranteed to hold, since agents might disconnect before plan generation completes or new and more beneficial opportunities might arise. • The non-deterministic nature of the environment is emphasized by the recognition that not only agents, but also exogenous events occur, in unpredictable and concurrent manner, affecting the state of the world. Semantics-based Framework for Context-Aware Services - UIC 2007

  15. Complex, Dynamic and Uncertain Environments – Relevant Works • STRIPS • Action Theories (Situation, Fluent, Event Calculus) • Action Languages (A, C+, GC+, K, E) • MDPs, POMDPs • We emphasize on the use of intuitive and mathematically correct formal frameworks, since they allow IS analysts to produce detailed, formal specifications of ambient computing processes. • Most approaches still trade simplicity for reality, due to the increased complexity of their reasoning mechanisms. • It is difficult to build a unified model that combines different phenomena, such as nondeterminism, concurrency, knowledge, continuous change etc. Semantics-based Framework for Context-Aware Services - UIC 2007

  16. Plan Representation, Evaluation and Sharing – Challenges • We need to represent the capabilities and specifications of different devices, so that distributed services can be adapted accordingly. • We assume that the existence of visitors possessing unknown mobile devices is going to be a common situation for our platform. • Profiles of devices must be flexible enough to capture both complexactions and decompositions of them to primitive ones, so that planning agents can understand and combine them to distribute responsibilities during service execution. • In addition, plan execution must be monitored online and contextual information should be considered when evaluating possible future steps. Semantics-based Framework for Context-Aware Services - UIC 2007

  17. Plan Representation, Evaluation and Sharing – Objectives • We need to dynamically associate with plan evaluation parameters, such as resource preservation, goal prioritization, importance value of actions, even trust and privacy metrics. • It is not enough to just build better planners, we also need to be able to recognize which planning problems and opportunities to consider in the first place. • We need to be able to weight alternative incomplete plans and to decide among competing alternatives. • We need to share common plan representations or ontologies for describing plans, goals and actions. Semantics-based Framework for Context-Aware Services - UIC 2007

  18. Plan Representation, Evaluation and Sharing – Relevant Works • Plan Representation • Hierarchical Task Networks • Skeletal Plans • Plan Evaluation and Monitoring • Model-based Diagnosis • Constraints and Important values: temporal constraints (i.e., action duration), motivations, goals with priorities and deadlines • Very few formal frameworks model complex actions and common plan representations. • Planning based on context and privacy parameters. Semantics-based Framework for Context-Aware Services - UIC 2007

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