MS – EasyLiving

EasyLiving

1. “Pervasive computing: a paradigm for the 21st century” — Debashis Saha 

The project is developing an architecture and related technologies for intelligent environments. The project supports research addressing middleware, geometric world modeling, perception, and service description. Key system feartures include computer vision, multiple sensor modalities, automatic and semiautomatic sensor calibration, and device-independent communication and data protocols.

HP – cooltown

Cooltown

1. “Pervasive computing: a paradigm for the 21st century” — Debashis Saha

The project focuses on extending Web technologies, wireless networks, and protable devices to create a virtual bridge between mobile users and physical entities and electronic services.

Cooltown uses URLs for addressing, physical beaconing and sensing of URLs for discovery, and localized web servers for directories to create a location-aware system that supports nomadic users. It leverages Internet connectivity on top of this ingrastructure to support communications services.

2.  “Modeling Context Information in Pervasive Computing Systems” (2002) — Karen Henricksen

The project proposed a web-based model of context in which each entity (person, place or thing) has a corresponding description that can be retrieved via a URL. This model is relatively informal; entity descriptions take the form of web pages, which may be unstructured and intended for human (rather thant application) consumption.

Cambridge – Sentient Computing

Sentient computing

1. “Pervasive computing: a paradigm for the 21st century” (2003)  — Debashis Saha

The project explores user interfaces that employ sensors and resource status data to maintain a world model shared by users and applications.

The world mdoel covers an entire building. Interfaces to programs extend seamlessly throughout the building. Computer desktops follow their owners and reflect real-time updates for object locations. The project has led to some new kinds of applications, like comtext-aware filing systems and smart posters.

2. “Modeling Context Information in Pervasive Computing Systems” (2002) — Karen Henricksen

The model is more formal, and is based on an object-modeling paradigm. A conceptual model of context is constructed using a language based on the ER model, and context information is stored at run-time in a relational database.

Washington – Portolano

Portolano

1. “Pervasive computing: a paradigm for the 21st century” — Debashis Saha 

The project seeks to create a testbed for investigating pervasive computing. The project emphasizes invisible, intent-based computing, which infers users’ intentions via thier actions in the environment and their interactions with everyday objects.

Project devices are highly optimized to particular tasks so that they blend into the world and require little technical knowledge on the users’ part. Portolano proposes an infrastructure based on mobile agents that interact with applications and users. Data-centric routing automatically migrates data among applications on the user’s behalf. Data thus becomes “smart”, and serves as an interaction mechanism within the environment.

CMU-Aura

Aura

1. “Pervasive computing: a paradigm for the 21st century” — Debashis Saha

The project aims to design, implement, deploy, and evaluate a large-scale computing system demonstrating a “personal information aura” that spans wearable, handheld, destop, and infrastructure computers.

Aura is a large umbrella project with many individual research thrusts. Darwin is a intelligent network at Aura’s core. Coda is a distributed file management system that supports nomadic file access, and Odyssey provides OS support for resource adaptation.

Theses products and others are evolving within the Aura project, which empahsizes pervasive middleware and application design.

UC Berkeley — Endeavour

 Endeavour

1. “Pervasive computing: a paradigm for the 21st century” — Debashis Saha

The project is an academic effort that focuses on the specifiation, design, and prototype implementation of a planet-scale, self-organizing, and adaptive “information utility”. The smart environment is pervasive-everywhere and always there-with components taht flow through the infrastructure, shape themselves to adapt to their usage, and cooperate on tasks.

Endavour’s key innovative technological capability is its pervasive support for fluid software. It includes processing, storage, and data management funcationality to arbitrarily and automatically distribute itself among pervasive devices and along paths through scalable computing platforms that are integrated with the pervasive networking infrastructure. The system can compose itself from perexisting hardware and software components to satisfy a service request while advertising the services it can provide to others.

Karen Henricksen

2006

 

1.      Developing context-aware pervasive computing applications: models and approach (2006)

This paper addresses the software engineering process, including context modeling techniques, a preference model for representing context-dependent requirements, and tow programming models.

2005

 

2.      Middleware for distributed context-aware systems (2005)

Most current middleware or infrastructure for context-aware systems have not adequately addressed issues such as mobility, fault tolerance or privacy. This paper provides an analysis of the requirements of a middleware, and a critical review of several middleware solutions and their own PACE middleware.

3.      Personalizing context-aware applications (2005)

This paper characterizes several approaches to personalization of context-aware applications and introduce our research on personalization using a novel preference model.

4.      Modeling context information with ORM （2005）

This paper addresses, drawing on their experiences with using an ORM-based context modeling approach to develop a variety of context-aware applications. It also shows how their extended variant of ORM is used to support the development of context-aware applications, and outline some of the remaining challenges.

5.      Context obfuscation for privacy via ontological descriptions (2005)

The paper proposes privacy protection mechanisms for users, which are intended to provent breaches of user privacy through unauthorized context disclosure. It describes a new obfuscation mechanism that can adjust the granularity of different types of context information to meet disclosure requirements stated by the owner of the context information.

6.      Applying a disciplined approach to the development of a context-aware communication application (2005) 

This paper demonstrates the use of a disciplined, model-based approach to engineer a context, session initiation protocol based communication application. The approach enables the description, acquisition, management and exploitation of arbitrary types of context and user preference information to enable adaptation to context changes. We consider a self-adapting communication application that exploits context and preference information to allow users to communicate seamlessly with one another.

7.      Extending context models for privacy in pervasive computing environments （2005）

This paper tackles the ownership challenges in an attempt to provide one of the missing pieces required for a complete privacy one of the missing pieces required for a complete privacy solution for context-aware systems. It argues that ownership information forms a natural extension to context models, and propose the integration of flexible notions of ownership into their previously developed context modeling techniques.

2004

8.      Towards a common context model for virtual community applications (2004)

This paper describes how the complexity associated with designing and implementing context-aware applications can be reduced through both context reuse and programming methods that allow context evaluation to be decoupled from applications.

9.      Towards a hybrid approach to context modeling, reasoning and interoperation

This paper investigates evaluates the most appropriate uses of ontology languages and tools in context-aware systems, and to explore the creation of a new hybrid solution that combines ontology concepts with previously developed approach to context modeling and reasoning.

10.  Automating context-aware application development

This paper describes an extensible set of tools they are developing for use in conjunction with their existing context modeling framework and infrastructure that provides substantial assistance to the development and deployment of context-aware applications.

11.  A software engineering framework for context-aware pervasive computing

This paper presents a conceptual framework and software infrastructure that together addresses known software engineering challenges, and enables further practical exploration of social and usable issues by facilitating the prototyping and fine-tuning of context-ware applications.

12.  Modeling and using imperfect context information

This paper explores the problem of imperfect context information and some of its causes, and proposes a novel approach for modeling incomplete and in accurate information.

2003

13.  Scalable location management for context-aware systems (2003)

This paper presents a location management system able to gather process and manage location information from a variety of physical and virtual location sensors. The system scales to the complexity of context-aware applications, to a variety of types and large number of location sensors and clients, and to geographical size of the system.

14.  Generating Context management infrastructure form high level context models

This paper presents a context modeling approach that offers a means for developers to describe and program with context at a high level, without the need to consider issues related to context gathering, management or representation. It also describes a mapping process that transforms high-level context models to management systems capable of maintaining and supplying context information to applications at run-time.

15.  Experiences in Using CC/PP in context-aware systems

The proposed context model is based on the CC/PP standard proposed to support context negotiation between web browsers and servers. They have defined a set of CC/PP components and attributes that allow expressing a variety of context information types and relationships between context descriptions.

2002

16.  Modeling context information in pervasive computing systems(2002)

This paper is concerned with the development of appropriate context modeling concepts for pervasive computing, which can form the basis for such a context management infrastructure. This model overcomes problems associated with previous context models, including their lack of formality and generality, and also tackles issues such as wide variations in information quality, the existence of complex relationships amongst context information and temporal aspects of context.

2001

17.  Infrastructure for pervasive computing: challenges (2001)

This paper presents our vision of pervasive computing and enumerates the software engineering challenges involved in realizing this vision. It also evaluates the current state of research and presents an agenda for future investigations in pervasive computing.

MIT — Oxygen

Oxygen 

1. “Pervasive computing: a paradigm for the 21st century” — Debashis Saha
The project rests on an infrastructure of mobile and stationrary devices connected by a self-configuring network. This infrastructure supplies abundant computation and communication, which are harnessed through system, perceptual, and software technologies to meet user needs.

The Oxygen project is focusing on eight environment-enabling technologies. Its emphasis is on understanding what turns an otherwise dormant environment into an empowered one to which users shift parts of their tasks.

Octber Report (Ontology, RDF, OWL, RML, SWRL, FOL, DL)

October Report

At first, I just want to know RDF and ontology, both of which often appear in papers about modeling contextual information. Ontology is a philosophical term, which describes the real entities. In computer science, ontology is used to describe objects and relationship between them. It supports common term knowledge base for information interchange. OWL is a language to explicitly represent the meaning of the terms on the web.
RDF is a data model to represent objects and their relationships by XML syntax and provides a simple semantics.

After representing information, I moved into the field of reasoning: which techniques are applied to reason with RDF data. Associating with OWL, Description logic describes the concept in a domain and the logic-based semantics given by a translation into first-logic predicate logic. Then I looked throught the introduction of two rule languages: RML and SWRL.
I. Ontology

1. What is the aim for ontology:

Ontology tries to find out what entities and what types of entities exist. Ontology has strong implications for the conceptions of reality.

2. What is described in ontology:

Finding – a subject, a relationship, and an object to talk about.

3. What types are classified with ontology:

• Foundation ontology: ontology attempts to describe general entities;

• Domain ontology: ontology is tied to a specific domain.

II. RDF

1. RDF is a data model for objects (“resources�) and relations between them, and provides a simple semantics of this data model, and these data models can be represented in XML syntax.

2. RDF schema is a vocabulary for describing properties and classes of RDF resources, with a semantics for generalization-hierarchies of such properties and classes.

III. OWL – Web Ontology Language

1. OWL is designed for use by applications that need to process the content of information. OWL facilitates greater machine interpretability of web content by providing additional vocabulary along with a formal semantics.

2. OWL and ontology:OWL can be used to explicitly represent the meaning of terms in vocabularies and the relationships between those terms. The representation of terms and their interrelationships is called ontology.

3. XML provides a surface syntax for structured documents, but imposes no semantic constraints on the meaning of these documents. XML schema is a language for restricting the structure of XML documents and also extends XML with datatypes.

4. OWL is modeled through an OO approach, and the structure of a domain is described in terms of classes and properties. From a formal point of view, OWL can be seen to be equivalent to description logic, which allows OWL to exploit the considerable existing body of DL reasoning including class consistency and consumption, and other ontological reasoning.

IV. First-order logic

1. FOL – First-Order Logic permits the formulation of quantified statements such as “there exists an x such that…� or “for any x, it is the case that…� where x is a member of the domain of discourse. A first-order (recursively-) axiomatisable theory is a theory that can be axiomatised as an extension of extension of first-order logic by adding a recursively enumerable set of first-order sentences as axioms.

2. First-order logic is mathematical logic that is distinguished from higher-order logic in that it does not allow quantification over properties. First-order logic is a strong enough to formalize all of set theory and thereby virtually all of mathematics. Its restriction to quantification over individuals makes it difficult to use for the purpose of topology. It is a stronger theory than sentential logic, but a weaker theory than second-order logic.

V. Description Logic

1. DL allows specifying a terminological hierarchy using a restricted set of first-order formulas. The equivalence of OWL and DL allows OWL to exploit the considerable existing body of DL reasoning fulfill important logical requirements, including concept satisfiability, class subsumption, class consistency, and instance checking.

2. DL means: (1) concept descriptions used to describe a domain; (2) the logic-based semantics which can be given by a translation into first-logic predicate logic. DL was designed as an extension to frames and semantic networks which were not equipped with a formal logic-based semantics.

VI. RML

1. RML – Rule Markup Language: to permit both forward and backward rules in XML for deduction, rewriting, and further inferential-transformational tasks: web-based rule storage, interchange, retrieval, and firing/application.

V. SWRL

1. SWRL – Semantic Web Rule Language: SWRL includes a high-level abstract syntax for Horn-like rules in both the OWL DL and OWL Lite sublanguages of OWL. A model-theoretic semantics is given to provide the formal meaning for OWL ontology including rules written in this abstract syntax.

2. The proposed rules are of the form of an implication between an antecedent (body) and consequent (head). The intended meaning can be read as: whenever the conditions specified in the antecedent hold, then the conditions specified in the consequent must also hold.The syntax for SWRL in this section abstracts from any exchange syntax for OWL and thus facilitates access to and evaluation of the language. This syntax extends the abstract syntax of OWL described in the OWL Semantics and Abstract Syntax document.