PERVASIVE COMPUTING MIDDLEWARE BY SCHIELE, HANDTE, AND BECKER A Presentation by Nancy Shah.

Slides:



Advertisements
Similar presentations
Annual Conference of ITA ACITA 2009 Realising Management and Composition of Self-Managed Cells in Body Area Networks Alberto Schaeffer-Filho, Emil Lupu,
Advertisements

MicroKernel Pattern Presented by Sahibzada Sami ud din Kashif Khurshid.
TU/e Service Discovery Mechanisms: two case studies / IC2002 Service Discovery Mechanisms: Two case studies Control point Device UPnP Terminal Domain Host.
Service-Based Paradigm Anchoring the Indefinable Field Of Pervasive Computing Presenter: Vijay Dheap.
Programming Languages for End-User Personalization of Cyber-Physical Systems Presented by, Swathi Krishna Kilari.
Sharing Content and Experience in Smart Environments Johan Plomp, Juhani Heinila, Veikko Ikonen, Eija Kaasinen, Pasi Valkkynen 1.
Agreement-based Distributed Resource Management Alain Andrieux Karl Czajkowski.
A Pervasive Reminder System for Smart Homes Sylvain GIROUX and Simon GUERTIN Département d’informatique, Université de Sherbrooke 2500 boul. Université,
Fraunhofer FOKUS Context Management in Dynamic Environments IWCMC 2009, June 2009 Jens Tiemann Humberto Astudillo Evgenij Belikov Fraunhofer Institute.
Martin Wagner and Gudrun Klinker Augmented Reality Group Institut für Informatik Technische Universität München December 19, 2003.
Model for Supporting High Integrity and Fault Tolerance Brian Dobbing, Aonix Europe Ltd Chief Technical Consultant.
Asa MacWilliams Lehrstuhl für Angewandte Softwaretechnik Institut für Informatik Technische Universität München Dec Software.
Transparent Environment for Replicated Ravenscar Applications Luís Miguel Pinho Francisco Vasques Ada-Europe 2002 Vienna, Austria June 2002.
Network Management Overview IACT 918 July 2004 Gene Awyzio SITACS University of Wollongong.
The PERSONA Service Platform for AAL Spaces Mohammad-Reza Tazari, Rancesco Furfari, Juan-Pablo Lazaro Ramos, and Erina Ferro Presented By: Omar Nachawati.
. Smart Cities and the Ageing Population Sustainable smart cities: from vision to reality 13 October ITU, Geneva Knud Erik Skouby, CMI/ Aalborg University-Cph.
RCSM, David Buchmann Seminar Ubicomp, Uni Fribourg Reconfigurable Context Sensitive Middleware Smart Classroom Tasks RCSM Parts Critics Presentation.
Terminal Bridge Extension Over Distributed Architecture MSc. Sami Saalasti.
PROGRESS project: Internet-enabled monitoring and control of embedded systems (EES.5413)  Introduction Networked devices make their capabilities known.
ATSN 2009 Towards an Extensible Agent-based Middleware for Sensor Networks and RFID Systems Dirk Bade University of Hamburg, Germany.
SensIT PI Meeting, April 17-20, Distributed Services for Self-Organizing Sensor Networks Alvin S. Lim Computer Science and Software Engineering.
What is adaptive web technology?  There is an increasingly large demand for software systems which are able to operate effectively in dynamic environments.
Emerging Research Dimensions in IT Security Dr. Salar H. Naqvi Senior Member IEEE Research Fellow, CoreGRID Network of Excellence European.
1 FM Overview of Adaptation. 2 FM RAPIDware: Component-Based Design of Adaptive and Dependable Middleware Project Investigators: Philip McKinley, Kurt.
Community Manager A Dynamic Collaboration Solution on Heterogeneous Environment Hyeonsook Kim  2006 CUS. All rights reserved.
Smart Home Technologies CSE 4392 / CSE 5392 Spring 2006 Manfred Huber
Anthony D. Wood, John A. Stankovic, Gilles Virone, Leo Selavo, Zhimin He, Qiuhua Cao, Thao Doan, Yafeng Wu, Lei Fang, and Radu Stoleru University of Virginia.
THE NEXT STEP IN WEB SERVICES By Francisco Curbera,… Memtimin MAHMUT 2012.
SensIT PI Meeting, January 15-17, Self-Organizing Sensor Networks: Efficient Distributed Mechanisms Alvin S. Lim Computer Science and Software Engineering.
How to connect non IP devices into the UPnP™v1 fabric Vijay Dhingra Director of Standards Echelon Corp.
Software Architecture Framework for Ubiquitous Computing Divya ChanneGowda Athrey Joshi.
Wireless Access and Terminal Mobility in CORBA Dimple Kaul, Arundhati Kogekar, Stoyan Paunov.
CPET 565 Mobile Computing Systems Context-Aware Computing (2) Lecture 11 Hongli Luo Indiana University-Purdue University Fort Wayne.
Linked-data and the Internet of Things Payam Barnaghi Centre for Communication Systems Research University of Surrey March 2012.
A Survey on Programming Model Context Toolkit Gaia ETC (of Equator Project) Tentaculus.
Page 1 WWRF Briefing WG2-br2 · Kellerer/Arbanowski · · 03/2005 · WWRF13, Korea Stefan Arbanowski, Olaf Droegehorn, Wolfgang.
Introduction Infrastructure for pervasive computing has many challenges: 1)pervasive computing is a large aspect which includes hardware side (mobile phones,portable.
Usable Security – CS 6204 – Fall, 2009 – Dennis Kafura – Virginia Tech Principles of Context aware systems Presented by: Rajesh Gangam Usable Security.
A Context Model based on Ontological Languages: a Proposal for Information Visualization School of Informatics Castilla-La Mancha University Ramón Hervás.
1 BRUSSELS - 14 July 2003 Full Security Support in a heterogeneous mobile GRID testbed for wireless extensions to the.
Master Course /11/ Some additional words about pervasive/ubiquitous computing Lionel Brunie National Institute of Applied Science (INSA)
Application of Operating System Concepts to Coordination in Pervasive Sensing and Computing Systems Benjamin J. Ewy, Larry M. Sanders Ambient Computing,
Distribution and components. 2 What is the problem? Enterprise computing is Large scale & complex: It supports large scale and complex organisations Spanning.
Ontology Mapping in Pervasive Computing Environment C.Y. Kong, C.L. Wang, F.C.M. Lau The University of Hong Kong.
An Architecture to Support Context-Aware Applications
Dynamic Synthesis of Mediators in Pervasive Environments Amel Bennaceur supervised by Valérie Issarny ARLES 14 February 2012, Junior Seminar, INRIA.
Internet of Things. IoT Novel paradigm – Rapidly gaining ground in the wireless scenario Basic idea – Pervasive presence around us a variety of things.
SelfCon Foil no 1 Variability in Self-Adaptive Systems.
Providing web services to mobile users: The architecture design of an m-service portal Minder Chen - Dongsong Zhang - Lina Zhou Presented by: Juan M. Cubillos.
SensorWare: Distributed Services for Sensor Networks Rockwell Science Center and UCLA.
CIMA and Semantic Interoperability for Networked Instruments and Sensors Donald F. (Rick) McMullen Pervasive Technology Labs at Indiana University
A Survey of Various Middleware Architectures Bhavyan Mehta, Sumeet Maru, Varun Jobanputra.
March 2004 At A Glance The AutoFDS provides a web- based interface to acquire, generate, and distribute products, using the GMSEC Reference Architecture.
Fuego Core 2005/7 Possible Directions Kimmo Raatikainen Principal Scientist Helsinki Institute for Information Technology
Towards ‘Ubiquitous’ Ubiquitous Computing: an alliance with ‘the Grid’ Oliver Storz, Adrian Friday, and Nigel Davies Computing Department, Lancaster University,
INTRODUCTION TO GRID & CLOUD COMPUTING U. Jhashuva 1 Asst. Professor Dept. of CSE.
By Jeremy Burdette & Daniel Gottlieb. It is an architecture It is not a technology May not fit all businesses “Service” doesn’t mean Web Service It is.
Software Architecture of Sensors. Hardware - Sensor Nodes Sensing: sensor --a transducer that converts a physical, chemical, or biological parameter into.
A Semi-Automated Digital Preservation System based on Semantic Web Services Jane Hunter Sharmin Choudhury DSTC PTY LTD, Brisbane, Australia Slides by Ananta.
Context-Aware Middleware for Resource Management in the Wireless Internet US Lab 신현정.
Mohd Rozaini Bin Abd Rahim, Norsheila Fisal, Rozeha A
Supporting Mobile Collaboration with Service-Oriented Mobile Units
Self Healing and Dynamic Construction Framework:
Context-Aware Computing
Distribution and components
Grid Computing.
Ambient Intelligence -by Internal Guide: M.Preethi(10C91A0563)
3rd Studierstube Workshop TU Wien
The Anatomy and The Physiology of the Grid
Self-Managed Systems: an Architectural Challenge
Presentation transcript:

PERVASIVE COMPUTING MIDDLEWARE BY SCHIELE, HANDTE, AND BECKER A Presentation by Nancy Shah

Vision of Pervasive Computing “Pervasive computing envisions applications that provide intuitive, seamless and distraction-free support for their users.” “… the applications combine and leverage the distinct functionality of a number of devices. Many of these devices are invisibly integrated into the environment.” “… provide high quality task support while putting only little cognitive load on users as the require only minimal manual input.”

Challenges to Application Developers  Unprecedented device heterogeneity  Unreliable wireless communication  Uncertainty in sensor readings  Unforeseeable execution environments  From static to highly dynamic  Changing user requirements  Fuzzy user preferences Development of pervasive applications in a non-trivial, time-consuming and error-prone task

Design Considerations  Organizational Model  Smart Environment Spatially limited area equipped with sensors and actuators Stationary devices Some devices are dynamically integrated Requires a powerful coordinating computer  Smart Peers Dynamically formed collection of peers Dynamic set of devices Decentralized: No coordinating computer More flexible, but more complicated

Design Considerations (cont.)  Provided Level of Abstraction  Full Transparency A completely generic solution All possible application scenarios  Configurable Automation Allows developer to forget about intrinsic problems Abstraction automates the task with some configuration  Simplified Exposure When configuration is no longer reasonable Restricted to automated gathering of information

Design Considerations (cont.)  Supported Tasks  Spontaneous Interaction Devices communicate with each other Detect and monitor the available set of devices  Context Management Coordinate measurements of multiple distributed sensors Fusion of data  Application Adaptation To the overall system properties To the available capabilities To the context of their users

Spontaneous Interaction  Ubiquitous Communication and Interaction  Interoperability Requires a common understanding of the semantics of shared functionalities Three main possibilities: Fixed Standardized Protocol Set Dynamically Negotiated Protocol Set Interaction bridges  Communication Abstractions Event Heap Remote Message Invocation

Spontaneous Interaction (cont.)  Integration of Heterogeneous Devices  Wide range of devices Different hardware/software Different capabilities and resources  Two different approaches Build multiple, yet compatible systems for different classes of devices Build modular systems with minimal yet extensible core

Spontaneous Interaction  Dynamic Mediation  Peer-based Discovery All nodes participate in the discovery together Clients can broadcast a discovery request Service providers can broadcast its services  Mediator-based Discovery Mediators manage a service registry for all devices Clients register services with the mediator Can coordinate entries with other mediators In absence of mediator no discovery is possible

Context Management  Definition of Context  Where you are  Who you are with  What resources are nearby  System adapts to context according to  Location of use  Collection of nearby people  Available network and computer infrastructure  Three Classes of Applications  Context-aware presentation  Automatic execution of a service  Tagging of context to information for later retrieval

Context Management (cont.)  Acquisition and Fusion  Accuracy Sensor readings are not a discrete value May deviate for another’s measurement of the same Sensors usually specify the mean and maximum error  Freshness Once the value is read, it begins aging The rate of change determines accuracy  Methods to improve accuracy Use multiple sensors or readings Use different technologies or perspectives

Context Management (cont.)  Modeling and Distribution  Costly  Sharing costs with other applications or institutions  Standardized interfaces Retrieved information must be interpreted across a number of applications  Standardized data Applications need to be able to interpret data

Context Management (cont.)  Provisioning and Access  Provides suitable abstractions for applications  Three classes of context for access Identity Location Time

Application Adaptation  Challenges  Integrating coordination of devices Different environments have different devices Set of devices changes over time Different devices can be used for same task  Coordination  Based on the target environment and the user  Able to adapt to many changes  Needs support at the middleware layer Not the application layer

Application Adaptation (cont.)  Inter-Application Adaptation  Several non-distributed applications  Applications are not aware of one another  Allows for reuse of traditional applications  Middleware can: Detect changes and adapt the set of applications Provide transparent transcoding services for user data Provide services to facilitate the interaction of applications  Issues Weak form of application coordination Cannot coordinate actions between applications when needed

Application Adaptation (cont.)  Intra-Application Adaptation  Single application distributed across several devices  Requires applications to run an application-defined building block  Middleware builds a model of the application using Individual building blocks Dependencies on one another Dependencies on environment  Issues Devices must be capable/willing to install additional code

Conclusion  Pervasive Applications  Provide seamless, intuitive, and distraction-free task support  Provide a set of supportive services Influenced by overall organization and targeted level of support  Heterogeneous Devices  Alleviates low-level communication issues  Handles details of gathering information from large numbers of sensors  Supports changing set of devices Intuitive Task Support is still a challenge as new devices and scenarios continue to emerge

Any Questions? Thanks!