A User-centric Task Computing Architecture for Pervasive Computing

2008 ◽  
Author(s):  
Faqun Jiang ◽  
Jintao Li ◽  
Zhenmin Zhu
Keyword(s):  
Pervasive Computing ◽  
Computing Architecture ◽  
User Centric

A pervasive computing architecture fostering integration in patient centred communities of care

2009 ◽  
Vol 10 (1/2) ◽  
pp. 49
Author(s):  
Federico Cabitza ◽  
Marco P. Locatelli ◽  
Marcello Sarini ◽  
Carla Simone
Keyword(s):  
Pervasive Computing ◽  
Computing Architecture

Secure and Private Service Discovery in Pervasive Computing Environments

2010 ◽  
Vol 2 (3) ◽  
pp. 46-59
Author(s):  
Feng Zhu ◽  
Wei Zhu
Keyword(s):  
Pervasive Computing ◽  
Service Discovery ◽  
Service Providers ◽  
Code Word ◽  
Sensitive Information ◽  
Word Form ◽  
Essential Step ◽  
Pervasive Service ◽  
Computing Environments ◽  
User Centric

With the convergence of embedded computers and wireless communication, pervasive computing has become the inevitable future of computing. Every year, billions of computing devices are built. They are ubiquitously deployed and are gracefully integrated with people and their environments. Service discovery is an essential step for the devices to properly discover, configure, and communicate with each other. Authentication for pervasive service discovery is difficult. In this chapter, we introduce a user-centric service discovery model, called PrudentExposure, which automates authentication processes. It encodes hundreds of authentication messages in a novel code word form. Perhaps the most serious challenge for pervasive service discovery is the integration of computing devices with people. A critical privacy challenge can be expressed as a “chicken-andegg problem”: both users and service providers want the other parties to expose sensitive information first. We discuss how a progressive and probabilistic model can protect both users’ and service providers’ privacy.

Pervasive Computing Architecture, Key Technologies and Issues Facing

2011 ◽  
Vol 135-136 ◽  
pp. 684-687
Author(s):  
Dai You Jiang
Keyword(s):  
User Interface ◽  
Embedded Systems ◽  
Pervasive Computing ◽  
Context Aware ◽  
Computing Architecture ◽  
Key Technology ◽  
Adaptive Technology ◽  
Key Technologies ◽  
Database Technology

This paper introduces the concept of pervasive computing, architecture, outlines the key technology of pervasive computing, including: middleware, context-aware technology, database technology, user interface technology, embedded systems technology and adaptive Technology, points out the major issues facing pervasive computing.

Embedding expression: Pervasive computing architecture for art and entertainment

2006 ◽  
Vol 2 (1) ◽  
pp. 1-36 ◽  
Author(s):  
Jeff Burke ◽  
Jonathan Friedman ◽  
Eitan Mendelowitz ◽  
Heemin Park ◽  
Mani B. Srivastava
Keyword(s):  
Pervasive Computing ◽  
Computing Architecture

Secure and Private Service Discovery in Pervasive Computing Environments

2011 ◽  
pp. 229-243
Author(s):  
Feng Zhu ◽  
Wei Zhu
Keyword(s):  
Pervasive Computing ◽  
Service Discovery ◽  
Service Providers ◽  
Code Word ◽  
Sensitive Information ◽  
Word Form ◽  
Essential Step ◽  
Pervasive Service ◽  
Computing Environments ◽  
User Centric

With the convergence of embedded computers and wireless communication, pervasive computing has become the inevitable future of computing. Every year, billions of computing devices are built. They are ubiquitously deployed and are gracefully integrated with people and their environments. Service discovery is an essential step for the devices to properly discover, configure, and communicate with each other. Authentication for pervasive service discovery is difficult. In this chapter, we introduce a user-centric service discovery model, called PrudentExposure, which automates authentication processes. It encodes hundreds of authentication messages in a novel code word form. Perhaps the most serious challenge for pervasive service discovery is the integration of computing devices with people. A critical privacy challenge can be expressed as a “chicken-and-egg problem”: both users and service providers want the other parties to expose sensitive information first. We discuss how a progressive and probabilistic model can protect both users’ and service providers’ privacy.

Sign in / Sign up

Export Citation Format

Share Document