Context ? situations ? policy - PowerPoint PPT Presentation

Loading...

PPT – Context ? situations ? policy PowerPoint presentation | free to download - id: 201318-ZDc1Z



Loading


The Adobe Flash plugin is needed to view this content

Get the plugin now

View by Category
About This Presentation
Title:

Context ? situations ? policy

Description:

Public infrastructure stores persistent data (painting images, guest book) 19th July 2004 ... guest book, group repository. Build middleware that combines the ... – PowerPoint PPT presentation

Number of Views:12
Avg rating:3.0/5.0
Slides: 19
Provided by: dancu7
Category:

less

Write a Comment
User Comments (0)
Transcript and Presenter's Notes

Title: Context ? situations ? policy


1
Context ? situations ? policy
  • Daniel Cutting, Aaron Quigley
  • University of Sydney

2
Introduction
  • Daniel Cutting
  • Ph.D. candidate at University of Sydney (Aaron
    Quigley supervisor, John Zic associate
    supervisor)
  • Part of the Smart Internet CRC
  • About half-way through Ph.D.
  • Thesis area application collaboration in
    pervasive computing environments

3
Outline
  • Pervasive computing
  • Motivating scenario (art gallery)
  • Middleware
  • data distribution policies
  • Context spaces
  • Application to scenario
  • Discussion

4
Pervasive computing
  • Mobile devices (constrained, wireless) fixed
    infrastructure (powerful, wireline)
  • Hypothesis applications in PCEs can be improved
    using context
  • maximise availability of data
  • minimise battery usage and network traffic
  • constrained by user preferences
  • use context to aid data distribution

5
Art gallery scenario
Bob was here.
Gillian
Edward
Bob
Cynthia
Sunflowers, Van Gogh
Bob was here.
6
Art gallery scenario
  • Guide publishes data that is pushed to students
    (marking image of painting)
  • Repository shared by group stores long-lived data
    (group photo)
  • Public infrastructure stores persistent data
    (painting images, guest book)

7
Middleware
  • Publish-subscribe good for events
  • markings on painting image
  • Tuple spaces good for data persistence
  • guest book, group repository
  • Build middleware that combines the two

8
Middleware distribution
  • Distributing/storing data is a problem
  • many devices, some small, wireless
  • may have powerful fixed infrastructure, but
    sometimes purely ad hoc networks
  • Middleware needs flexible data distribution and
    storage policy
  • Use context to aid this policy

9
Context
  • Sensed/inferred values from environment, network,
    devices, applications and users
  • e.g. beacons, bandwidth, storage capacity, usage
    patterns, preferences
  • Complex to base policy on raw context
  • interpose symbolic situations
  • context ? situations ? distribution policy

10
Context spaces
  • Treat context as n-dimensional space
  • Each dimension is type of context
  • e.g. bandwidth, storage capacity
  • sample context vector might be high,low
  • Specific situation vectors also exist (statically
    specified or learnt over time)
  • Find nearest situation vector to convert
    context vectors to situation

11
Context spaces
12
Dynamic clustering
  • Dont specify situation vectors
  • Cluster context vectors to automatically identify
    inherent situations
  • How should policy act if no situations exist
    until run-time?
  • Situations can shift over time to reflect changes
    to contextual sources

13
Scenario context ? situations
  • Decentralised
  • each device determines own context
  • To build context space, designer identifies
    available context, e.g.
  • local power, bandwidth, storage
  • neighbours power, bandwidth, storage
  • size, priority, relevance, persistence of data
  • painting beacons, etc.

14
Scenario context ? situations
  • Select context for dimensions
  • data importance I, persistence P, size S
  • context vector is of form I,P,S
  • For static space, specify situations
  • signature, photo, demonstration
  • e.g. photo 0.1,0.8,0.8 is when data is not very
    important, persistent and large (like a
    photograph)

15
Scenario situations ? policy
  • A device putting data into the middleware system
    can
  • store locally, broadcast, broadcast digest
  • Make distribution policy using situations
  • signature ? broadcast
  • photo ? digest
  • demonstration ? store

16
Scenario context ? policy
Group photo at Sunflowers
Group photo at Sunflowers
Group photo at Sunflowers
Nearest situation vector is photo photo ? digest
Unimportant (0.2) Long-lived (0.7) Large size
(0.9)
17
Discussion
  • Representing nominal and cyclic dimensions is
    troublesome
  • Can situations ? policy be automated in clustered
    context space?
  • Unknown values in context vectors could cause
    spurious results - project to lower dimensions?

18
Static classification
  • During design-time
  • manually specify situation vectors
  • During run-time
  • measure raw context
  • determine context vector
  • find nearest situation vector based on a metric
    such as Euclidean distance
  • space is not altered - essentially a lookup
About PowerShow.com