Identity Management & Nymity in the Intelligent Environment
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Transcript Identity Management & Nymity in the Intelligent Environment
Data availability in a
mobile environment
Daniel Cutting
University of Sydney & Smart Internet Technology CRC
Talk outline
Introduction
objective, motivation, approach
literature review
Distributed operating systems & file systems,
distributed applications, context.
initial model
papers, future plans.
Introduction
Earlier distributed systems used fixed machines
and networks
portables led to ‘offline’ operation
mobile devices led to ad hoc networks and weak
connectivity
Want to run applications across them
need to share data.
Objective
Hypothesis: sharing of data between mobile
devices can be improved by using context
Maximise availability of data to applications
minimise battery usage and network traffic
constrained by codified semantics and user policies
use relevant contextual information to aid sharing.
identify context appropriate to each situation
find heuristics for representing all situations.
Personal Persistent (PP)
Joint Transient (JT)
Communal Persistent (CP)
Approach
Build data sharing model for experiments
test various data distribution policies
run simulations, but maybe also a prototype
build simple applications
Test general data availability.
Distributed operating systems
Abstraction: thread/storage not processor/network
Amoeba: server/terminal, processor pool
Sprite: distributed over terminals
distributed virtual machines: cJVM, Jupiter, …
MagnetOS: distributes objects around sensor
network
works for some applications in some environments.
generally brittle for mobile environments.
Distributed file systems
Abstraction: file/directory (open/read/write/close)
Andrew: client/server, fully connected
Coda: Andrew + disconnected mode
Odyssey: ‘application-aware adaptation’
DFS is OK when network is stable, not so good
when transient.
Distributed applications
Why not distribute at application level?
application components + communication
RPC/RMI, sockets, …
mobile devices weakly connected, so want
decoupled communication
Middleware.
Publish-subscribe systems
Clients receive events matching subscriptions
anonymous, decoupled
cannot ‘store’ data
Elvin
Federation, quenching.
Tuple spaces
Linda
anonymous, decoupled, can store data
Tuple: <a,b,c>, tuple space contains tuples
OUT(t), IN(t), RD(t).
but no notifications
LIME: Linda in a Mobile Environment
Merging/separation of tuple spaces.
Context
Bottom-up (sensors, aggregated, inferred)
top-down (user preferences, input)
use of context often ad hoc, hard to reuse
so, formalise
CSCP: structured, interchangeable,
(de)composable, uniform, extensible, standardised
Context Toolkit: GUI-like widgets + generators,
interpreters, servers.
Model
Design data sharing model around middleware
generalise for more types of apps: “Middies”
distribute blocks according to a policy
Members, spaces, blocks, reactors, matchers.
Full, server, random, context-aware.
context:
Device: battery, storage
application/user: access patterns, directives.
Papers
“Middies: Passive Middleware Abstractions for Pervasive
Computing Environment”. With Adam Hudson and Aaron
Quigley. Submitted to ICPS 2004.
“BlueStar: Beacon + MPC based location detection”.
With Belinda Ward, Aaron Quigley, Chris Ottrey, Bob
Kummerfeld. To appear at IEEE PLANS 2004
“AR phone: Accessible Augmented Reality in the
Intelligent Environment”. With Adam Hudson, Mark
Assad and David Carmichael. Presented at OZCHI 2003.
Future plans
April 2004 - deeper context study completed
May 2004 - completed model design and
confirmed hypothesis
October 2004 - completed construction of model
November 2004 - journal paper
February 2005 - begin experiments
March 2006 - submit thesis.
Comments and questions
Daniel Cutting
University of Sydney
[email protected]