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
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Introduction
objective, motivation, approach
literature review
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Distributed operating systems & file systems,
distributed applications, context.
initial model
papers, future plans.
Introduction
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Earlier distributed systems used fixed machines
and networks
portables led to ‘offline’ operation
mobile devices led to ad hoc networks and weak
connectivity
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Want to run applications across them
need to share data.
Objective
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Hypothesis: sharing of data between mobile
devices can be improved by using context
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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
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Build data sharing model for experiments
test various data distribution policies
run simulations, but maybe also a prototype
build simple applications
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Test general data availability.
Distributed operating systems
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Abstraction: thread/storage not processor/network
Amoeba: server/terminal, processor pool
Sprite: distributed over terminals
distributed virtual machines: cJVM, Jupiter, …
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MagnetOS: distributes objects around sensor
network
works for some applications in some environments.
generally brittle for mobile environments.
Distributed file systems
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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
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Why not distribute at application level?
application components + communication
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RPC/RMI, sockets, …
mobile devices weakly connected, so want
decoupled communication
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Middleware.
Publish-subscribe systems
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Clients receive events matching subscriptions
anonymous, decoupled
cannot ‘store’ data
Elvin
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Federation, quenching.
Tuple spaces
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Linda
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anonymous, decoupled, can store data
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Tuple: <a,b,c>, tuple space contains tuples
OUT(t), IN(t), RD(t).
but no notifications
LIME: Linda in a Mobile Environment
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Merging/separation of tuple spaces.
Context
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Bottom-up (sensors, aggregated, inferred)
top-down (user preferences, input)
use of context often ad hoc, hard to reuse
so, formalise
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CSCP: structured, interchangeable,
(de)composable, uniform, extensible, standardised
Context Toolkit: GUI-like widgets + generators,
interpreters, servers.
Model
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Design data sharing model around middleware
generalise for more types of apps: “Middies”
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distribute blocks according to a policy
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Members, spaces, blocks, reactors, matchers.
Full, server, random, context-aware.
context:
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Device: battery, storage
application/user: access patterns, directives.
Papers
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“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
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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]