Programming Pervasive and Mobile Computing Applications: The TOTA Approach

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Programming Pervasive and MobileComputing
Applications The TOTA Approach

• Presented By Hector M Lugo-Cordero, MS
• EEL 6883

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Full Citation

• Authors Marco Mamei and Franco Zambonelli
• From Università di Modena e Reggio Emilia
• Title Programming pervasive and mobile computing
  applications The TOTA approach
• Published at ACM Transactions on Software
  Engineering and Methodology (TOSEM), vol. 18,
  issue 4, July 2009

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Agenda

• Introduction
• Essentials
• Programming
• Evaluation
• Conclusions
• References

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Agenda

• Introduction
• Essentials
• Programming
• Evaluation
• Conclusions
• References

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The Problem

• Information processing is incorporated into
  everyday objects
• Agents can come and leave at any time
• Information is context (environment) dependent
• Need for a simple programming framework

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TOTA

• A tupple oriented middleware
• Tuples are injected into the network
• No central common space

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Case Study Scenario

• Imagine a huge museum like Le Louvre on France
• Many tourists come per day
• Makes hard for the management of services and
  information
• Assume every user has a wireless-enabled computer
• Museum layout can change over time and people
  come and go as they want

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Current Approaches

• Direct communication
• Communicate with other agents is direct (i.e.
  hardcoded)
• Not very dynamic
• Shared data-space
• Hard coordination
• Event base
• Notifications needed
• These are general (no context awareness)

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Agenda

• Introduction
• Essentials
• Programming
• Evaluation
• Conclusions
• References

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The TOTA Approach

• Gathers elements from both tuple-based and
  event-base models
• Distributed tuples injected to the network are
  cloned and propagated across the network
• A peer-to-peer network, each node running TOTA is
  the space with limited neighbors
• Tuples structure
• T (C, P, M)
• C content, P propagation, M maintenance

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TOTA Example (Information)
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TOTA in Le Louvre

• Assumption that there is a large wireless
  network, with a backbone
• How to provide information and planning to avoid
  queues
• ArtPiece
• C (description, location, distance)
• P Propagate to all peers increasing distance
• M update if topology changes

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Solutions (Information)

• Solution 1
• Art pieces propagate tuples
• Tourists query for the one with lower distance
  value
• Solution 2
• Art pieces do not propagate tuples
• Users query for information
• Art pieces reply

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TOTA Example (Meeting)
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Solution (Meeting)

• Meeting
• C (tourist_name, distance)
• P propagate to all peers, increase distance by
  one
• M update the distance tuple upon tourist move
• Tourist are guided with a GUI to the same place
• using the highest distance
• recursive process
• No coordination is specified by TOTA

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TOTA Architecture
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Agenda

• Introduction
• Essentials
• Programming
• Evaluation
• Conclusions
• References

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TOTA Implementation

• Java based
• Using 802.11b broadcast
• Avoid unicast handshake
• Deployed emulator to increase network size
• Only 16 PDAs and some laptops were used
• The same code of the emulator could be used on
  devices
• Emulator ran in mixed modes (real and emulated
  devices)

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TOTA Requirements

• What are the primitives that interact with the
  middleware?
• How to specify tuples T (C, P, M)?
• How to code coordinated and context-aware
  activities?

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TotaTuple
public class MyTuple extends TotaTuple,
implements ReactiveComponent //ReactiveComponent
exposes the react() method TotaTuple myTuple
new MyTuple(new ObjectHello)
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Tota API
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TOTA Predefined Tuples
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Programming ArtAgent1
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Programming TouristAgent1
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Programming ArtAgent2
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Programming TouristAgent2
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Programming MeetingAgent
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Agenda

• Introduction
• Essentials
• Programming
• Evaluation
• Conclusions
• References

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Software Engineering Analysis

• Context information makes TOTA general but more
  difficult for agents to react
• Separation of tuples (context) and agents (logic)
  however simplify this
• Incorporation of command and template design
  patterns facilitate tuple programming

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Tuple Propagation/Deletion Evaluation

• Highly scalable since only propagate to its
  immediate neighbors
• Tu Trcv Tprop Tsend Ttravel
• Propagation Time on a WiFi PDA (IPAQ 400 MHz)
• Tprop 99.7 ms
• Tsend 67.2 ms
• Ttravel 0 ms
• Trcv 21.2 ms
• Tu 188.1 ms

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Tuple Propagation/Deletion Evaluation (cont.)

• For X hops TXU XTU
• In practice is a little more (1020 from mean)
• Only HotTuples/MetricTuples and SpaceTuples were
  affected by topology

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Load and Memory Evaluation

• Load is accounted to local agent execution and
  propagation/maintenance rules
• Storage is small enough for micro-sensors, but
  requires each one to store it
• Java implementation leaves TOTA opened for
  improvements in an optimized C version

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Agenda

• Introduction
• Essentials
• Programming
• Evaluation
• Conclusions
• References

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Conclusions

• TOTA support pervasive and mobile applications
• By using distributed tuples so agents can
• Extract contextual information
• Coordinate each other
• Dynamically adjusts as topology changes
• TOTA weaknesses
• Strict structure (hard mapping)
• Security and privacy issues
• Complex operations arent very supported

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My Thoughts

• Strengths
• TOTA seems like a powerful, portable API
• Weaknesses
• Authors claimed that it is context independent
  but only the museum scenario was used
• Unclear mapping on how to transform real problems
  to TOTA tuples
• Suggestions
• Adding flow of traffic by layer to see how to
  interpret the pool of tuples over the network
• Demonstrate the application on different domains,
  and give a clearer mapping
• Implementation in C for devices that do not
  posses a JVM
• Include wired backbone

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Agenda

• Introduction
• Essentials
• Programming
• Evaluation
• Conclusions
• References

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References

• http//www.wikipedia.org
• http//www.agentgroup.unimo.it/wiki/index.php/TOTA
  
• http//www.agentgroup.unimo.it/wiki/images/2/21/Tu
  torial.pdf
• http//www.agentgroup.unimo.it/wiki/images/8/8b/To
  ta.zip

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Questions