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Transversal Issues in Real-Time Sense-and-Respond Systems

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Title: Transversal Issues in Real-Time Sense-and-Respond Systems


1
Transversal Issues in Real-Time Sense-and-Respond
Systems
Ahmad T. Al-Hammouri Vincenzo Liberatore Huthaifa
A. Al-Omari Case Western Reserve
University Stephen M. Phillips Arizona State
University Support by NASA NAG3-2578,
NAG3-2799, NNC05CB20C, NNC04AA12A
NSF CCR-0329910 Department of Commerce TOP
39-60-04003.
2
Real-Time SR
  • Objective
  • Tele-epistemological vision
  • Networked SR extend human reach beyond spatial
    barriers
  • Remote control of physical environment by sense
    and respond
  • Potential Applications
  • Industrial automation
  • Automatic asset mgmt. (RFID)
  • Disaster Recovery
  • UAVs LNK03
  • Home robotics

3
Our contributions
  • Formulate Real-Time SR for Networks research
  • Middleware demonstration
  • Playback buffers
  • Congestion control
  • Work in-progress
  • Multihoming, implementation, etc.

4
(No Transcript)
5
Real-Time SR and Networks
  • Real-Time SR involve the physical environments
  • Real-Time objectives and constraints
  • Real-time objectives
  • Correctness, reliability, and safety
  • Flexibility, scalability, and efficiency
  • Communication networks
  • No timeliness or QoS guarantees BW limitation,
    losses, delays, and jitter
  • Focus has been on
  • Control theory, real-time systems, middleware,
    and data bases

6
Main thesis
  • Networks research is critical for Real-Time SR
  • Playback buffers
  • Congestion control
  • Quality-of-Service
  • Major technology gap
  • Multimedia streaming, anyone?

7
Transversal issues
  • SR control environments
  • Radically differ in complexity and in
    applications
  • Include hierarchical levels of abstraction
  • Transversal issues
  • Address the necessity of providing QoS for SR
  • These are
  • Adaptability and tolerance
  • Congestion control
  • Security, fault tolerance, etc.

8
Transversal issues
  • We are currently involved in _at_ Case
  • Adaptability and tolerance
  • Congestion control

9
Adaptability and tolerance
  • SR systems must be adaptable to
  • Delays
  • Jitter

10
Adaptability and tolerance (cont.)
  • .di s vary randomly
  • Decompose di as di t ?i
  • .t the nominal round-trip delay (predictable
    across i)
  • .?i the variation (jitter) in every round-trip
    time delay
  • Two subproblems
  • Predictable delays
  • Jitter

11
Adaptability and tolerance (cont.)
  • Predictable delays (?i 0, di t)
  • Methods to mitigate predictable delays
  • Sacrificing performance to preserve stability,
    e.g., robots teleoperation
  • Use of system models predict a future state
  • Jitter
  • Jitter causes inaccurate predictions in
    delay-compensation techniques
  • Playback buffers can eliminate jitter

12
Playback buffers
Packet
Sequence number
generation
Adapted from Peterson Davie
T
ime
13
Playback buffers multimedia vs. SR
  • Different performance metrics
  • Round-trip delay jitter
  • Playback delays are determined by controller
  • Controller is away from the host that applies the
    signal
  • Controller needs RTT to detect a delay spike

VoIP stream
14
Our contribution
  • Combined strategies of playback, control laws,
    and adaptive sampling
  • Controller determines playback delay based on RTT
    samples
  • Adaptive playback delay
  • Based on the playback delay, Controller
    determines
  • control signal, and
  • sampling rate

15
Transversal issues
  • We are currently involved in _at_ Case
  • Adaptability and tolerance
  • Congestion control

16
Congestion control
  • Match sources transmission rates to network
    capacity
  • Achieve fair bandwidth allocation between
    different flows
  • Example
  • S1 r1, r2, r3 0.5, 1.5, 0.5
  • S2 r1, r2, r3 0.25, 1.75, 0.75
  • S3 r1, r2, r3 0.0, 2.0, 1.0

17
Congestion control (cont.)
  • Define a Utility function, Ui(ri)
  • Performance of system i transmitting at rate ri
  • Mathematical formulation
  • max S U(ri)
  • s.t. S ri Cl , l 1,, L
  • and ri rmin,i

18
Congestion control (cont.)
queuen
Sink
Source
19
Our contribution
  • Choice of a utility function, Ui(Ai, ri)
  • Function of speed of physical dynamics, Ai
  • Monotonically increasing and strictly concave
    with ri
  • Tailoring the general optimization
    framework for SR

20
Additional directions
  • Implement these methods
  • Middleware vs. lower-level layers
  • Exploit transport layer protocols
  • SCTP Multihoming and reliability to SR
  • Power management control

21
Thank you
  • Comments
  • Questions
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