Transversal Issues in Real-Time Sense-and-Respond Systems Ahmad T. Al-Hammouri Vincenzo Liberatore...
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Transcript of Transversal Issues in Real-Time Sense-and-Respond Systems Ahmad T. Al-Hammouri Vincenzo Liberatore...
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.
6/5/2005 Ahmad Al-Hammouri EESR '05
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Real-Time S&R Objective
Tele-epistemological vision Networked S&R 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
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Our contributions
Formulate Real-Time S&R for Networks research Middleware demonstration Playback buffers Congestion control Work in-progress
Multihoming, implementation, etc.
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6/5/2005 Ahmad Al-Hammouri EESR '05
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Real-Time S&R and Networks
Real-Time S&R 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
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Main thesis
Networks research is critical for Real-Time S&R Playback buffers Congestion control Quality-of-Service
Major technology gap Multimedia streaming, anyone?
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Transversal issues
S&R control environments: Radically differ in complexity and in applications Include hierarchical levels of abstraction
Transversal issues Address the necessity of providing QoS for S&R These are:
Adaptability and tolerance Congestion control Security, fault tolerance, etc.
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Transversal issues
We are currently involved in @ Case: Adaptability and tolerance Congestion control
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Adaptability and tolerance
S&R systems must be adaptable to Delays Jitter
R
S
d2
d1
d3 di
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Adaptability and tolerance (cont.)
.di ’s vary randomly
Decompose di as di = τ + ξi
.τ : the nominal round-trip delay (predictable across i) .ξi : the variation (jitter) in every round-trip time delay
Two subproblems: Predictable delays Jitter
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Adaptability and tolerance (cont.)
Predictable delays (ξi = 0, di = τ) 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
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Networkdelay
Packetarrival
Playback buffersS
eque
nce
num
ber
Packetgeneration
Buffer
Playback
Time Adapted from:Peterson & Davie
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Playback buffers: multimedia vs. S&R
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
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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
6/5/2005 Ahmad Al-Hammouri EESR '05
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Transversal issues
We are currently involved in @ Case: Adaptability and tolerance Congestion control
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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 }
r1
r2 r3
C1 = 2 C2 = 1
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Congestion control (cont.)
Define a Utility function, Ui(ri)
Performance of system i transmitting at rate ri
Mathematical formulation
max Σ U(ri)
s.t. Σ ri ≤ Cl , l = 1,…, L
and ri ≥ rmin,i
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Congestion control (cont.)
Source Sinkqueuen
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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 S&R
r
U(A,r)
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Additional directions
Implement these methods Middleware vs. lower-level layers
Exploit transport layer protocols SCTP: Multihoming and reliability to S&R
Power management control
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Thank you
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