Transversal Issues in Real-Time Sense-and-Respond Systems Ahmad T. Al-Hammouri Vincenzo Liberatore Huthaifa A. Al-Omari Case Western Reserve University

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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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


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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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Transversal Issues in Real-Time Sense-and-Respond Systems Ahmad T. Al-Hammouri Vincenzo Liberatore Huthaifa A. Al-Omari Case Western Reserve University