robust manet design john p. mullen, ph.d. timothy i. matis, ph.d. smriti rangan karl adams center...
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Robust MANET Design
John P. Mullen, Ph.D.
Timothy I. Matis, Ph.D.
Smriti Rangan
Karl Adams
Center for Stochastic Modeling
New Mexico State University
May 16, 2004
11/20/2003 2
What Are MANETS ?
A MANET is a mobile ad-hoc wireless communication network that is capable of autonomous operation• Each node is capable of transmitting,
receiving, and routing packets of information. • The network has no fixed backbone (such as
with the Internet and cellular phones) • The nodes are able to enter, leave, and move
around the network independently and randomly
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Mobile Ad Hoc Path Search
Y
XAB
I
G
EF
C
D
H
11/20/2003 4
Same MANET After a While
Y
XAB
I
G
EF
C
D
HH
X
I
G
FE
D
B
A
C
Y
11/20/2003 5
Types of Packets
• Control Packets – – RREQ’ s and RREP’s – Used to establish communication links
between the source and destination nodes. There are numerous protocols that have been proposed for their “optimal” use in finding reliable links at minimal bandwidth
– ACK’s – Used to ascertain the quality of a link and ensure successful communication. The destination node sends an acknowledgement (ack) packet back to the source after each successful data packet transmission.
• Data Packets– Contain the actual information that is to be communicated
broken up into “packets” of uniform size – Data packets are much larger than control packets
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Protocol Taxonomy
Single channel protocols
uniform
Destination based
reactiveproactive
topology-based
reactiveproactive
Non-uniform
partitioning
Neighbor selection
AODVTORAABR
DSDVWRP
DSR
GSR
CEDARCBRP
ZRPOLSR
11/20/2003 7
MANET Models
• Current MANET Models– Received power is a deterministic function of
distance
– Node communication (preceived pmin) is flawless within a nominal range, r0, and is not possible (preceived pmin) beyond this range
• In actuality, the received power process is highly stochastic due primarily to shadowing and fading
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Current Assumption:
Rec. Power is a deterministic function of distance
p(r)
Current vs. Observed
Field Measurements:
From Neskovic 2002 – Fig. 2
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Evaluating Protocols
• The deterministic power assumption is the default of most simulation software (OpNet, NS2, NAB) used to evaluate protocol performance
• The stochastic problem is typically viewed as a minor (and unimportant) nuisance by the CS and EE communities that design these protocols
11/20/2003 10
Rayleigh Fading
• The instantaneous received voltage in an inefficient, low power, and complex RF environment often follows a Rayleigh distribution
• As a result, it follows that received power is exponentially distributed
• Further, we assume power exponentially decays with distance
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PDF of Received Power
c
i
c
ip r
r
Fp
p
r
r
FppFcrrpf
i0min0min
min0 exp1
),,,,|(
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Initial Test Scenario
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Rec Power –Current Model
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Current vs Proposed Model
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Real Vs. MemorexInstantaneous Rec Power
-20
-10
0
10
20
30
0.5 1 1.5 2 2.5
r/r0
p/p_m
in (dB
)
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Impact on Link Throughput
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Findings
• Not all packets within nominal range are transmitted successfully
• Not all packets outside the range are unsuccessful
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Scenario Two – DSR Protocol
Source Relay Dest.
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RF Propagation Distances
Source Relay Dest.
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Throughput
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End-to-End Delay
Delay = 0.004 secIn no-fading model
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Route Discovery Time
One Route discoveryIn no-fading model
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Transmit Buffer Size
Buffer size is 2.0In no-fading model
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Hops per Route
1.5 hops average A-B: 1 hop A-C: 2 hops In no-fading model
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The Basic Problem
Source Relay Dest.
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Ping - Pong
2-hop 1-hop0.6
0.4
A B C A B C
0.8
0.20.995
1 - 0.46
0.0050.75
0.25 p2 = 2p1
p2 = 50p1
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Throughput vs. Tries
11/20/2003 28
Delay vs. Tries
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Buffer Size vs. Tries
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Findings• Only through accurate stochastic
simulations can 1. The true performance of existing protocols
be evaluated2. The parameters of these protocols be
optimized for robust performance 3. New robust protocols be developed
• Parameters not significant in deterministic models (such as packet retry) are important in stochastic models
11/20/2003 31
Robust MANET Design
• RSM may be used to optimize the performance of established protocols for the controllable parameters (F, number of TX tries, etc.) over the uncontrollable parameters (c, TX rate, etc.)
• As an example, consider optimizing the number of TX tries (1,2,3,4) over 2 levels of TX rate (71.5,143 in packets/sec) using throughput as a measure of performance
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Throughput (packets/sec)
Throughput (packets/sec)
0
10
20
30
40
50
60
0 1 2 3 4 5
Tries
Rep 1
Rep 2
Avg
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Throughput (High/Low Data Rates)
Throughput (Packets/sec)
0
20
40
60
80
0 1 2 3 4 5
Tries
71.5 P/sec
143 P/sec
11/20/2003 34
Relative Throughput
Relative Throughput
0%
20%
40%
60%
80%
100%
0 1 2 3 4 5
Tries
Rep 1
Rep 2
Avg
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Relative Throughput(High/Low)Relative Throughput
0%
20%
40%
60%
80%
100%
0 1 2 3 4 5
Tries
71.5 P/sec
143 P/sec
11/20/2003 36
Mean Delay
Mean Delay (sec)
0
1
2
3
0 1 2 3 4 5
Tries
Rep 1
Rep 2
Avg
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Mean Delay(High/Low)
Mean Delay (sec)
0
1
2
3
4
0 1 2 3 4 5
Tries
71.5 P/s
143 P/sec
11/20/2003 38
Mean Transmit Buffer Size
Mean Xmit Buffer Size
0
10
20
30
40
0 1 2 3 4 5
Tries
Rep 1
Rep 2
Avg
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Mean Total Bits Per Second
Mean Total Bits Per Second
0
50
100
150
200
0 1 2 3 4 5
Tries
Rep 1
Rep 2
Avg
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Mean Routing Bits per Second
Mean Routing Bits Per Second
02468
10121416
0 1 2 3 4 5
Tries
Rep 1
Rep 2
Avg
11/20/2003 41
Mean Non-Routing Bits
Mean Non-Routing Bits Per Second
0
50
100
150
200
0 1 2 3 4 5
Tries
Rep 1
Rep 2
Avg
11/20/2003 42
Questions ?
John [email protected]
Center for Stochastic Modellinghttp://engr.nmsu.edu/~csm