JENNA: a Jamming Evasive Network-coding Neighbor

Transcription

JENNA: a Jamming Evasive Network-coding Neighbor
“The point in which wireless personal PDAs and the related networks are
sufficiently computationally intelligent about radio resources and related
computer-to-computer communications to detect user communications
needs as a function of use context, and to provide radio resources and
wireless services most appropriate to those needs”, Mitola 2000.
“A Cognitive Radio is a radio that can change its transmitter parameters
based on interaction with the environment in which it operates”, FCC 2003.
Orient
Observe
The cognition
cycle
Outside
world
Asterjadhi
Plan
Learn
Act
Decide
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
Limited spectrum resources shared among:
› Cognitive radios (CRs)
 opportunistically access these resources
› Primary radios (PRs)
 Owners of the spectrum resources
 Assure interference-free communications
› Primary user emulation attackers (static jammers)
 Jam with a simil-PR signal for own communications
 Detection and neighbor advertisement
› Random hopping attackers (reactive jammers)
 Launch DoS attacks to CRs’ operation
 Prompt evasion of jammed channel
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Static jammer
PR
CR
PSD
Reactive jammer
time
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First step prior to network deployment

Before:
›
›
›
›

Learn about the wireless environment
Spectrum sensing to identify free channels
Gather data on spectrum utilization, QoS
Primary users and static jammers detection
During neighbor discovery:
› Estimation of number of CRs in the network
› Detection of reactive jammers’ presence

After:
› Cooperative spectrum sensing
› Network setup
› Channel allocation
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
Need not know actual number of nodes, n.
› Nodes know the label set size N and channels C

Follow deterministic channel hopping
patterns
› Use round-robin pattern easy to detect
› Easy for jammers to disrupt neighbor discovery
› Hopping pattern spans over all channels C

Guarantee neighbor discovery in finite time
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


Requires knowledge of number of nodes n
Nodes are globally time-synchronized (GPS)
Different pseudo-random hopping patterns
› Single Frequency Channel selection (Cfree = 1)
 Fast neighbor discovery
 Susceptible to reactive jamming attacks
› Random channel hopping (SLF scheme)
 Slow neighbor discovery
 Robust to jamming attacks
› Other hopping patterns with reduced neighbor
discovery delay but susceptible to jamming
attacks (internal jammers or compromised
nodes).
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
Randomized algorithm
› Nodes hop randomly over Cfree

Fully distributed
› No central entity for coordination

Plesio-chronous time-slotted architecture
› need no global time synchronization among
nodes
› synchronisation at the slot boundaries


Does not require to know n to terminate
Assure faster neighbor discovery w.h.p.
› discovery delay depends on number of nodes, n

Very robust to jamming attacks
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Orient
The cognition cycle
Observe
•Process acquired data
• Free
•Busy (CR ? Jammer)
Learn
Scanning
phase
Wireless
environment
Cfree
Process received
packet
Estimate
•
• number of CRs, n
• Timeout Tout
• buffer rank
• Transmit
•Defer Tx
Act
Asterjadhi
Plan
•Allocate resources
• Create packet
• Tout , rank, n
Decide
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Network coding is a particular in-network data processing
technique that exploits the characteristics of the wireless medium
in order to increase the capacity or the throughput of the
network.
.
Terminology
Canonical example
 Communication network =
finite directed graph
Acyclic communication network =
network without any direct cycle
 Source node = node with no
incoming edges (square)
 Channel = noiseless communication
link for the transmission of a data unit
per unit time (edge).
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R
B
PA, PB
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Slot 4
Slot 3
Slot 2
Slot 1
A
PA, PB
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R
B
Slot 3
Slot 2
Slot 1
A
PA, PB
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PA, PB
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
Send the encoding vector within the same packet


Packetization: Header removes need for centralized
knowledge of graph topology and encoding/decoding functions
Nodes stores within their buffers the received packets

Buffering: Allows asynchronous packets arrivals & departures
with arbitrarily varying rates, delay, loss
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Full characterization of the spectrum resources
• Randomly hop over all channels Ctot
• Detect the presence of Primary Radios
• Detect Static jammers
Begin neighbor discovery and estimation of local variables
• Randomly hop over all channels Cfree
• Every received packet stores in the header CR ids
• all CRs ids that participated on packet creation (estimate n)
• Estimate Tout: all CRs have met and advertised their R duration
End neighbor discovery
• Randomly hop over all channels Cfree
• Node can decode buffer content
• Locally activate Tout (Unsync)
•Transmit packets with decreasing common Tout value (Sync)
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channels
nodes
5
5
4
3
2
1
10
J1
7
6
P1
J1
8
8
J1
8
J1
7
5
J1
8
J1
6
8
1
J1 J1
4
5
7
6
9
2
9
J1
3
7
8
J1
3
5
7
2
1
J1
1
J1
2
J1
8
3
8
J1
J1
6
time [slots]
2
3
9
6
1
7
4
10
5
8
PASSIVE
ACTIVE
Rall estimate
scanning
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transition phase, R
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



DET : Deterministic algorithm C*n*log(N)
RMS : Random Message Selection
SLF : Selfish
GF(x) Unsync: NetCod Unsynchronized
› Discovery ends independently for each node

GF(x) Sync: NetCod Synchronized
› Discovery ends at the same time-slot w.h.p.
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CR i
RMS
SLF
i
2
6
9
i
2
6
9
6
i
 RMS : Randomly pick a
control packet from the buffer.
 SLF: Send only own control
packet.
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 GF(x) : Send a linear combination
of all packets in the buffer
 CCat: Concatenate all packets
in the buffer.
i
2
6
i
9
6
2
i
GF(x)
CCat
x
9
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We propose a neighbor discovery algorithm
for single hop cognitive radio networks, able
to provide full neighbor discovery in a timeasynchronous and distributed way.
 Future work is looking towards the extension
of the algorithm to multi-hop cognitive radio
networks
 Provide a joint solution for neighbor
discovery and cluster formation in very
challenging wireless environments

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