Transcript CogNet - Cognitive Networking

CogNet - Cognitive Networking
NSF NeTS/FIND (Future Internet Network Design)
Collaborative Project
Rutgers University
University of Kansas
Carnegie Mellon University
CogNet in Perspective
• GENI (Global Environment for Network
Innovations)
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Global experimental facility that will foster
exploration and evaluation of new networking
architectures (at scale) under realistic
conditions
Major infrastructure, expected to be $367
million
• FIND (Future Internet Network Design)
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Requirements for global network of fifteen
years from now - what should that network
look like and do?
How would we re-conceive tomorrow's global
network today, if we could design it from
scratch?
Innovative ideas in broad area of network
architecture, principles, and design
Research projects expected to be funded at
$20 million per year in progressive phases
Provides experiments and architectures that
will be pursued on the GENI infrastructure
Wireless Networking Challenges
Why is wireless networking hard?
• Mobility is inherent with untethered
• Resources are constrained
• Spectrum “scarcity” → bandwidth & delay issues
• Environment changes
• Mobility → different surroundings (indoor, urban, rural)
• Varying physical properties
• Wireless communication path changes over time
Cognitive / Agile Radio Platforms
(-100dBm)
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Flexible in RF carrier frequency (~0 - 6 GHz)
Flexible in bandwidth (several 10’s MHz)
Flexible in waveform
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Traffic characteristics measured at network
layer
Error rate & characteristics (BER and
distribution)
– MAC layer per packet error information
– Network and transport layer per flow
correlations
Receive characteristics
– Physical layer – signal strength, interfering
signals, background noise
– MAC layer – transmit power, antenna in
use
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HMC488MS8G
CLoss = 10 dB
P1dB = +8 dBm
LO Drive 0dBm
-3dB
R
-10dB
-5dB
0-30dB RX
Attenuation
Control
Act ive RX Antenna Module
BASEBAND I
0
90
I
L
+19dB
-5dB
1.850-2.450 GHz
(-81dBm)
(-66dBm)
LNA
+19dB
AD8347
AD8349
ADF4360
ADF4113
SMV3300A
FOX801BE-160
BGA2031
MGA-83563
MGA-82563
MGA-545P8
MGA-86576
HMC488MSG 8
ERA-1SM
4 @60mA
2 @25mA
2 @50mA
+3. 3
+5
80
150
240
15
20
5
70
200
100
140
50
100
40
770mA 440mA
BW=30 MHz
GAIN
CONTROL
3.4 GHz
I DET
Q DET
Jumper
Select
SPI Bus
MGA-82563
Gain = [email protected] GHz
P1dB =+17dBm@4. 0 G Hz
ADF4360-1
2.150-2.450 GHz
RX IF G AIN
CONTRO L
AD5601
6 BI T DAC
3 dB
POWER
DI VDER
-2dB
RX LO 1
FOX801BE-160
TCXO
LO 3
(+3. 5dBm)
BASEBAND Q
ADF4360-2
1.850-2. 150 GHz
MC68HC08
Microcontroller
I²C
DPB Input
16.0 MHz
REF CLK OUT
ADF4113
+9dB
(+3. 5dBm)
-5dB
SMV3300A
(+5dBm)
TX LO 2
Microst rip
Lumped
(+25dBm)
+8dBi
5.250-5.850 GHz
(+17dBm)
(+21dBm)
(+15dBm)
(+9dBm)
TX IF GAIN
CO NTROL
ERA-1SM
Gain = [email protected] GHz
P1dB = +12dBm
(-2dBm)
(-8dBm)
3.4 GHz
ADF4360-1
2.150-2.450 GHz
BASEBAND I
(+7dBm)
(+3dBm)
L
R
+17dB
AD8349
I-Q MODULATOR
700 MHz - 2.7 GHz
1.850-2.450 GHz
(-3dBm)
PA
-4dB
-5dB
O PTIONAL
MGA-545P8
Gain = +11. [email protected] GHz
P1dB = [email protected] GHz
PSAT = [email protected] GHz
ADF4360-2
1.850-2.150 GHz
AD5601
6 BIT DAC
Act ive TX Antenna Module
A/D and D/A driven
Generated/processed by programmable DSP and/or FPGAs
Dials to observe
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5. 250-5.850 GHz
(-77dBm)
LNA
-4dB
AD8347
I-Q DEMODULATOR
800 MHz - 2.7 G Hz
MGA-86576
Gain = [email protected] GHz
P1dB = [email protected] GHz
NF =1.8dB@6. 0 GHz
+8dBi

I
-10dB
+9dB
0
90
BW=30 MHz
-5dB
BASEBAND Q
For use w ith passi ve
anten na
MGA-83563
Gain = [email protected] GHz
P1dB = [email protected] GHz
PSAT = [email protected] GHz
BGA2031
Gain = [email protected] GHz (2.7 V CT RL )
G = [email protected] GHz
P1dB = [email protected] GHz
5 GHz RF PCB Block Diagram
1
D. DePardo
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1
27 JULY 05
Knobs to influence
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Physical layer
– Frequency & bandwidth
– Transmit power
– Beam width & direction
– Data rate, code, & chipping rate
MAC protocol
– FEC strength
– Retransmit scheme
– MTU size
– Encryption & parameters
Network layer
– Routing protocol
– Addressing plan(s)
– ACLs
Interface framework with a flexible, usable set of scalable parameters
Adapt to resource constraints, environment, varying physical conditions, application
Cognitive Networking
Cognitive (from Wikipedia) – applying the experience
gathered in one place by one being
to actions by another being elsewhere
• Developing experimental protocol stack for cognitive
networks, not just cognitive radios
• Scalable autoconfiguration & network management
• Dynamic network layer supporting tailored functionality
(IP, group messaging, rich queries, etc.)
• Builds on the foundation of cognitive radios (e.g., Rutgers
/ GNU Radio, KU Agile Radio), but extends it further up
the protocol stack, and explores across stack
CogNet Vision
The Global Control Plane and Architecture Internetworking
Name & Service Discovery
Cross-Layer Aware Routing
Forwarding Incentives
Network Management Architecture
Future Internet
Network
Layer
Protocols
Supernode
(mobile or fixed)
Spectrum
Coordination
Flexible
MAC Layer
PHY
Adaptation
Cognitive Radio Nodes
Autoconfiguration and Bootstrapping Protocols
Network Layer Overlays
Overlay 1
Overlay 2
Core Network
Supernode
(mobile or fixed)
Mobile Nodes
Network Layer Innovations Example
• Sensor networks with resource constraints
• Size, weight, power limits → bandwidth, processing power limits
• Traditional IP networking not the best answer
• Substantial overhead
• Unnecessary communications
• Innovations
• Lightweight network-layer protocols
• Operations on data flow – e.g., nodes
do not forward sensor data values
that are unchanged
• Gateways
Wireless Sensor Network
Network Layer Overlays
• Structured and unstructured P2P, DHT
• Services may map better to particular overlays
• Search, distributed file storage, load balancing, multicast messaging
• Overlay typically denotes an application layer network of
semi-persistent links between participating nodes, that is
used to forward messages between the distributed
application elements
• Can also use them for Layer 3 forwarding
• Inspired by M. Caesar, M. Castro, E. Nightingale, G. O'Shea and A.
Rowstron, "Virtual Ring Routing: Network routing inspired by DHTs",
Sigcomm 2006, Pisa, Italy, September 2006,
http://research.microsoft.com/~antr/VRR.htm
• Explore how having tailored layer 3s, (IP, range-based
overlays, multicast optimized overlays, etc.) may impact
end-to-end network architecture for interoperating
cognitive wireless subnets and the future Internet
Network Layer Overlays
• Research topics
• How to use, position, and discover routers between the overlays
themselves, and the Internet
• How applications can decide which network layer to use
– Legacy approach manipulating resolver libraries
– New approach by applications aware of the Global Control
Plane (GCP)
• Implement multiple new network layers (linux kernel changes for
experiments, implement within ns2 for simulations, and explore if
common code can be leveraged)
• Ideally explore performance tradeoffs (more overhead, etc.
versus better utilization, etc.) in simulation and real cognitive
radio network (KUAR or Rutgers/GNU Radio)
Routing and Platforms
• XORP
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Routing protocol implementations, extensible API, and configuration tools
IPv4 and IPv6 – BGP, RIP, PIM-SM, and IGMP/MLD
• Routing Control Platform (RCP)
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Computes BGP routes for the routers in an AS
Incorporates complete routing information & network engineering
• Provides basis for experimentation with interdomain routing
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Inter-overlay – between overlays on same network
Gateways (supernodes) between networks
XORP
Source: M. Caesar, et al, "Design and implementation of a Routing Control Platform“, NSDI 2005
Source: XORP Design Overview
Network Management Architecture
• Global Control Plane
Network Wide Cross Layer Interaction
Node 1
Network Management
Information
Exposed Via
Management And
Service Discovery
Overlays
Applications
Local
Instance
of the
Global
Control
Plane
Rich
Query
IP
Group
Messaging
Cognitive Networking Layer
Cognitive Radio & MAC Layers
Node 2
Node 3
Network Management
Information
Exposed Via
Management And
Service Discovery
Overlays
Network Management
Information
Exposed Via
Management And
Service Discovery
Overlays
Global Control Plane
• Implement overlay for inter-node transmission of control
plane data (position, capabilities, errors, signal strength,
etc.)
• Implement parts of local node control plane necessary to
perform network layer research
• Primarily application and layer 3
• CMU/Rutgers will implement layer 1 & 2 for their radios
• KU may implement local node control plane layer 1 & 2 for KUAR
• Explore performance – analytically & experiment
• Overlay overhead versus better data for cognitive decisions using local
cross-layer and global cross-network information
• Assertion - make better cognitive decision knowing local node
information and receiving node environments as well as details above
any intermediate hops
CogNet Summary
• Developing experimental protocol stack for cognitive
networks, not just cognitive radios
• Scalable autoconfiguration & network management
• Dynamic network layer supporting tailored functionality
(IP, group messaging, rich queries, etc.)
• Building on foundation of cognitive radios (e.g., Rutgers
& GNU Radio, KU Agile Radio), but extends it further up
the protocol stack, and explores across stack
CogNet - Cognitive Networking