future directions in wireless technology and the path to
TRANSCRIPT
1
Future Directions in Wireless Technology and the Path to Pervasive Computing
IEEE PerCom 2006March 15, 2006
Rutgers, The State University of New JerseyD. Raychaudhuri
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Introduction: Wireless Technology Roadmap
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Introduction: Future Wireless Network Scenario
Future Internet
Infostationcache
WLANAccess Point
WLANHot-Spot
VOIP(multi-mode)
Low-tier clusters(e.g. low power 802.11 sensor)
Ad-hocnetwork
extension
Public Switched Network(PSTN)
BTS
High-speed data & VOIP
Broadband Media cluster(e.g. UWB or MIMO)
BTS
BSC
MSC
CustomMobileInfrastructure(e.g. GSM, 3G)
CDMA, GSMor 3G radio access network
Generic mobile infrastructure
Today Future
GGSN,etc.
Voice(legacy)
High-speed data & VOIP
Relay node
• Fast, short-range radios• Low-power sensors• Multiple radio standards• Self-organizing ad-hoc nets• Dynamic spectrum sharing• Uniform core network (IP+)• Wide range of applications
pervasive computing
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WPAN radio
Today’s Wireless Systems The Future
Low-tier services
IP
802.11 Radio
Ethernet
Mobile ServiceMiddleware
IP
WLAN Services
3G/4GRadio
WLANradio
WPAN/low-tier radio
2.5G/3G Radio
GSM/GPRS
2.5G/3G Services
3G AccessNetwork
PSTN IP
WPAN networklayer (e.g. Bluetooth)
Generic Radio Access Network
Radio-specific vertically integrated systems withcomplex interworking gateways
Security QoS VPN ContentDelivery
Wireless/Mobile Services
Radio Independent modular system architecturefor heterogeneous networks
uniformradio API’s
genericnetwork API
uniform serviceAPI (Internet+)
Unified IP+ mobile networkincl supportfor mobility,multihop mesh,Multiple radios,freq coord, etc,
servicefeaturemodules
Introduction: Next Generation Protocol Architecture
area that needsstandards focus
CognitiveRadio/SDR
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Introduction: Wireless Technology Trends
RadioTechnology
NetworkArchitecture
PrimaryApplications
~1 Mbps 3G/WCDMA~10-54 Mbps WLAN
2G/CDMA & TDMA~1 Mbps WLAN
~100 Mbps+4G/OFDM, 802.16 &802.11e,n WLAN;~500 Mbps UWB,
Sensor radio, RFID
Cellular networksEthernet + WLAN
IP-based networksfor both
Cellular & WLAN
IP+ Layer 7 overlayinfrastructure net;
Ad-hoc low-tiernetworks
Telephony;PC/LAN
Telephony;Multimedia;
Mobile Internet
Telephony; Multimedia;
Mobile InternetSensor Nets
~1995-2000 ~2000-2005 ~2010+
Higher speed,OFDM Very wideband signals
Low power radiosCognitive radio
Mobile IPv6, etc.
Beyond IP networks(e.g. content aware routing)
New transport protocols
Cross-layer techniques;Improved MAC for ad-hoc
and QoS support
Self-organizing multi-hop
VOIP, H264, HTTP, etc.P2P, location-aware services
Sensor net applications,Embedded wireless (M2M)
Pervasive systems
Adaptive RadioNetworks
Next-GenCellular
Next-GenWLAN
HomeNetworks/
PAN
Mesh/Hybrid
Networks
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Introduction: Technology Roadmap
HardwarePlatforms
Protocols& Software
2000 2005 2010+
BasicWireless
Technologies
SystemApplications
3G Cellular
~11 Mbps QPSK/QAM
~2 Mbps WCDMA
~ 1 Mbps Bluetooth
~10 Mbps OFDM
~50 Mbps OFDM
~100 Mbps UWB
Broadband Cellular (3G)
WLAN (802.11a,b,g) ad-hoc/mesh
IP-based Cellular Network (B3G)
~100 Mbps OFDM/CDMA
~500 Mbps UWB
~200 Mbps MIMO/OFDM
Unified Wireless Access+ IP-based core network
802.11 WLAN card/AP
Cellular handset, BTS
Bluetooth module*
3G services
GSM, GPRS services
Mobile WLAN services
IP networks, 3G+WLAN
WLAN security, enterprise
Cellular VOIP gateway
802.11 Mesh Router*
Commodity BTS
3G Base Station RouterSelf-Organizing Ad-Hoc
Radio Router
Multi-standardCognitive Radio*
Next-Gen WLAN(including ad-hoc mesh)
Mobile Networks beyond IP…
Content- and locationaware service API’s
WLAN office/home public WLANhome media
networks
3G/WLAN HybridMobile Internetopen systems
4G Systems
Ad-Hoc & P2P Sensor Nets
Embedded Radio(wireless sensors)
dynamicspectrumsharing
Pervasive Systems
WLAN+ (802.11e,n)
Sensor radios(Zigbee, Mote)
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Wireless Networks Pervasive Systems
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Pervasive Systems: Typical Architecture
Mobile Internet (IP-based)
Overlay Pervasive Network Services
Compute & StorageServers
User interfaces forinformation & control
Ad-Hoc Sensor Net A
Ad-Hoc Sensor Net B
Sensor net/IP gateway GW
3G/4GBTS
PervasiveApplication
Agents
Relay Node
Virtualized Physical WorldObject or Event
Sensor/Actuator
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(Frictionless Capitalism)**2Find goods and services on your PDA as you walk through townWalk into your dept store and pick up what you need (no cashier!)
“Smart” Transportation systemsget routed around traffic jams in real-timereceive collision avoidance feedback, augmented reality displaysbe guided to an open parking spot in a busy garage
Airport logistics and securityWalk on to your plane (except for physical security check)Find your (lost) bags via RFID sensorsAirport authorities can screen passenger flows and check for unusual patterns
Smart office or homeSearch for physical objects, documents, booksMaintain a “lifelog” that stores a history of events by locationAssisted living for the disabled or elderly
Pervasive Applications: Some Examples
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Sensors in roadway interact with sensor/actuator in carsOpportunistic, attribute-based binding of sensors and carsAd-hoc network with dynamically changing topologyClosed-loop operation with tight real-time and reliability constraints
Pervasive Applications: Highway Safety
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Emergency event triggers interaction between object sensors and body sensors and initiate external communication
Heterogeneous ad-hoc networkSensors used to detect events and specify locationReal-time communication with care provider
Pervasive Applications: Assisted Living
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Heterogeneity of network elements & end-devicesSensor nodes, forwarding nodes, mobile devices, etc.Low power radio, wireless access networks, the Internet
Self-organizing and robust systemDynamically changing topologyNetwork links, nodes and services subject to failure
Ad-hoc network with power-efficient lower tierSensors with limited power and rangeNetwork optimized for power efficiency and scale
Attribute- or location- based connectivityDynamic binding without prior knowledge of network addressOverlay network routing based on content
Intermittent network availabilityWireless link availability <<100%Caching of data and opportunistic applications
Pervasive Systems: Some Properties
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Pervasive System Technologies
Next-generation WLAN &UWBInfostations, sensor platforms
Ad-Hoc Wireless Network (MAC,Discovery & Routing)
Content-based or location-awareoverlay network
Pervasive ComputingMiddleware/ApplicationsOpportunistic, robust, context-aware
software framework
Attribute and location aware networkservices for dynamic binding
Self-organizing low-tier network servicesefficiently supporting small, power-limitedwireless devices
High-speed short-range radio technologiesfor broadband and opportunistic data access
Technology Challenge
Scalable network infrastructure capableof supporting multiple low-tier wireless nets IP Network with Heterogeneous
Radio Access & Mobility
Unlicensed Spectrum &Cognitive radio
Spectrum management/licensing techniquesfor dense wireless deployment
Legend
Early research
Active R&Dstage
Emergingtechnologies
Secu
rity
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IP NetworkIP Network
Pervasive Systems: Key Technologies
ContentRouter
Wireless Access Point
Radio Forwarding Node
Future Cognitive RadioWireless Sensors
Infostation(wireless cache)
TinyOS
Ad-Hoc Net Protocols
Caching, Dynamic Binding
PHY Adaptation
CR Software Platform
Adaptive CR Net Protocols
Ad-Hoc Net Protocols
Caching, Dynamic Binding
ApplicationAgents
Caching, Dynamic Binding
Ad-Hoc Net Protocols
IP Network Gateway
ApplicationServer
Application
Application
Content-Based Routing
Content-Based Routing
Content-Based Routing
IP Routing
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Cognitive Radio
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Cognitive Radio: Scope of Spectrum ProblemSpectrumAllocation
Rules(static)
INTERNET
BTS
AuctionServer
(dynamic)
SpectrumCoordination
Server(dynamic)
AP
Ad-hocsensor cluster(low-power, high density)
Short-rangeinfrastructure
mode network (e.g. WLAN)
Short-range ad-hoc net
Wide-area infrastructuremode network (e.g. 802.16)
Pervasive systems dense deployment of wireless devicesProliferation of multiple radio technologies, e.g. 802.11a,b,g, UWB, 802.15, 802.16, 4G, etc.How should spectrum allocation rules evolve to achieve high efficiency?Available options include:
Agile radios (interference avoidance)Dynamic centralized allocation methodsDistributed spectrum coordination (etiquette)Collaborative ad-hoc networks
Etiquettepolicy
SpectrumCoordination
protocols
Spectrum Coordinationprotocols
Dynamic frequencyprovisioning
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Cognitive Radio: Common Spectrum Coordination Channel (CSCC)
Common spectrum coordination channel (CSCC) Common spectrum coordination channel (CSCC) can be used to coordinate radios with different PHY
Requires a standardized out-of-band etiquette channel & protocolPeriodic tx of radio parameters on CSCC, higher power to reach hidden nodesLocal contentions resolved via etiquette policies (..independent of protocol)Also supports ad-hoc multi-hop routing associations
Frequency
CH#N
CH#N-1
CH#N-2
CH#2
CH#1
CSCC
::
Ad-hocnet B Ad-hoc
net A
Ad-hocPiconet
MasterNode
CSCCRX range
for X
CSCCRX range
for Y
Y
X
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CSCC: Proof-of-Concept Experiments
WLAN-BT Scenario
Different devices with dual mode radios running CSCCd=4 meters are kept constantPriority- based etiquette policy
19
CSCC Results: Throughput Traces
0 20 40 60 80 100 120 140 160 180 200 220 240
3.4
3.6
3.8
4.0
4.2
4.4
4.6
4.8
WLA
N T
hrou
ghpu
t (M
bps)
Time (Seconds)
CSCC on CSCC off
WLAN session with BT2 in initial position
WLAN = high priority
0 50 100 150 200 250 30030
35
40
45
50
55
60
65
Blue
toot
h Th
roug
hput
(Kbp
s)
Time (Seconds)
CSCC on CSCC off
BT session with BT2 in initial position
Bluetooth = high priority
Observations:WLAN session throughput can improve ~35% by CSCC coordinationBT session throughput can improve ~25% by CSCC coordination
20
MPC8260
TMS320C6701XC2V6000FPGA
100BaseT EthernetMegarray
Connector-244 Configurable
I/O pins
Cognitive Radio: Hardware Platforms
Next-generation software-defined radio supporting fast spectrum scanning, adaptive control of modulation waveforms and collaborative network processingFacilitates efficient unlicensed band coordination and multi-standard compatibility between radio devices
Bell Laboratories Software Defined Radio (Baseband Processor)Courtesy of Dr. T. Sizer
21
Cognitive Radio: WINLAB prototype
radio
BasebandFPGA
BasebandProcessor Core
(DSP)
SRAM
PacketFPGA
Clock Mgmt
A/D
D/A
A/D
D/A
A/D
D/A
Wakeup
Packet BufferDRAM)
Host(CR Strategies)
radio
radio
Local ethernet drop
WINLAB’s “network centric” concept for cognitive radio prototype (..under development in collaboration with GA Tech & Lucent Bell Labs)
Requirements include:~Ghz spectrum scanning,- Etiquette policy processing- PHY layer adaptation (per pkt)- Ad-hoc network discovery- Multi-hop routing ~100 Mbps+
Agile radioI/O
Software defined modem Network Processor
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INTERNETINTERNET
Cognitive Radio: Adaptive Wireless Networks
AA
BB
D
C
D
E
F
Cognitive radios will have the capability of forming collaborative ad hoc networks with considerable flexibility in PHY, MAC
Incentives for spectrum conservation and collaboration (vs. competition)Rapid changes in network topology, PHY bit-rate, etc. implications for routingFundamentally cross-layer approach – need to consider wired net boundaryHigh-power cognitive radios may themselves serve as Internet routers…
Bootstrapped PHY &control link
End-to-end routed pathFrom A to F
23
Ad-Hoc Wireless Networks
24
Ad-Hoc Networks: Flat vs. HierarchicalHierarchical structure is essential, and helps to achieve:
Scalability, i.e. improved max throughput and delay/QoSEffective integration with 3G/4G, WLAN and InternetImproved coverage & power consumption at subscriber radios
Wired Internet Infrastructure
Gateway node
Potential bottleneck
“Flat” mesh network with ad-hoc routing
End-user radios(with routing capability)
Wired Internet Infrastructure
BTS
BTS
AP
Forwarding node
End-user radios(no routing capability)
Multi-tieredInterfaces to
wired network
Wide Area Cell
3G cell
Hierarchical architecture with radio forwarding nodes and AP’s/BS’s
Ad-hoc associations
Ad-hoc associations
Microcell
Forwarding NodeExtended Coverage
Power & computinglimitations at low-tier nodes
Throughput per node scales ~ 1/sqrt(n)
Throughput per node can scale ~1 with right ratio of FN’s, AP’s (Zhao, CISS 2006)
25
Ad-Hoc Networks: Hierarchical Capacity
320 kbps
77 kbps
4 pkts/s 16 pkts/s
0 10 20 300
1
2
3
x 105
Packet rate (pkts/s)
Thr
ough
put (
bps)
HierFlat
0 10 20 300
1
2
3
4
Packet rate (pkts/s)
Avg
del
ay (s
imul
ated
s)
HierFlat
0 10 20 300
0.1
0.2
0.3
0.4
Packet rate (pkts/s)
Rou
ting
over
head Hier
Flat
0 10 20 300
0.5
1
Packet rate (pkts/s)
Pkt
del
iver
y fra
ctio
n
HierFlat
Hierarchy and wired integration significantly improve network throughput, delay and packet loss.
Routing overhead decreased as well.
Reference: S. Zhao, I. Seskar and D. Raychaudhuri, "Performance and Scalability of Self-Organizing Hierarchical Ad Hoc Wireless Networks", Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC 2004), March 21-24, 2004, Atlanta
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TransmitPower
HopsToAP
NodeType
SequenceNumber
Cluster ID
PacketType
NodeID
BroadcastMAC
SourceMAC
Beacon Frame Format
Low-tier access links(AP/FN Beacons, MN Associations, Data)
Ad-hoc infrastructure links between FNs and APs(AP/FN Beacons, FN Associations, Routing Exchanges, Data)
Forwarding Node (FN)
Access Point (AP)
FN
AP
FNcoverage
area
APcoverage
area
Low-tier(e.g. sensor)Mobile Node (MN)
FN
Self-organized ad-hoc network
MN
MN
MN
MN
MN
MNMN MN
Internet
FN
AP
Channel 4
Channel 2
Beacon
Transmit Power Required: 1mW
Beacon
Assoc
Transmit Power Required: 4mW
FN
AP
SN•Scan all channels•Associate with FN/AP•Send data
FN•Scan all channels•Find minimum delay links to AP•Set up routes to AP•Send beacons•Forward SN data
Ad-Hoc Network: Discovery ProtocolCreates efficient ad-hoc network topology just above MAC layer in order to reduce burden on routing protocol…
27
Ad-Hoc Network: Topology FormationDelay Constrained Energy Minimization:
•LP-based optimizations in MATLAB•Objective: Minimize energy to AP subject to delayconstraint of n hops•Energy consumption due to tx power•Two-ray ground propagation model
Access PointForwarding NodeSensor Node
28
Ad-Hoc MAC: D-LSMA Scheduling
Link scheduling to allow parallel transmissions, solves “exposed node” useful for QoS on ad-hoc FN-FN infrastructure in hierarchical systemsDistributed scheduling algorithm (upper MAC), using 802.11-based lower MAC
D
E
A
B
C
to C to ERTS retransmit
to C to Cto E to Eto C
t0 t1 t2
T
A
DE
B C RTSCTSDATA
Upper MACScheduler
D-LSMA
Classified flows
Lower MAC
……
29
Ad-Hoc MAC: D-LSMA Results
B
CA
D
1
2 34 5
6 7 8
9
10
1112 13
1415
ns-2 Simulation parameters:Size: 800 m by 800 mTX range: 250 metersPHY Data rate: 1MbpsCBR packet size: 512B
0
20
40
60
80
100
A B C D
Throughput (Kbps)
D-LSMA 802.11
0
0.2
0.4
0.6
0.8
1
A B C D
Latency (secs)
Offered per-flow load: 110Kbps
30
Ad-Hoc Routing: PHY/MAC Aware Metric
Cross- layer routing can improve network performance via awareness of PHY and MAC conditions:
Simple end-to-end delay metric including MAC congestion and PHY rate~20% improvement in typical scenarios, more in congested networksExperiments show the need to avoid interactions with 802.11 PHY “autorate” algorithm
Alternate Path
Nominal Path
PHY=54 Mbps
PHY=27 Mbps
PHY=6.5 Mbps
Region ofMAC congestion
802.11Autorate
Fixed rate
31
Access PointUS Robotics 2450 AP
AMD Elan SC400 processor
1 MB Flash, 4 MB RAM
Prism-2 based PCMCIA card
Forwarding nodeCompulab 586 CORE
AMD Elan SC520 CPU
2 MB NOR flash + 64 MB NAND Flash on board
Dual PCMCIA slots
SensorsIntrinsyc Cerfcube
Intel PXA 250 (XScale processor)
CF-based wireless support
HA
RD
WA
RE
PLA
TFO
RM
SOFT
WA
RE
802.11b ad-hoc mode
Ad-Hoc Networks: SOHAN Prototype
32
Ad-Hoc Networks : “SOHAN” ResultsFlat HierarchicalSystem Parameters:
0.9 sq. km, 20 mobiles/sensors, 4 FNs, 2 APs802.11a with multiple frequencies
15 20 25 30 35 40 45 50 55 60 6510
15
20
25
30
35
40
45
50
System offered load (Mbps)
Sys
tem
Thr
ough
put
(Mbp
s)
Total System Throughput for flat and hierarchical topologies
FlatHierarchical
Flat
Hierarchical
• “SOHAN” system evaluated for realistic deployment scenario with ~25 nodes
• Results show that system scales well and significantly outperforms flat ad-hoc routing (AODV)
APFN
MN
Mapping on to ORBITRadio grid emulator
33
Ad-Hoc Networks : Next Steps Progress on separate components (routing, MAC, PHY adaptation, cross- layer, power management) but holistic solutions still work- in- progress
Focus on scaling, topology optimization and efficient multi-hop MACHierarchical structure, integrated approach to MAC & routing, some cross-layerUse of multiple frequencies, spectrum coordination proceduresGlobal control plane approach to support generalized routing/MAC/spectrum algorithms..?
Software stack with Global Control Plane
(“GCP”)
Adaptive OFDM PHYBootstrap PHY
MAC FirmwareGlobal Control Sig
Spectrum/MAC MAC Scheduler & BW mgr
Cross-layer Ad Hoc RoutingRouting Algorithm
Net Mgmt
34
Infostations
35
Infostations: Service ConceptUsing radio hot-spots (WLAN, other...) to deliver/retrieve context-and location-aware information to/from mobiles/sensors
operation includes: detection of Infostation, adaptive bit-rate selection, dynamic association, content caching and opportunistic data delivery
Internet
Low-speed wide-areaaccess
Infostationcell
Mobile Infostation
Roadway Sensors
Mobile User
Data Cache
Ad-HocNetwork
OpportunisticHigh-Speed Link
(MB/s)
Infostation
OpportunisticHigh-Speed Link
(MB/s)
36
Infostations: Short-Range Radio Propagation
Results show that channel is well-behaved for distance ~5-10m 100’s of Mbps achievable with OFDM, UWB or other modulations (...802.11a adapting to max 54 Mbps can be used as a first approximation)
Measured data fromDomazetovic & Greenstein[2001]
W
z
dtra
jectory
Offset w
Scenario 1: Open Roadway With Trees
37
Infostations: Pass-thru MAC Protocol
Mobile user passes through Infostation in sec during which ~MB files are downloaded/uploaded
Requires modifications to conventional WLAN MAC, including fast synch, pre-authentication, etc. (... related to interworking discussed before)Motivates 2-tier arch with ~10m service zone (for high-speed data transfer) and ~50m access control zone (for sync, authentication, ...)
Infostationsaccess pointData cache
~100 MB/sFast transfer
Low-speed control channel(for synch & service setup)
ServiceZone
Access ControlZone
Transit time ~secTotal transit time ~10sec
38
Infostations: “i-media” PrototypeWINLAB’s “i-media” prototype for caching and delivery of mobile content
802.11 WLAN AP with MAC optimizationswired network interface (Ethernet, DSL,..)on board processing & cache storageXML-based content routing for information delivery services
Project now moving to lab trials/tech transfer stage:
media file delivery demonstrations with wireless service operatorsEmergency response and military applications
39
Pervasive Network Software
40
Pervasive Networks: Layered Model
•••
•••
•••
•••
•••
••••••
<>
<>
<>
<>
<>
<>
<>
Sensors & Actuators
HierarchicalAd-Hoc Data Network
Content Network
Autonomous AgentsAffinityGroups
Courtesy of Prof. Max Ott
41
Pervasive Networks: Software ModelSensor net scenarios require a fundamentally new software model (…not TCP/IP or web!!):
Large number of context-dependent sources/sensors with unknown IP addressContent-driven networking (…not like TCP/IP client-server!)Distributed, collaborative computing between “sensor clusters”Varying wireless connectivity and resource levels
Sensor NetSoftwareModel
Pervasive Computing ApplicationPervasive Computing Application
Agent 2Agent 1
Agent 3
SensorCluster A
SensorCluster B
Run-timeEnvironment(network OS)
ResourceDiscovery
Ad-hoc Routing
OS/ProcessScheduling
Overlay Network for Dynamic Agent <-> Sensor
Association
42
Pervasive Networks: Overlay Services for Dynamic Binding
Overlay networks can be used for dynamic binding between sensor devices, end-users and application programs
Use of XML or similar content descriptor to specify sensor data and application profile“Layer 7” overlay network (implemented over IP tunnels) provides binding service between producers (sensors) and consumers (servers, users)
Content ConsumersSensor ContentProducer
OverlayRouter
A
Interest Profile
XMLDescriptor Overlay
RouterB
ApplicationAgent
Mobile User
43
Location is a more natural addressing mechanism
Location becomes more important than a network address
Opportunistic message forwarding within geographic perimeterRetransmissions from different vehicles Delay-tolerant networking
Desired message delivery zone
(Idealized) Broadcast range
Irrelevant vehicles in radio range for few seconds
Passing vehicle,in radio range for tens of seconds
Following vehicle,in radio range for minutes
Pervasive Networks: Geocasting
44
Even if traces are collected anonymously, origins and destination can reveal private dataAutomated algorithms can identify the position of home from single day GPS traces with high accuracy (see graph)Correlation with address databases can identify driver[515110X 4300483Y 13Z]
Accuracy of Home Identification
0
20
40
60
80
100
1 2 3 4
Algorithms
Per
cent Correct
WrongOut of samples
Pervasive Networks: Location Privacy
45
Malware spreads through short- range peer- to- peer communications
E.g. Cabir Bluetooth worm 6/2004
Service provider perimeter defenses (firewalls, virus scanners) are ineffectiveChallenge
Novel detection mechanismsLocation-aware immunization
ServiceProvider
Imm
unization
Detection
Pervasive Networks: Security Aspects
DOS Attack
46
Pervasive Networks: Sensor SocketsNeed for more powerful socket abstractions for general-purpose sensor net programming. Requirements include:
Choice of networking modes (ad-hoc, content-based, proxy IP, etc.)Choice of datagram and static/dynamic binding modesTransport layer reliability and flow control options
47
Concluding Remarks: ORBIT and GENI
48
Pervasive Networks: Experimental Research Challenges
Significant challenge in system validation and performance evaluation:
Large scale ~100’s to 1000’s of sensor nodes, mobiles, etc.Need for realistic wireless connections and usage scenariosShould incorporate CPU processing and energy constraintsReproducibility of results at various time scales is criticalAlso need to consider experimenter cost/resource limitations
Motivates a hierarchy of testbeds: simulation, controlled emulation, real-world systems, …
49
ORBIT Testbed: Radio Grid
80 ft ( 20 nodes )
70 ft
m (
20 n
odes
)
Control switch
Data switch Application Servers
(User applications/ Delay nodes/
Mobility Controllers / Mobile Nodes)
Internet VPN Gateway / Firewall
Back-end servers
Front-endServers
Gigabit backboneVPN Gateway to
Wide-Area Testbed
SA1 SA2 SAP IS1 IS2 ISQ
RF/Spectrum Measurements Interference Sources
50
ORBIT: Radio Grid Hardware
512 MBRAM
Gigabit Ethernet(control)
GigabitEthernet
(data)
AtherosminiPCI802.11a/b/g
22.1Mhz
1 Ghz
pwr/resetvolt/temp
20 GBDISK
Serial Console110
VAC
RJ11 NodeIdBox+5v standby
PowerSupply
CPUVIA
C3 1Ghz
AtherosminiPCI802.11a/b/g
BluetoothUSB
CPURabbit Semi
RCM3700
10 BaseTEthernet
(CM)
51
ORBIT Testbed: Radio Grid
400-node radio grid system at Tech Center II (construction completed 7/05)
ORBIT radio nodehardware
64-node radio grid prototype at Busch Campus (8/04)
52March 20, 2006
Urban
300 meters
500 meters
Suburban
20 meters
ORBIT Testbed
20 meters
HallwayOffice
30 meters
ORBIT: Radio Grid Mapping
53
ORBIT : Mapping of AP Scenarios
○ RXAP
NLS/COM/CircleN = 80, Link SNR Range =37 dB, Mapping MSE = 0.11 dB
0 20 40 60 80-15
-10
-5
0
5
10
15
20
25
Index of SNR Samples
Lin
k S
NR
/ G
rid
SIN
R, d
B
Link SNRGrid SINR
0 5 10 15 200
5
10
15
20
Horizontal Axis
Ver
tica
l A
xis
APInterfererMapped RX Node
NLS/RES/LINEN=80, Link SNR Range =36dB, Mapping MSE = 0.35 dB
0 20 40 60 800
5
10
15
20
25
30
35
40
Index of SNR Samples
Lin
k S
NR
/ G
rid
SIN
R, d
B
0 5 10 15 200
5
10
15
20
Horizontal Axis
Ver
tica
l A
xis
APInterfererMapped RX Node
Link SNRGrid SINR
○ RXAP
Matching of SNR vectors
54
ORBIT Radio Grid: Running an Experiment
OML Server
USER / CONTROLLER
OBSERVER SERVICES
GRID
Node configuration
- Select nodes
- Configure interfaces
Application configuration
- Download application and libraries
- Configure application parameters
OML configuration
- Configure measurement collection
parameters
Experiment Script
DB
Nod
eHan
dler
Nod
eAge
nt(p
er n
ode)
OML Client (per node)
START
END
ww
w Fetch results
Experiment details
Run time statistic
collection
Off-line Storage of results
Display
Sta
ticD
ynam
ic
(Change channel, power, sleep
on/off etc during experiment)
55
ORBIT Testbed: Field Trial System
Lucent “Base Station Router”with IP interface
“Open API” 802.11a,b,gORBIT radio node
56
GENI intended to serve as programmable experimental infrastructure
Nationwide coverage with at least 25 PoP’sSeveral peering points with current InternetEdge routers and backbone switches with fiberFully programmable, virtualizable routers as the main building block~5-6 wireless sub-networks covering urban and suburban areas
Future Research Testbeds: NSF’s “GENI” System
57
Future Research Testbeds: Sensor Networks in GENI
2-3 sensor network projects to be selected via proposal process in view of application-specific nature
Sensor network experiments will leverage 802.11 mesh or 3G wide area infrastructure in GENI dense deployments for protocol testing at scaloeProvide “user deployment kit” with platforms including sensor nodes and sensor/WLAN or sensor/3G gateway
Dual-radio ad-hoc router(includes wired interface for
AP sites)
RadioNodes
~50-100 mspacing
Ad-hocRadiolinks Access Point (wired)
Ad-Hoc Radio Node
Spectrum Monitor
Sensor Net Area
Sensor Nodes
Sensor Gateway
802.11 Access Pointor Relay Node
802.11 radio link
Short-range sensor radio link
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Future Research Testbeds: Cognitive Radio Subnet in GENI
Advanced “technology demonstrator” of cognitive radio networks for reliable wide-area services (over a ~50 Km**2 coverage area) with spectrum sharing, adaptive networking, etc.
Cognitive radio platform to be selected from competing research projectsRequires enhanced software interfaces for control of radio PHY, discovery and bootstrapping, adaptive network protocols, etc. – suitable for protocol virtualizationNew experimental band for cognitive radio (below 1 Ghz preferable)
Cognitive Radio Network Node
Cognitive Radio Client
Cognitive Radio Network Node
Cognitive Radio Client
Connections to GENIInfrastructure
Spectrum MonitorsSpectrum Server
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Web Sites for More Information:
WINLAB: www.winlab.rutgers.eduORBIT: www.orbit-lab.orgGENI: www.geni.net