key wireless networking technologies in the …staff.ustc.edu.cn/~xinming/wireless...

KEY WIRELESS NETWORKING TECHNOLOGIES IN THE NEXT DECADE

I. F. AKYILDIZI. F. AKYILDIZ

Broadband & Wireless Networking LaboratoryBroadband & Wireless Networking LaboratorySchool of Electrical and Computer EngineeringSchool of Electrical and Computer Engineering

Georgia Institute of TechnologyGeorgia Institute of TechnologyTel: 404Tel: 404--894894--5141; Fax: 4045141; Fax: 404--894894--7883 7883

Email: Email: [email protected]@ece.gatech.eduWeb: http://Web: http://www.ece.gatech.edu/research/labs/bwnwww.ece.gatech.edu/research/labs/bwn

2IFA’2006 CHINACOM

KEY WIRELESS NETWORKING TECHNOLOGIES IN THE NEXT DECADE - OVERVIEW

• WIRELESS LANs• SATELLITE NETWORKS• SENSOR & ACTOR NETWORKS• WIRELESS MESH NETWORKS• WiMAX• xG WIRELESS SYSTEMS/DYNAMIC SPECTRUM ACCESS NETWORKS/

COGNITIVE RADIO NETWORKS

FUTURE INTERNET SEAMLESS CO-EXISTINCE OF ALL THESE NETWORKS


Internet, Internet, Satellite, Satellite, UAVUAV

Sink

Sink

TaskManager

SENSOR NETWORKS ARCHITECTURE

I.F. Akyildiz, W. Su, Y. Sankarasubramaniam, E. Cayirci,“Wireless Sensor Networks: A Survey”, Computer Networks (Elsevier) Journal, March 2002.


SENSOR NODE HARDWARESENSOR NODE HARDWARE

Power UnitPower Unit ANTENNAANTENNA

Sensor ADCSensor ADCProcessorProcessor

MemoryMemoryTransceiverTransceiver

ocation Finding Systemocation Finding System MobilizerMobilizer SmallSmallLow powerLow powerLow bit rateLow bit rateHigh density High density Low cost (dispensableLow cost (dispensableAutonomousAutonomousAdaptiveAdaptive

SENSING UNIT PROCESSING UNIT


SENSOR NETWORK TESTBEDSENSOR NETWORK TESTBED@ BWN LAB@ BWN LAB


SENSOR NODE FEATURESSENSOR NODE FEATURES

2 x AA batteries; Solar Energy2 x AA batteries; Solar EnergyPowerPower100 feet 100 feet Radio Range Radio Range 0.75 0.75 mWmWPower Power

40 40 kbitskbits/sec (max)/sec (max)Data RateData Rate

916MHz or 433MHz916MHz or 433MHz(ISM Bands)(ISM Bands)

Radio FrequencyRadio Frequency4K bytes4K bytesEEPROMEEPROM4K bytes4K bytesSRAMSRAM128K bytes128K bytesFlashFlash4 MHz4 MHzSpeedSpeed

MPR300CBMPR300CBProcessor/Radio BoardProcessor/Radio Board


SENSOR NETWORKS FEATURESSENSOR NETWORKS FEATURES

APPLICATIONS: APPLICATIONS: Military, Environmental, Health, Home, Traffic, Space ExplMilitary, Environmental, Health, Home, Traffic, Space Exploration, oration, Chemical Processing, Volcanoes, Mining, Disaster ReliefChemical Processing, Volcanoes, Mining, Disaster Relief……. .

SENSOR TYPESSENSOR TYPES::Seismic, Low Sampling Rate Magnetic, Thermal, Visual, InfSeismic, Low Sampling Rate Magnetic, Thermal, Visual, Infrared, rared, Acoustic, RadarAcoustic, Radar……

SENSOR TASKSSENSOR TASKS::Temperature, Humidity, Vehicular Movement, Lightning CondiTemperature, Humidity, Vehicular Movement, Lightning Condition, tion, Pressure, Soil Makeup, Noise Levels, Presence or Absence Pressure, Soil Makeup, Noise Levels, Presence or Absence of of Certain Types of Objects, Mechanical Stress Levels on AttCertain Types of Objects, Mechanical Stress Levels on Attached ached Objects, Current Characteristics (Speed, Direction, Size) Objects, Current Characteristics (Speed, Direction, Size) of an of an ObjectObject ……..


COMMUNICATION PROTOCOLSCOMMUNICATION PROTOCOLS

Application LayerApplication Layer

Transport LayerTransport Layer

Network LayerNetwork Layer

Data Link LayerData Link Layer

Physical LayerPhysical Layer

Power M

anagement Plane

Power M

anagement Plane

Task Managem

ent PlaneTask M

anagement Plane


RESEARCH ON COMMUNICATION PROTOCOLS SO FAR !!!

TWEAKING KNOWN CLASSICAL COMMUNICATION PROTOCOLS FORMAC, ROUTING, TRANSPORT LAYERS

TWEAKING KNOWN TOPOLOGY and POWERMANAGEMENT SCHEMES

A “PAPER WRITING RACE !!!!”


EXAMPLE: EXAMPLE: TRANSPORT LAYER PROTOCOLSTRANSPORT LAYER PROTOCOLS* End* End--toto--End Problem is separated into smaller distancesEnd Problem is separated into smaller distances

(TCP SPLITTING idea !!) (TCP SPLITTING idea !!) Reliable MultiReliable Multi--Segment Transport (RMST) Protocol [1]Segment Transport (RMST) Protocol [1]

* End* End--toto--End Problem is converted into HopEnd Problem is converted into Hop--byby--Hop Control Hop Control PSFQ PSFQ -- Pump Slowly Fetch Quickly [2] Pump Slowly Fetch Quickly [2]

* Adjusting Reporting Rates for Congestion and Flow Control base* Adjusting Reporting Rates for Congestion and Flow Control based ond onSpatial Correlation Spatial Correlation

ESRT ESRT –– EventEvent--otot--Sink Reliable Transport [3]Sink Reliable Transport [3]

1. F. Stann and J. Heidemann, “RMST: Reliable Data Transport in Sensor Networks,”Proc. of IEEE SNPA’03, May 2003, Anchorage, Alaska.

2. Y. Wan, A. T. Campbell and L. Krishnamurthy, 2. Y. Wan, A. T. Campbell and L. Krishnamurthy, ““PSFQ: A Reliable Transport Protocol for PSFQ: A Reliable Transport Protocol for Wireless Sensor Networks,Wireless Sensor Networks,”” Proc. ACM WSNA’02, Sept. 2002, Atlanta, GA.

3. O. Akan and I.F. Akyildiz, “ESRT: Event to Sink Reliable Transport in WSNs”,IEEE Tr. on Networking, October 2005.


Example: Example: ROUTING PROTOCOLS ROUTING PROTOCOLS

1. DATA CENTRIC PROTOCOLSFlooding, Gossiping, SPIN, SAR (Sequential Assign. Routing), Rumor Routing, Directed Diffusion, Constrained Anisotropic Diffused Routing, COUGAR, ACQUIRE

2. HIERARCHICAL PROTOCOLSLEACH, PEGASIS, TEEN (Threshold Sensitive Energy Efficient Sensor Network

Protocol), APTEEN, 3. LOCATION BASED (GEOGRAPHICAL) PROTOCOLS

MECN, SMECN (Small Minimum Energy Com Netw), GAF (Geographic Adaptive Fidelity), GEAR, Distributed Topology/GeographicRouting Algorithm


EXAMPLE:EXAMPLE: MAC PROTOCOLSMAC PROTOCOLS

IEEE 802.11 [1] S-MAC [2] TRAMA [3]TRAMA [3]CCCC--MAC [4]MAC [4]

[1] IEEE 802.11, “Wireless LAN MAC and PHY Specifications,” 1999[2] W. Ye et. al. , “An Energy Efficient MAC Protocol for

Wireless Sensor Networks,” Proc. ACM MOBICOM, Roma, July 2001.[3] V. Rajendran, et. al., “Energy-Efficient, Collision-Free Medium Access Control for

Wireless Sensor Networks,” Proc. ACM SenSys 2003, LA, November 2003. [4] M.C. Vuran and I.F. Akyildiz, “Collabarative Correlation Based MAC Protocol for

Wireless Sensor Networks, IEEE Trans. on Networking, April 2006.


GRAND CHALLENGE:GRAND CHALLENGE:

Physical Layer

Application Layer

Transport Layer

Network Layer

MAC Layer

Task Managem

ent Plane

Power M

anagement Plane

Application Layer

Cross-Layer M

anagem

ent P

lane

Power M

anagement Plane

Communication Module

Our ViewOur View

Cross-Layer Melting

Traditional ApproachTraditional Approach

Traditional layered approach is not suitable for WSNs


XLM: CrossXLM: Cross--Layer ModuleLayer ModuleM. C. M. C. VuranVuran, O. B. , O. B. AkanAkan, and I. F. , and I. F. AkyildizAkyildiz,,““XLM: A Cross Layer Module for Efficient Communication in WirelesXLM: A Cross Layer Module for Efficient Communication in Wireless s Sensor Networks,Sensor Networks,““ Proc. of Int. Conf on Info Science and Systems, Proc. of Int. Conf on Info Science and Systems, CISSCISS’’06, Princeton, March06, Princeton, March 2006.2006.

PHY

Application Layer

Transport

Network

MAC

XLM: Cross -Layer MODULE


GRAND CHALLENGE:GRAND CHALLENGE:

User Requirements/User Requirements/ApplicationsApplications

ArchitectureArchitectureand Topologyand Topology

CommunicationCommunicationProtocolsProtocols

HOW TO REALIZE THE MAPPING??


From User Requirements/Applications to From User Requirements/Applications to Network/Protocol DesignNetwork/Protocol Design

User Requirements/ApplicationsUser Requirements/Applications–– Coverage areaCoverage area–– Physical conditions (indoor, Physical conditions (indoor,

outdoor)outdoor)–– RealReal--time monitoring or delay time monitoring or delay

tolerant monitoringtolerant monitoring–– Network lifetimeNetwork lifetime–– Cost requirementsCost requirements–– Event type (frequency, priority Event type (frequency, priority

levels)levels)–– Type of sensor data (video, Type of sensor data (video,

audio, data)audio, data)–– SecuritySecurity

Architecture and TopologyArchitecture and Topology–– Number of nodesNumber of nodes–– Sensor types (acoustic, video,Sensor types (acoustic, video,

seismic, thermo)seismic, thermo)–– Deployment type (random or Deployment type (random or

deterministic)deterministic)

Protocol ParametersProtocol Parameters–– Sampling rateSampling rate–– Reporting rateReporting rate–– Error control codesError control codes–– MAC type MAC type –– Routing strategyRouting strategy–– Encryption techniqueEncryption technique


FURTHER GRAND CHALLENGESFURTHER GRAND CHALLENGES

Cost Reduction to CENTS ??

Deployment (Architecture) Decisions(optimum # of sensors, optimum # of sinks,optimal locations, fast deployment, reusability,terrain considerations)


FURTHER GRAND CHALLENGESFURTHER GRAND CHALLENGES

How to deal with TERABYTE of sensed information??Network Monitoring and Management?Graphical User Interface (GUIs)How to integrate WSNs into NGWI ? REALISTIC APPLICATIONS!!!!


SEMISEMI--GRAND CHALLENGE:GRAND CHALLENGE:Optimal Packet Size and Error Control for Optimal Packet Size and Error Control for WSNsWSNsY. Y. SankarasubramaniamSankarasubramaniam, I. F. , I. F. AkyildizAkyildiz, S. McLaughlin, , S. McLaughlin, ””Optimal Packet Size for Wireless Sensor NetworksOptimal Packet Size for Wireless Sensor Networks””, , IEEE SNPA, May 2003.IEEE SNPA, May 2003.

Determining the optimal packet size for sensor networks is necessary to operate at high energy efficiencies.The multihop wireless channel and energy consumption characteristics are the two most important factors that influence choice of packet size.

Payload (Payload (<=73<=73))Header (Header (22)) Trailer (FEC) (Trailer (FEC) (>=3>=3))


FURTHER PHYSICAL LAYER CHALLENGESFURTHER PHYSICAL LAYER CHALLENGES

New Channel Models (I/O/Underwater/Underground/Deep Space)New Channel Models (I/O/Underwater/Underground/Deep Space)

Explore Antenna TechniquesExplore Antenna Techniques

Cognitive Radios ??Cognitive Radios ??

UltraWideBandUltraWideBand ?? ??


Networks of wirelessly interconnected devices that allow retrieving video and audio streams, still images, and scalar sensor data.

Also able to store process in realAlso able to store process in real--time, correlate time, correlate and fuse multimedia data originated from and fuse multimedia data originated from heterogeneous sources.heterogeneous sources.

Wireless Multimedia Sensor NetworksWireless Multimedia Sensor NetworksI.F. I.F. AkyildizAkyildiz, T. , T. MelodiaMelodia, K. , K. ChowdhuryChowdhury, , ““A Survey on Wireless MultimedA Survey on Wireless MultimedSensor NetworksSensor Networks””,, Computer Networks (Elsevier), March 2007.Computer Networks (Elsevier), March 2007.


Wireless Multimedia Sensor NetworksWireless Multimedia Sensor Networks

(a)gle-tier flat, homogeneous sensors, ributed processing,ralized storage

(b)Single-tier clustered, heterogeneous sensors, centralized processing, centralized storage

(c)Multi-tier, heterogeneous sensors,distributed processing, distributed sto

InternetInternet

Gateway

Multimediaprocessing hubVideo sensorAudio sensorHigh end video sensor

Wireless gatew

LEGEND

Storage hub

Sink

Scalar sensor


Video SensorsVideo Sensors

Stargate board interfaced with a medium resolution cameraStargate hosts an 802.11 card and a MICAz mote that functions as gateway to the sensor network


StargateStargate + Garcia = Multimedia Mobile+ Garcia = Multimedia MobileSensorSensor

MobileMobileOnboard IR Sensors Onboard IR Sensors PanPan--tilt Cameratilt CameraConnects to a Connects to a MICAzMICAz networknetworkOnboard Linux Operating SystemOnboard Linux Operating System


SEVERAL RESEARCH CHALLENGESSEVERAL RESEARCH CHALLENGES

Differentiation between traffic types Differentiation between traffic types Integrated Traffic: (AUDIO, VIDEO, DATA, STILL IMAGE)–– Delay in/sensitive, Jitter in/sensitive, Loss Delay in/sensitive, Jitter in/sensitive, Loss

in/sensitive, Different data rates in/sensitive, Different data rates

Channel Allocation and Scheduling (Multimedia Channel Allocation and Scheduling (Multimedia Traffic Management)Traffic Management)


Resource ConstraintsVariable Channel CapacityApplication-Specific QoS RequirementsHigh Bandwidth DemandMultimedia Source Coding TechniquesPower ConsumptionIntegration with Internet (IP) Architecture and Other Wireless TechnologiesProtocols, algorithms and architectures to maximize the network lifetime while providing the QoS required by the application are a critical issue.

WMSNs CHALLENGES


FURTHER RESEARCH CHALLENGESFURTHER RESEARCH CHALLENGES

How to guarantee How to guarantee delay bounds and jitter bounds?delay bounds and jitter bounds?How to realize How to realize data aggregation?data aggregation?Explore the Explore the tradeoffstradeoffs between between quality and energy consumption!!quality and energy consumption!!Differentiation of TCP Differentiation of TCP vsvs UDP traffic UDP traffic Distributed source coding at different sensors Distributed source coding at different sensors How to realize routing satisfying How to realize routing satisfying QoSQoS requirements?requirements?How to do Medium Access Control for different traffic classes?How to do Medium Access Control for different traffic classes?Synchronization (intraSynchronization (intra--media, intermedia, inter--media)media)CrossCross--layer design for multimedia trafficlayer design for multimedia traffic


Sink

Task Manager

Wireless Sensor and Actor Networks I.F. I.F. AkyildizAkyildiz and I. H. and I. H. KasimogluKasimoglu, , ““Wireless Sensor and Actor Networks: Research ChallengesWireless Sensor and Actor Networks: Research Challenges””Ad Hoc Networks Journal (Elsevier), Oct. 2004.Ad Hoc Networks Journal (Elsevier), Oct. 2004.


Sub-Kilogram Intelligent Tele-robots (SKITs): Networked Robots having Coordination & WirelessCommunication Capabilities


Robotic Mule: Autonomous Battlefield Robot designed for the Army


Low Flying Helicopter Platform


GRAND CHALLENGESGRAND CHALLENGES

SensorSensor--Actor Coordination & CommunicationActor Coordination & Communication

ActorActor--Actor Coordination & CommunicationActor Coordination & Communication

REALREAL--TIME COMMUNICATION!!!!TIME COMMUNICATION!!!!


Challenges:Challenges:– Which sensor(s) communicate with which actor(s)?– How should the communication occur? – What are the requirements of the communication?(i.e., real-time, energy efficiency)

SENSOR-ACTOR COORDINATION


ACTORACTOR--ACTOR COORDINATIONACTOR COORDINATION

Challenges:Challenges:–– Which actor(s) should execute which Which actor(s) should execute which action(saction(s)?)?

–– What is the optimum number of actors What is the optimum number of actors performing the actions?performing the actions?

CURRENT PROJECT@GaTech: NSF & DoDExploring Spatial and Temporal Correlation for WSANs


A Distributed Coordination Framework for WSANsA Distributed Coordination Framework for WSANsT. Melodia, D. Pompili, C. Gungor, I. F. Akyildiz, Proc. ACM MOBIHOC Conference, Illinois, May 2005.to appear in IEEE Transactions on Mobile Computing, 2007

ComprehensiveComprehensive frameworkframework forfor coordinationcoordinationproblemsproblemsSENSORSENSOR--ACTORACTOR COORDINATIONCOORDINATION1.1. OptimalOptimal EventEvent--drivendriven ClusteringClustering2.2. A DistributedA Distributed ScalableScalable ProtocolProtocolACTORACTOR--ACTOR COORDINATIONACTOR COORDINATION3.3. OptimalOptimal SolutionSolution4.4. RealReal--timetime LocalizedLocalized AuctionAuction


Soil Condition Sensor

-Water-Salinity-Temperature

Underground Wireless Sensor NetworksUnderground Wireless Sensor NetworksI.F. Akyildiz and Erich Stuntebeck, “Underground Sensor Networks: Research Challenges”, Computer Networks (Elsevier) Journal, Nov. 2006.

Sink


Existing Underground Sensor TechnologyExisting Underground Sensor Technology

arge number of sensors wired to an above-ground data-logger, which uses wires, cellular, or long-range ingle-hop wireless for backhaul of

data

ROBLEM: Wired sensors are costly o deploy, datalogger units are

expensive, above-ground antennas and equipment may be unsightly

OLUTION: Underground wireless sensor nodes

Datalogge

Moistursensor


Underground Underground WSNsWSNs::Research ChallengesResearch Challenges

Dynamic ChannelDynamic ChannelPower ConstraintsPower ConstraintsVery Low Data RatesVery Low Data RatesExtremely Extremely LossyLossy EnvironmentEnvironmentNew Communication Protocols neededNew Communication Protocols needed

NOTE: OwnNOTE: Own field experiments: crossbow motes do not field experiments: crossbow motes do not communicate underground when they are more thancommunicate underground when they are more than0.5m apart. 0.5m apart.


I.F. Akyildiz, D. Pompili, T. Melodia, I.F. Akyildiz, D. Pompili, T. Melodia, ““Underwater Underwater Acoustic Sensor Networks: Research ChallengesAcoustic Sensor Networks: Research Challenges””,,Ad Hoc Networks (Elsevier) Journal, March 2005Ad Hoc Networks (Elsevier) Journal, March 2005

Drifters, Gliders

UNDERWATER SENSOR NETWORKSUNDERWATER SENSOR NETWORKS


Research Challenges for UW Sensor NetworkResearch Challenges for UW Sensor Network

• Available bandwidth is severely limited

• UW channel is severely impaired (in particular due to multi-path and fading)

• Very long and extremely variable propagation delays

. Very high bit error rates and temporary losses of connectivity (SHADOW ZONES)


Research Challenges for UW Sensor NetworkResearch Challenges for UW Sensor Network

. Battery power is limited and usually batteries cannot be recharged; no solar energy!!

• Very prone to failures because of fouling, corrosion, etc.

• New communication protocols needed!!


Wireless Mesh NetworksI.F. Akyildiz et.al., “Wireless Mesh Networks: Research Challenges”, Computer Networks (Elsevier) Journal, March 2005Shorter Version in IEEE Communication Magazine, Sept. 2005.


Mesh Routers


Zigbee Mesh Router @ BWN Lab


Mesh RoutersMesh Routers


MESH CLIENTS


CHARACTERISTICSCHARACTERISTICS

MultiMulti--hop Wireless Networkhop Wireless NetworkSupport for Ad Hoc Networking, and Capability of Support for Ad Hoc Networking, and Capability of SelfSelf--Forming, SelfForming, Self--Healing, and SelfHealing, and Self--OrganizationOrganizationMultiple radios and multiple channel systemsMultiple radios and multiple channel systemsMultiple Types of Network Access Multiple Types of Network Access ((WiMAXWiMAX, , WiFisWiFis))Advanced radio techniques: Advanced radio techniques: Directional and smart antennas, MIMO system, Directional and smart antennas, MIMO system, reconfigurable radios, frequency agile/cognitive radios, reconfigurable radios, frequency agile/cognitive radios, software radiossoftware radiosCompatible and Interoperable with Existing Wireless NetworksCompatible and Interoperable with Existing Wireless Networks


Application ScenariosApplication Scenarios

Broadband Home NetworkingBroadband Home NetworkingCommunity and Neighborhood NetworkingCommunity and Neighborhood NetworkingEnterprise NetworkingMetropolitan Area NetworksTransportation SystemsBuilding AutomationHealth and Medical SystemsSecurity Surveillance SystemsDisaster Relief Networks


ADVANTAGES OF ADVANTAGES OF WMNsWMNs

Very high reliabilityBudget reduction for capital, installation and commissioningReduced power consumptionAdaptiveReduced operation costsHighly flexible in terms of capacity, coverage and availability


MAC PROTOCOLSMAC PROTOCOLS

Single Channel Single Channel MACsMACs Multiple Channel Multiple Channel MACsMACs

Improving Existing MAC Protocols Improving Existing MAC Protocols Cross Cross--Layer Design with Advanced PHY LayerLayer Design with Advanced PHY LayerTechniquesTechniques

A. A. MACsMACs based on Directional Antennasbased on Directional AntennasB. B. MACsMACs with Power Controlwith Power Control

A. MultiA. Multi--Channel SingleChannel Single--Transceiver MACTransceiver MACB. MultiB. Multi--Channel and MultiChannel and Multi--Rate Rate MACsMACsC.C. MultiMulti--Channel MultiChannel Multi--Transceiver Transceiver MACMACD. MultiD. Multi--Radio Radio MACsMACs


MAC LAYER MAC LAYER -- Open Research IssuesOpen Research Issues

* * Scalable MultiScalable Multi--Channel Channel MACsMACs* MAC/Physical Cross* MAC/Physical Cross--Layer DesignLayer Design* Network Integration in the MAC Layer* Network Integration in the MAC Layer* MAC Protocol Implementation* MAC Protocol Implementation


Routing Layer Routing Layer -- Open Research IssuesOpen Research Issues

* Scalability* Scalability* More Accurate Performance Metrics* More Accurate Performance Metrics* Routing/MAC Cross* Routing/MAC Cross--Layer DesignLayer Design


Transport Layer Transport Layer -- Research ChallengesResearch Challenges

Effect of multi-channel operations Unfair service between short and long flowsHeterogeneous application requirements Dynamic network connectivityNetwork congestion and contention


Ugly TruthUgly Truth

The max available BW degrades at the rate of 1/2, 1/4, 1/8 depending on the number of hops. e.g., 4 hops away the max BW is 1/16 of the total available BW

Browsing and email do not count

Video (where both latency and BW matter) or VOIP (where BW is 64Kbps but latency matters) performance problems!

e.g., A simple 4 hop with 10 clients, VOIP phones will not work well beyond the first or second hop – the latency and jitter caused by CSMA/CA contention windows will be unbearable.


WMNsWMNs GREAT CONCEPTGREAT CONCEPT

* * Challenge:How to manage the dynamics of WMNs so users receive an acceptable level of performance in terms of both latency and throughput?


WiMAXWiMAX: New Broadband Last Mile: New Broadband Last Mile

WiWi--FiFi for the for the last one hundred feet (300 ft) last one hundred feet (300 ft) WiMAXWiMAX (Worldwide Interoperability for Microwave Access)(Worldwide Interoperability for Microwave Access)

for the last mile (30 miles)for the last mile (30 miles)Remote neighborhoods without Internet access via cable or DSLRemote neighborhoods without Internet access via cable or DSLEven in areas with cable or DSL access, Even in areas with cable or DSL access, an additional/cheaper alternative (less than $50/month).an additional/cheaper alternative (less than $50/month).Uplink and downlink up to 75 MbpsUplink and downlink up to 75 Mbps70 companies worldwide, including AT&T, 70 companies worldwide, including AT&T, CovadCovad and Intel. and Intel.


WiMAXWiMAX ARCHITECTUREARCHITECTURE


WiMAXWiMAX AntennaAntenna


Two Forms of Wireless ServiceTwo Forms of Wireless Service

1. Non1. Non--LineLine--ofof--Sight Service:Sight Service:((WiFiWiFi sort of service, where a small antenna on sort of service, where a small antenna on computer connects to the tower) computer connects to the tower) (2 GHz to 11 GHz)(2 GHz to 11 GHz)

2. Line2. Line--ofof--Sight ServiceSight Service::(A fixed dish antenna points straight at the (A fixed dish antenna points straight at the WiMAXWiMAX tower from a rooftop or pole) tower from a rooftop or pole) ((66 GHz)66 GHz)


RESEARCH CHALLENGESRESEARCH CHALLENGES

* Limited Radio Spectrum* High Cost* Incomplete Network Architecture* Interoperability testing and market field trials


Executive Summary

Project No.04-157: Communications Infrastructure for Electric System Automation

AN APPLICATION:Hybrid Network Architecture for Electrical System Automation

– Wireless Automatic Meter Reading (WAMR):Energy consumption statisticsEffective billing managementRemote activation and deactivation of the customer services

–– Electric System Monitoring:Electric System Monitoring:Equipment (e.g., distribution transformer, feeder, recloser/sectionalizer, capacitor, etc.) monitoringFast identification of service interruptions and incipient faultsTimely restoration of the electric utility services


Executive Summary

Project No.04-157: Communications Infrastructure for Electric System Automation

AN APPLICATION:Hybrid Network Architecture for Electrical System Automation


DYNAMIC SPECTRUM ALLOCATION NETWORKS (DSANCOGNITIVE RADIO NETWORKS; xG INIATIVE

Dynamic Spectrum Dynamic Spectrum AllocationAllocation


OVERALL VIEWOVERALL VIEW

Dynamic Spectrum Dynamic Spectrum AllocationAllocation

Applications

TCP/UDP

IP

MAC

Error Control

Physical

AdaptiveAdaptive

ProtocolProtocol

SuiteSuite

WirelessLANs & MANs

Cellular(2,3,4-G) Mesh Networks

SensorNetworks


RESEARCH CHALLENGES in RESEARCH CHALLENGES in DSANsDSANsI.F. I.F. AkyildizAkyildiz et.alet.al., ., ““Dynamic Spectrum Access Dynamic Spectrum Access Networks, Cognitive Radio NetworksNetworks, Cognitive Radio Networks: Research Challenges: Research ChallengesComputer Networks (Elsevier) Journal,Computer Networks (Elsevier) Journal, Sept. 2006.Sept. 2006.

* Architecture * Cognitive Radio Design* Mobility Management* Spectrum Management

* Spectrum Sensing* Spectrum Decision* Spectrum Handoff


RESEARCH CHALLENGES in RESEARCH CHALLENGES in DSANsDSANs

Spectrum Sharing• Sensing Algorithms• Interference Problems• Higher Level Protocols Adaptivity• Fairness and Security

key wireless networking technologies in the …staff.ustc.edu.cn/~xinming/wireless...

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