future networking paradigms (sensor networks and interplanetary internet) ian f. akyildiz broadband...

FUTURE NETWORKING PARADIGMS

(Sensor Networks and

InterPlanetary Internet)

Ian F. AkyildizIan F. Akyildiz

Broadband & Wireless Networking LaboratoryBroadband & Wireless Networking Laboratory

School of Electrical and Computer EngineeringSchool of Electrical and Computer Engineering

Georgia Institute of TechnologyGeorgia Institute of Technology

Tel: 404-894-5141; Fax: 404-894-7883 Tel: 404-894-5141; Fax: 404-894-7883

Email: [email protected]: [email protected]

Web: http://www.ece.gatech.edu/research/labs/bwnWeb: http://www.ece.gatech.edu/research/labs/bwn

2IFA’2004

Internet, Internet, Satellite, Satellite, etcetc

Sink

Sink

TaskManager

SENSOR NETWORKS ARCHITECTURE

Several Several thousand nodesthousand nodes

Nodes are tens Nodes are tens of feet of each of feet of each otherother

Densities as high Densities as high as 20 nodes/m3as 20 nodes/m3

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

3IFA’2004

SENSOR NODE SENSOR NODE HARDWAREHARDWARE

Power UnitPower Unit Power GeneratorPower Generator

Sensor ADCSensor ADCProcessorProcessor

MemoryMemoryTransceiverTransceiver

Location Finding SystemLocation Finding System MobilizerMobilizer

SmallSmall Low powerLow power Low bit rateLow bit rate High density High density Low cost (dispensable)Low cost (dispensable) AutonomousAutonomous AdaptiveAdaptive

SENSING UNITPROCESSING UNIT

4IFA’2004

MICA MotesMICA MotesBWN Lab @ GaTechBWN Lab @ GaTech

Processor and Radio platform (MPR300CB) is based on Atmel ATmega 128L low power Microcontroller that runs TinyOs operating system from its internal flash memory.

Processor/Radio Processor/Radio BoardBoard

MPR300CBMPR300CB

SpeedSpeed 4 MHz4 MHz

FlashFlash 128K bytes128K bytes

SRAMSRAM 4K bytes4K bytes

EEPROMEEPROM 4K bytes4K bytes

Radio FrequencyRadio Frequency 916MHz or 916MHz or 433MHz (ISM 433MHz (ISM Bands)Bands)

Data RateData Rate 40 Kbits/Sec 40 Kbits/Sec (Max)(Max)

Power Power 0.75 mW0.75 mW

Radio Range Radio Range 100 feet (prog.)100 feet (prog.)

PowerPower 2 x AA batteries2 x AA batteries

5IFA’2004

Examples for Sensor Examples for Sensor NodeNodess

UC Berkeley: COTS DustUC Berkeley:

Smart Dust

UCLA: WINS

Rockwell: WINS

JPL: Sensor Webs

6IFA’2004

Examples for Sensor Examples for Sensor NodeNodessRene Rene MoteMote

Dot Dot MoteMote

weC MoteMica node

7IFA’2004

SENSOR NETWORKS FEATURESSENSOR NETWORKS FEATURES

APPLICATIONS: APPLICATIONS: Military, Environmental, Health, Home, Space Exploration, Military, Environmental, Health, Home, Space Exploration, Chemical Processing, Disaster Relief…. Chemical Processing, Disaster Relief….

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

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

8IFA’2004

Factors Influencing Sensor Factors Influencing Sensor Network DesignNetwork Design

A. Fault Tolerance (Reliability)A. Fault Tolerance (Reliability)B. ScalabilityB. ScalabilityC. Production CostsC. Production CostsD. Hardware ConstraintsD. Hardware ConstraintsE. Sensor Network TopologyE. Sensor Network TopologyF. Operating EnvironmentF. Operating EnvironmentG. Transmission Media G. Transmission Media H. Power ConsumptionH. Power Consumption

9IFA’2004

Sensor Networks Sensor Networks Communication ArchitectureCommunication Architecture

Application LayerApplication Layer

Transport LayerTransport Layer

Network LayerNetwork Layer

Data Link LayerData Link Layer

Physical LayerPhysical Layer

Pow

er M

anagem

ent

Pow

er M

anagem

ent

Pla

ne

Pla

ne

Mobility

Managem

ent

Mobility

Managem

ent

Pla

ne

Pla

ne

Task M

anagem

ent P

lane

Task M

anagem

ent P

lane

Used by sink and all sensor nodesUsed by sink and all sensor nodes Combines power and routing awarenessCombines power and routing awareness Integrates data with networking protocolsIntegrates data with networking protocols Communicates power efficiently throughCommunicates power efficiently through wireless medium andwireless medium and Promotes cooperative efforts.Promotes cooperative efforts.

10IFA’2004

WHY CAN’T AD-HOC NETWORK PROTOCOLS BE USED HERE?

Number of sensor nodes can be several orders of magnitude higher

Sensor nodes are densely deployed and are prone to failures

The topology of a sensor network changes very frequently due to node mobility and node failure

Sensor nodes are limited in power, computational capacities, and memory

May not have global ID like IP address. Need tight integration with sensing tasks.

11IFA’2004

APPLICATON LAYERAPPLICATON LAYERSMP: Sensor Managament SMP: Sensor Managament ProtocolProtocolSystem Administrators interact with Sensors using SMP.System Administrators interact with Sensors using SMP.

TASKS:TASKS: Moving the sensor nodesMoving the sensor nodes Turning sensors on and offTurning sensors on and off Querying the sensor network configuration and the status Querying the sensor network configuration and the status

of of nodes and re-configuring the sensor networknodes and re-configuring the sensor network

Authentication, key distribution and security in dataAuthentication, key distribution and security in data communicationcommunication Time-synchronization of the sensor nodesTime-synchronization of the sensor nodes Exchanging data related to the location finding algorithmsExchanging data related to the location finding algorithms Introducing the rules related to data aggregation, Introducing the rules related to data aggregation, attribute-based naming and clustering to the sensor attribute-based naming and clustering to the sensor

nodesnodes

12IFA’2004

APPLICATON LAYERAPPLICATON LAYER(Query Processing)(Query Processing)

Users can request data from the network-> Users can request data from the network-> Efficient Query Efficient Query ProcessingProcessing

User Query Types:User Query Types:

1. 1. HISTORICAL QUERIES:HISTORICAL QUERIES:

Used for analysis of historical data stored in a storage area Used for analysis of historical data stored in a storage area (PC),(PC),

e.g., what was the temperature 2 hours back in the NW e.g., what was the temperature 2 hours back in the NW quadrant.quadrant.

2. ONE TIME QUERIES: 2. ONE TIME QUERIES:

Gives a snapshot of the network, Gives a snapshot of the network, e.g., what is the current e.g., what is the current temperature in the NW quadrant.temperature in the NW quadrant.

3. PERSISTANT QUERIES:3. PERSISTANT QUERIES:

Used to monitor the network over a time interval with Used to monitor the network over a time interval with respect to some parameters, respect to some parameters, e.g., report the temperature e.g., report the temperature for the next 2 hours.for the next 2 hours.

13IFA’2004

APPLICATON LAYERAPPLICATON LAYER

Sensor Query and Tasking Language (SQTL):Sensor Query and Tasking Language (SQTL):(C-C Shen, et.al., “Sensor Information Networking Architecture and Applications”, (C-C Shen, et.al., “Sensor Information Networking Architecture and Applications”, IEEE Personal Communications MagazineIEEE Personal Communications Magazine, pp. 52-59, August 2001.), pp. 52-59, August 2001.)

SQTL is a procedural scripting language.SQTL is a procedural scripting language. It provides interfaces to It provides interfaces to access sensor hardwareaccess sensor hardware: :

- getTemperature, turnOn- getTemperature, turnOn

for for location awarenesslocation awareness::

- isNeighbor, getPosition- isNeighbor, getPosition

and for and for communicationcommunication::

- tell, execute.- tell, execute.

14IFA’2004

APPLICATON LAYERAPPLICATON LAYER

Sensor Query and Tasking Language (SQTL):Sensor Query and Tasking Language (SQTL):

By using the By using the uponupon command, a programmer can command, a programmer can create an event handling block for three types of create an event handling block for three types of events:events:- - Events generated when a message is received by a sensor Events generated when a message is received by a sensor node,node,

- Events triggered periodically,- Events triggered periodically,

- Events caused by the expiration of a timer.- Events caused by the expiration of a timer.

These types of events are defined by SQTL These types of events are defined by SQTL keywordskeywords receivereceive, , everyevery and and expireexpire, respectively., respectively.

16IFA’2004

Data Centric QueryData Centric Query

Attribute-based Attribute-based naming naming architecturearchitecture

Data centric Data centric protocolprotocol

Observer sends a Observer sends a query and gets query and gets the response from the response from valid sensor nodevalid sensor node

No global IDNo global ID

17IFA’2004

APPLICATON LAYER APPLICATON LAYER Task Assignment and Data Advertisement Task Assignment and Data Advertisement ProtocolProtocol

INTEREST DISSEMINATIONINTEREST DISSEMINATION * * Users send their interest to a sensor Users send their interest to a sensor node, node, a subset of the nodes or the entire a subset of the nodes or the entire network.network. * This interest may be about a certain * This interest may be about a certain attribute attribute of the sensor field or a triggering event.of the sensor field or a triggering event.

ADVERTISEMENT OF AVAILABLE DATAADVERTISEMENT OF AVAILABLE DATA * * Sensor nodes advertise the available Sensor nodes advertise the available data to data to the users and the users query the data the users and the users query the data which which they are interested in.they are interested in.

18IFA’2004

APPLICATON LAYERAPPLICATON LAYERSensor Query and Data Dissemination Sensor Query and Data Dissemination ProtocolProtocol

Provides user applicatons with interfaces to issue queries, respond to queries and collect incoming replies.These queries are not issued to particular nodes, instead

ATTRIBUTE BASED NAMING (QUERY) “The locations of the nodes that sense temperature higher than 70F”LOCATION BASED NAMING (QUERY) “Temperatures read by the nodes in region A”

19IFA’2004

Interest DisseminationInterest Dissemination

SinkSink

Query:Query:

Sensor nodes that read >70Sensor nodes that read >70ooF F temperaturetemperature

7171

6868

6868

6969

7171

7575

7171

6767

7171

6666

Interest dissemination is performed to assign the sensing tasks to the sensor nodes. Either sinks broadcast the interest or sensor nodes broadcast an advertisement for the available data and wait for a request from the sinks.

20IFA’2004

Data Aggregation (Data Data Aggregation (Data Fusion)Fusion)

Query:Query:

Sensor nodes that read >70Sensor nodes that read >70ooF F temperaturetemperature

7171

7575

SinkSink

6868

6868

6969

71717171

6767

7171

6666

The sink asks the sensor nodes to report certain conditions. Data coming from multiple sensor nodes are aggregated.

21IFA’2004

Location Awareness Location Awareness (Attribute Based Naming)(Attribute Based Naming)

SinkSink

Query:Query:

Temperatures read by the nodes Temperatures read by the nodes in Region A in Region A

7171

6868

6868

6969

7171

7575

7171

6767

7171

6666

Region ARegion A

Region BRegion B

Region CRegion C

Query an Attribute of the sensor field

Important for broadcasting, multicasting, geocasting and anycasting

22IFA’2004

APPLICATON LAYER RESEARCH APPLICATON LAYER RESEARCH NEEDSNEEDS

Sensor Network Management ProtocolSensor Network Management Protocol Task Assignment and Data Advertisement Task Assignment and Data Advertisement ProtocolProtocol Sensor Query and Data Dissemination Sensor Query and Data Dissemination ProtocolProtocol Sophisticated GUI Sophisticated GUI

(Graphical User Interface) Tool(Graphical User Interface) Tool

23IFA’2004

TRANSPORT LAYERTRANSPORT LAYERReliable Multi-Segment Transport Reliable Multi-Segment Transport (RMST)(RMST) F. Stann and J. Heidemann, “RMST: Reliable Data Transport in Sensor Networks,” In Proc. IEEE SNPA’03, May 2003, Anchorage, Alaska, USA

SinkSink

RMST NodeRMST Node

Source Node

RMST provides end-to-end data-RMST provides end-to-end data-packetpacket transfer reliabilitytransfer reliability Each RMST node caches the packetsEach RMST node caches the packets When a packet is not received before When a packet is not received before the the so-called WATCHDOG timer expires, so-called WATCHDOG timer expires, a a NAK is sent backward NAK is sent backward The first RMST node that has the The first RMST node that has the requiredrequired packet along the path retransmitpacket along the path retransmitss the the packetpacket

RMST relies on RMST relies on Directed DiffusionDirected Diffusion schemescheme

24IFA’2004

Transport Layer Transport Layer PSFQ - Pump Slowly Fetch PSFQ - Pump Slowly Fetch QuicklyQuicklyC. C. Y. Wan, A. T. Campbell and L. Krishnamurthy, Y. Wan, A. T. Campbell and L. Krishnamurthy,

“PSFQ: A Reliable Transport Protocol for Wireless Sensor Networks“PSFQ: A Reliable Transport Protocol for Wireless Sensor Networks,” ,” In In Proc. ACM WSNA’02Proc. ACM WSNA’02, September 2002, Atlanta, GA, September 2002, Atlanta, GA

– Packets are injected slowly into the networkPackets are injected slowly into the network– Aggressive hop-by-hop recovery in case of packet lossesAggressive hop-by-hop recovery in case of packet losses– ““PUMP” performs controlled flooding and requires each PUMP” performs controlled flooding and requires each

intermediate node to create and maintain a data cache intermediate node to create and maintain a data cache to be used for local loss recovery and in-sequence data to be used for local loss recovery and in-sequence data delivery.delivery.

– Applicable only to strict sensor-sensor guaranteed Applicable only to strict sensor-sensor guaranteed deliverydelivery

– And for control and management of the end-to-end And for control and management of the end-to-end reliability for the downlink from sink to sensorsreliability for the downlink from sink to sensors

– Does not address congestion controlDoes not address congestion control

25IFA’2004

Related WorkRelated Work

Wireless TCP variants are NOT suitable for Wireless TCP variants are NOT suitable for sensor networkssensor networks– Different notion of end-to-end reliabilityDifferent notion of end-to-end reliability– Huge buffering requirementsHuge buffering requirements– ACKing is energy drainingACKing is energy draining

BOTTOMLINE:BOTTOMLINE: Traditional end-to-end Traditional end-to-end guaranteed reliability guaranteed reliability (TCP solutions)(TCP solutions) cannot be applied here.cannot be applied here.

New Reliability Notion is required!!!New Reliability Notion is required!!!

26IFA’2004

Reliable EVENT Transport in WSN

NEW NOTION: Reliably Detect/Estimate EVENT features from COLLECTIVE information

Challenges: – Significant energy and processing constraints, multi-hop ad

hoc communication– Network congestion

Need to address Need to address Congestion Congestion ControlControland and ReliabilityReliability in Sensor in Sensor Networks !Networks !

27IFA’2004

Event Radius Sink

Sensor nodes

Event-to-Sink Event-to-Sink ReliabilityReliability

Sensor networks are Sensor networks are event-drivenevent-driven Multiple correlated data flows from event to Multiple correlated data flows from event to

sink sink Goal is to reliably detect/estimate event Goal is to reliably detect/estimate event

features from collective informationfeatures from collective information Necessitates Necessitates event-to-sink collective reliability event-to-sink collective reliability

notionnotion

O. B. Akan, I. F. Akyildiz, and Y. Sankarasubramaniam, “ESRT:Event-to-O. B. Akan, I. F. Akyildiz, and Y. Sankarasubramaniam, “ESRT:Event-to-Sink Reliable Transport in Wireless Sensor Networks,”Sink Reliable Transport in Wireless Sensor Networks,” in in Proceedings Proceedings of ACM MOBIHOC 2003,of ACM MOBIHOC 2003, pp. 177-188, Annapolis, Maryland, USA, June pp. 177-188, Annapolis, Maryland, USA, June 2003. 2003.

Also tAlso to appear in IEEE/ACM Transactions on Networkingo appear in IEEE/ACM Transactions on Networking,, 2004.2004.

28IFA’2004

Event Radius Sink

Sensor nodes

Event-to-Sink Event-to-Sink ReliabilityReliability

Sink decides about event features every Sink decides about event features every time units time units Observed event reliability DObserved event reliability Di i , the DISTORTION observed , the DISTORTION observed

in event estimation in the decision interval in event estimation in the decision interval i i at the sinkat the sink Desired event reliabilityDesired event reliability D*D* ,the desired event estimation ,the desired event estimation

distortion level for reliable event detection distortion level for reliable event detection – Application specific, known a priori at the sinkApplication specific, known a priori at the sink

Normalized reliability Normalized reliability i i == D*/D*/ DDii Reporting rate Reporting rate ff packet transmissions rate at source packet transmissions rate at source

nodes nodes

29IFA’2004

StateState DescriptionDescription ConditionCondition

(NC,LR)(NC,LR) (No Congestion, Low reliability)(No Congestion, Low reliability) f < ff < fmaxmax and and < 1 - < 1 -

(NC,HR)(NC,HR) (No Congestion, High reliability)(No Congestion, High reliability) f f f fmaxmax and and > 1+ > 1+

(C,HR)(C,HR) (Congestion, High reliability)(Congestion, High reliability) f > ff > fmaxmax and and > 1 > 1

(C,LR)(C,LR) (Congestion, Low reliability)(Congestion, Low reliability) f > ff > fmaxmax and and 1 1

OOROOR Optimal Operating RegionOptimal Operating Region f < ff < fmaxmax and and [[1- 1- , 1+ , 1+ ]]

Network StatesNetwork States

30IFA’2004

f

ESRTESRTProtocol OverviewProtocol Overview

Determine reporting frequency f to achieve desired reliability D* with minimum resource utilization

Source (Sensor nodes): – Send data with reporting frequency f – Monitor buffer level and notify congestion to the sink

Sink: – Measures the observed event reliability Di at the end of

decision interval i – Performs congestion decision based on the feedback

from the sources nodes (to determine f >

< fmax). – Updates f based on i = D*/ Di and f >

< fmax (congestion) to achieve desired event reliability D*

31IFA’2004

ESRT ESRT Congestion Detection Congestion Detection MechanismMechanism

ACK/NACK not suitableACK/NACK not suitable We use local buffer level monitoring in We use local buffer level monitoring in

sensor nodes sensor nodes

Mark Mark CNCN field in packet if congested field in packet if congested

bk bk-1

b

B

f

Event

IDCNCN

(1 bit)Destinatio

n

Time

Stamp Payload FEC

bk : Buffer fullness level at the end of reporting interval k

b : Buffer length increment

B : Buffer size

f : reporting frequency

32IFA’2004

StateState Frequency UpdateFrequency Update CommentsComments

(NC,LR)(NC,LR) ffi+1i+1 = f = fi i / / ii Multiplicative increase, achieve desired Multiplicative increase, achieve desired reliability asapreliability asap

(NC,HR)(NC,HR) ffi+1i+1 = f = fi i ((i i + 1) / 2+ 1) / 2ii Conservative decrease, no compromise on Conservative decrease, no compromise on reliabilityreliability

(C,HR)(C,HR) ffi+1i+1 = f = fi i / / ii Aggressive decrease to state (NC,HR)Aggressive decrease to state (NC,HR)

(C,LR)(C,LR) ffi+1i+1 = f = fi i ii Exponential decrease, relieve congestion Exponential decrease, relieve congestion

asapasap

OOROOR ffi+1i+1 = f = fii UnchangedUnchanged

ESRT OperationESRT OperationFrequency UpdateFrequency Update

33IFA’2004

S0 = (NC,LR) S0 = (NC,HR)

S0 = (C,HR) S0 = (C,LR)

ESRT PerformanceESRT Performance

34IFA’2004

NETWORK LAYER NETWORK LAYER (ROUTING(ROUTING BASIC KNOWLEDGE) BASIC KNOWLEDGE)

The constraints to calculate the routes:The constraints to calculate the routes:1. Additive Metrics: 1. Additive Metrics: Delay, hop count, distance, assigned costs (sysadmin Delay, hop count, distance, assigned costs (sysadmin preference), preference), average queue length...average queue length...

2. Bottleneck Metrics: 2. Bottleneck Metrics: Bandwidth, residual capacity and other bandwidth Bandwidth, residual capacity and other bandwidth related metrics. related metrics.

REMARK:REMARK:All routing algorithms are based on the same principle used as in All routing algorithms are based on the same principle used as in Dijkstra's, Dijkstra's, which is used to find the which is used to find the minimum cost pathminimum cost path from source to from source to destination.destination.Dikstra and Bellman solve the SHORTEST PATH PROBLEM…Dikstra and Bellman solve the SHORTEST PATH PROBLEM…RIP (Distant Vector Algorithm) -> Bellman/Ford AlgorithmRIP (Distant Vector Algorithm) -> Bellman/Ford AlgorithmOSPF (Open Shortest Path Algorithm) OSPF (Open Shortest Path Algorithm) Dikstra Algorithm Dikstra Algorithm

35IFA’2004

Routing Algorithms Constraints Regarding Power Efficiency (Energy Efficient Routing)

SinkSink

E (PA=1)E (PA=1) F (PA=4)F (PA=4)

D (PA=3)D (PA=3)

A (PA=2)A (PA=2)B (PA=2)B (PA=2)

C (PA=2)C (PA=2)

TT

Route 1: Sink-A-B-T (PA=4)Route 1: Sink-A-B-T (PA=4)Route 2: Sink-A-B-C-T (PA=6)Route 2: Sink-A-B-C-T (PA=6)Route 3: Sink-D-T (PA=3)Route 3: Sink-D-T (PA=3)Route 4: Sink-E-F-T (PA=5)Route 4: Sink-E-F-T (PA=5)

Maximum power available (PA) routeMaximum power available (PA) route Minimum hop routeMinimum hop route Minimum energy routeMinimum energy route Maximum minimum PA node Maximum minimum PA node routeroute (Route along which the (Route along which the minimum PA is larger than the minimum PA is larger than the minimum PAs of the other routesminimum PAs of the other routes is preferred, e.g., Route 3 is the is preferred, e.g., Route 3 is the most efficient; Route 1 is the most efficient; Route 1 is the second).second).

36IFA’2004

Global (Unique) addresses, local addresses.

Unique node addresses cannot be used in many sensor networks

- sheer number of nodes- energy constraints- data centric approach

Node addressing is needed for- node management- sensor management- querying- data aggregation and fusion- service discovery- routing

Why can’t we use conventional routing algorithms here?

37IFA’2004

NETWORK LAYER NETWORK LAYER (ROUTING for SENSOR NETWORKS)(ROUTING for SENSOR NETWORKS)

Important considerations:Important considerations:

Sensor networks are mostly data Sensor networks are mostly data centriccentric

An ideal sensor network has attribute An ideal sensor network has attribute based addressing and location based addressing and location awarenessawareness

Data aggregation is useful unless it Data aggregation is useful unless it does not hinder collaborative effortdoes not hinder collaborative effort

Power efficiency is always a key factorPower efficiency is always a key factor

38IFA’2004

Some ConceptsSome Concepts

Data-Centric– Node doesn't need an identity

What is the temp at node #27 ?

– Data is named by attributesWhere are the nodes whose temp recently exceeded

30 degrees ? How many pedestrians do you observe in region X? How many pedestrians do you observe in region X? Tell me in what direction that vehicle in region Y is Tell me in what direction that vehicle in region Y is

moving?moving?

Application-Specific– Nodes can perform application specific

data aggregation, caching and forwarding

39IFA’2004

Taxonomy of Routing Taxonomy of Routing ProtocolsProtocols for Sensor Networksfor Sensor NetworksCategorization of Routing Protocols for Wireless Sensor

Networks:(K. Akkaya, M. Younis, “A Survey on Routing Protocols for Wireless Sensor Networks,” Elsevier AdHoc (K. Akkaya, M. Younis, “A Survey on Routing Protocols for Wireless Sensor Networks,” Elsevier AdHoc Networks, 2004)Networks, 2004)

1. Data Centric Protocols Flooding, Gossiping, SPIN, SAR (Sequential Assignment Routing) , Directed Diffusion, Rumor Routing, Gradient Based Routing, Constrained Anisotropic Diffused Routing, COUGAR, ACQUIRE

2. Hierarchical LEACH, TEEN (Threshold Sensitive Energy Efficient Sensor Network

Protocol), APTEEN, PEGASIS, Energy Aware Scheme

3. Location Based MECN, SMECN (Small Minimum Energy Com Netw), GAF (Geographic Adaptive Fidelity), GEAR

40IFA’2004

Conventional Conventional ApproachApproachFLOODINGFLOODING

B

D E

FG

C

A

Broadcast data to all neighbor nodesBroadcast data to all neighbor nodes

41IFA’2004

ROUTING ALGORITHMSROUTING ALGORITHMSGossipingGossiping

GOSSIPING:Sends data to one randomly selected neighbor.

Example:Example:

42IFA’2004

Problems ofFlooding and Gossiping

PROBLEMS:PROBLEMS:

Although these techniques are simple and Although these techniques are simple and reactive, they have some disadvantages reactive, they have some disadvantages including: including:

* * Implosion (NOTE: Gossiping avoids this by selecting only one node; but this causes delays to propagate the data through the network)

* Overlap * Resource Blindness * Power (Energy) Inefficient

43IFA’2004

ProblemsProblems

A B

C (r,s)(q,r)

q s

Data OverlapData OverlapImplosionImplosion

A

B C

D

(a)

(a)

(a)

(a)

Resource BlindnessResource Blindness

No knowledge about the available power of resourcesNo knowledge about the available power of resources

r

44IFA’2004

GossipingGossiping

Uses randomization to save energyUses randomization to save energySelects a single node at random and sends the Selects a single node at random and sends the data to itdata to it

Avoids implosionsAvoids implosions Distributes information slowlyDistributes information slowly Energy dissipates slowlyEnergy dissipates slowly

45IFA’2004

The Optimum The Optimum ProtocolProtocol

B

D E

FG

C

A““Ideal”Ideal”

– Shortest-path routesShortest-path routes– Avoids overlapAvoids overlap– Minimum energyMinimum energy– Need global topology Need global topology

informationinformation

46IFA’2004

SPIN: Sensor Protocol for Information via Negotiation(W.R. Heinzelman, J. Kulik, and H. Balakrishan, “Adaptive Protocols for (W.R. Heinzelman, J. Kulik, and H. Balakrishan, “Adaptive Protocols for Information Dissemination in Wireless Sensor Networks”,Information Dissemination in Wireless Sensor Networks”, Proc. ACM MobiCom’99Proc. ACM MobiCom’99, pp. 174-185, 1999 ), pp. 174-185, 1999 )

Two basic ideas:Two basic ideas: Sensors communicate with each other Sensors communicate with each other

about the data that they already have about the data that they already have and the data they still need to obtainand the data they still need to obtain

to conserve energy and operate efficientlyto conserve energy and operate efficiently exchanging data exchanging data aboutabout sensor data may be sensor data may be

cheapcheap

Sensors must monitor and adapt to Sensors must monitor and adapt to changeschanges

in their own energy resourcesin their own energy resources

47IFA’2004

SPINSPIN

Good for disseminating information to all sensor nodes.Good for disseminating information to all sensor nodes. SPIN is based on data-centric routing where the sensors SPIN is based on data-centric routing where the sensors broadcast an broadcast an advertisement for the available data and wait for a request from advertisement for the available data and wait for a request from interested sinksinterested sinks

1. ADV1. ADV2. REQ2. REQ3. DATA3. DATA

1.1.

2.2.

3.3.

48IFA’2004

SPINSPIN

ADVADVREQREQ

DATADATA

ADVADVREQREQDATADATA

49IFA’2004

ROUTING ALGORITHMROUTING ALGORITHM(DIRECTED DIFFUSION)(DIRECTED DIFFUSION)

(C. Intanagonwiwat, R. Gowindan and D. Estrin, “Directed Diffusion: A Scalable and Robust (C. Intanagonwiwat, R. Gowindan and D. Estrin, “Directed Diffusion: A Scalable and Robust

Communication Paradigm for Sensor Networks”, Communication Paradigm for Sensor Networks”, Proc. ACM MobiCom’00Proc. ACM MobiCom’00, pp. 56-67, 2000.), pp. 56-67, 2000.)

- This is a DATA CENTRIC ROUTING scheme!!!!This is a DATA CENTRIC ROUTING scheme!!!!- The idea aims at diffusing data through sensor nodes by The idea aims at diffusing data through sensor nodes by using using

a a naming schemenaming scheme for the data. for the data.- The main reason behind this is to get rid off The main reason behind this is to get rid off unnecessaryunnecessary

operation of routing schemes tooperation of routing schemes to save save EnergyEnergy..

Also Also RobustnessRobustness and and ScalingScaling requirements need to be requirements need to be considered.considered.

50IFA’2004

Directed DiffusionDirected Diffusion

Interest PropagationInterest Propagation

SourceSource SinkSink

Gradient SetupGradient SetupData DeliveryData Delivery

51IFA’2004

Directed DiffusionDirected Diffusion

FeaturesFeatures

Sink sends interest, i.e., task descriptor, to all sensor nodes.Sink sends interest, i.e., task descriptor, to all sensor nodes. Interest is named by assigning attribute-value pairs.Interest is named by assigning attribute-value pairs.

sinksink

sourcesource

sinksink

sourcesource

sinksink

sourcesource

Interest PropagationInterest Propagation Gradient SetupGradient Setup Data DeliveryData Delivery

DrawbacksDrawbacks

Cannot change interest unless a new interest is broadcast.Cannot change interest unless a new interest is broadcast.

52IFA’2004

LEACHLEACH

Low Energy Adaptive Clustering Hierarchy Low Energy Adaptive Clustering Hierarchy (LEACH)(LEACH)(W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy-Efficient (W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy-Efficient Communication Protocol for Wireless Microsensor Networks,'' Communication Protocol for Wireless Microsensor Networks,'' IEEE IEEE Proceedings of the Hawaii International Conference on System SciencesProceedings of the Hawaii International Conference on System Sciences, pp. , pp. 1-10, January, 2000.)1-10, January, 2000.)

- * * LEACH is a clustering based protocol which minimizes LEACH is a clustering based protocol which minimizes energy dissipation energy dissipation

in sensor networks.in sensor networks.

Idea:Idea:

* Randomly select sensor nodes as cluster heads, so the * Randomly select sensor nodes as cluster heads, so the high energyhigh energy

dissipation in communicating with the base station is dissipation in communicating with the base station is spread to all sensor spread to all sensor

nodes in the sensor network. nodes in the sensor network.

* Forming clusters is based on the received signal * Forming clusters is based on the received signal strength.strength.

* Cluster heads can then be used kind of routers (relays) * Cluster heads can then be used kind of routers (relays) to the sink.to the sink.

-

53IFA’2004

LEACHLEACH

Optimum Number of Clusters ---????????

- too few: nodes far from cluster heads– too many: many nodes send data to SINK.

54IFA’2004

Other ProtocolsOther Protocols

1. Energy Aware Routing R. Shah, J. Rabaey, “Energy Aware Routing for Low Energy Ad Hoc Sensor Networks,” IEEE WCNC’02, Orlando, March 2002.

2. Rumor Routing D. Braginsky, D. Estrin, “Rumor Routing Algorithm for Sensor Networks,” ACM WSNA’02, Atlanta, October 2002.

3. Threshold sensitive Energy Efficient sensor Network (TEEN) A. Manjeshwar, D.P. Agrawal, “TEEN: A Protocol for Enhanced Efficiency in Wireless Sensor Networks,” IEEE WCNC’02, Orlando, March 2002.

4. Constrained Anisotropic Diffusion Routing (CADR) M. Chu, H.Hausecker, F. Zhao, “Scalable Information-Driven Sensor Querying and Routing for Ad Hoc Heterogeneous Sensor Networks,” International Journal of High Performance Computing Applications, Vol. 16, No. 3, August 2002.

55IFA’2004

Other ProtocolsOther Protocols

5. Power Efficient Gathering in Sensor Information Systems (PEGASIS) S. Lindsey, C.S. Raghavendra, “PEGASIS: Power Efficient Gathering in Sensor Information Systems,” IEEE Aerospace Conference, Montana, March 2002.

6. Self Organizing Protocol L. Subramanian, R.H. Katz, “An Architecture for Building Self Configurable Systems,” IEEE/ACM Workshop on Mobile Ad Hoc Networking and Computing, Boston, August 2000.

7. Geographic Adaptive Fidelity (GAF) Y. Yu, J. Heideman, D. Estrin, “Geography-informed Energy Conservation for Ad Hoc Routing,” ACM MobiCom’01, Rome, July 2001.

56IFA’2004

Open Research Open Research IssuesIssues

• Store and Forward Technique that combines data fusion and aggregation.

• Routing for Mobile Sensors Investigate multi-hop routing techniques for high mobility environments.

• Priority Routing Design routing techniques that allow different priority of data to be aggregated, fused, and relayed.

• 3D Routing

57IFA’2004

Medium Access Control (MAC) in WSNMedium Access Control (MAC) in WSN

IEEE 802.11 [1] – Originally developed for WLANs – Per-node fairness– High energy consumption due to idle

listening S-MAC [2]

– Aims to decrease energy consumption by sleep schedules with virtual clustering

– Redundant data are still sent with increased latency due to sleep schedules

[1] IEEE 802.11, “Wireless LAN Medium Access Control (MAC) and Physical Layer [1] IEEE 802.11, “Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications,” 1999(PHY) Specifications,” 1999[2] W. Ye, J. Heidemann and D. Estrin, “An Energy Efficient MAC Protocol for [2] W. Ye, J. Heidemann and D. Estrin, “An Energy Efficient MAC Protocol for Wireless Sensor Networks,” Wireless Sensor Networks,” In Proc. ACM MOBICOM ’01, In Proc. ACM MOBICOM ’01, pp.221 –235, Rome, pp.221 –235, Rome, Italy 2001Italy 2001

58IFA’2004

Related WorkRelated Work TRAMA[3] TRAMA[3]

– Based on time-slotted structure Based on time-slotted structure – Information about every two-hop neighbor is Information about every two-hop neighbor is

used for slot selectionused for slot selection– High signaling overhead for high density High signaling overhead for high density

networksnetworks– High latency due to time-slotted structureHigh latency due to time-slotted structure

[3] V. Rajendran, K. Obraczka, and J. J. Garcia-Luna-Aceves, [3] V. Rajendran, K. Obraczka, and J. J. Garcia-Luna-Aceves, “Energy-Efficient, Collision-Free Medium Access Control for “Energy-Efficient, Collision-Free Medium Access Control for Wireless Sensor Networks,” in Wireless Sensor Networks,” in Proc. ACM SenSys 2003Proc. ACM SenSys 2003, Los , Los Angeles, California, November 2003.Angeles, California, November 2003.

59IFA’2004

MAC for Sensor NetworksMAC for Sensor Networks

WSN are characterized by dense deployment of sensor WSN are characterized by dense deployment of sensor nodesnodes

MAC Layer ChallengesMAC Layer Challenges– Limited power resourcesLimited power resources– Need for a self-configurable, distributed protocolNeed for a self-configurable, distributed protocol– Data centric approach rather than per-node fairnessData centric approach rather than per-node fairness

Exploit Exploit spatial correlationspatial correlation to to reduce transmissions in MAC reduce transmissions in MAC layer !layer !

60IFA’2004

If a node transmits data then all its If a node transmits data then all its correlation neighbors have redundant correlation neighbors have redundant informationinformation

Route-thru data has higher priority Route-thru data has higher priority over generated dataover generated data

Filter outFilter out transmission of transmission of redundant data and redundant data and prioritizeprioritize filtered data through the network!filtered data through the network!

M.C. Vuran, and I. F. Akyildiz, “Spatial Correlation-M.C. Vuran, and I. F. Akyildiz, “Spatial Correlation-based Collaborative Medium Access Control in Wireless based Collaborative Medium Access Control in Wireless Sensor Networks,”Sensor Networks,” submitted for publicationsubmitted for publication, Nov. , Nov. 2003.2003.

Collaborative MAC (CMAC) Collaborative MAC (CMAC) ProtocolProtocol

61IFA’2004

Collaborative MAC (CMAC) Collaborative MAC (CMAC) ProtocolProtocol

Source function: Source function: Transmit event Transmit event informationinformation

Router function: Router function: Forward packets from Forward packets from other nodes in the multi-other nodes in the multi-hop path to the sinkhop path to the sink

Two componentsTwo components– Event MAC (E-MAC)Event MAC (E-MAC)– Network MAC Network MAC

(N-MAC)(N-MAC)

62IFA’2004

Node SelectionsNode Selections

Choose representative nodes such thatChoose representative nodes such that– They are located as close to the event They are located as close to the event

source as possiblesource as possible– They are located as farther apart from They are located as farther apart from

each other as possibleeach other as possible.

63IFA’2004

CMAC PerformanceCMAC Performance

Medium Access Delay Packet Drop Rate

64IFA’2004

CMAC PerformanceCMAC Performance

Avg. Energy Consumption

65IFA’2004

ConclusionsConclusions

Spatial correlation in sensor networks is Spatial correlation in sensor networks is exploited on both Transport and MAC exploited on both Transport and MAC layerslayers

Redundant transmissions are suppressedRedundant transmissions are suppressed Number of transmissions are reduced Number of transmissions are reduced

instead of number of transmitted bitsinstead of number of transmitted bits Both protocols achieve low energy Both protocols achieve low energy

consumptionconsumption

66IFA’2004

Research Needs for Sensor Research Needs for Sensor NetworksNetworks

• An Analytical Framework for Sensor Networks Find a Basic Generic Architecture and Protocol development which can be tailored to specific applications.• More theoretical investigations of the Architecture and Protocol developments• Follow the TCP/IP Stack, i.e., keep the Strict Layer Approach ???• Cross Layer Optimization• Explore both Spatial-Temporal Correlations for Protocol development

67IFA’2004

FURTHER OPEN RESEARCH FURTHER OPEN RESEARCH ISSUESISSUES

Research to Research to integrate WSN domain into integrate WSN domain into NGWI NGWI (Next Generation Wireless Internet)(Next Generation Wireless Internet)

e.g., interactions of Sensor and AdHoc e.g., interactions of Sensor and AdHoc Networks or Sensor and Satellite or any Networks or Sensor and Satellite or any other combinations…other combinations…

Explore the SENSOR/ACTOR NETWORKSExplore the SENSOR/ACTOR NETWORKS

Explore the SENSOR-ANTISENSOR Explore the SENSOR-ANTISENSOR NETWORKSNETWORKS

68IFA’2004

Need for Realistic Need for Realistic ApplicationsApplications

• Clear Demonstration of Testbeds and Realistic Applications

• Not only data or audio but also video Overall I Integrated Traffic.

SOME OF OUR EFFORTS IN BWN LAB @ GaTech

• MAN for Meteorological Observations• SpINet for Mars Surface• Airport Security Sensors/Actors• Sensor Wars• Wide Area Multi-Campus Sensor Network

69IFA’2004

MEDIUM ACCESS CONTROL MEDIUM ACCESS CONTROL (MAC) (MAC) FURTHER RESEARCH NEEDSFURTHER RESEARCH NEEDS

MAC for sensor networks must have inbuilt MAC for sensor networks must have inbuilt power power

management, mobility management and failure management, mobility management and failure recovery recovery

strategiesstrategies Need for a self-configurable, distributed Need for a self-configurable, distributed protocolsprotocols Data centric approach rather than per-node Data centric approach rather than per-node fairnessfairness Develop MACs which differentiate Multimedia Develop MACs which differentiate Multimedia TrafficTraffic

Exploit Exploit Spatial & Temporal CorrelationSpatial & Temporal Correlation

70IFA’2004

Some sensor network applications like mobile Some sensor network applications like mobile trackingtracking require high data precisionrequire high data precision

Coding gain is generally expressed in terms of the Coding gain is generally expressed in terms of the additionaladditional transmit power needed to obtain the same BER transmit power needed to obtain the same BER without codingwithout coding

FEC is preferred over ARQFEC is preferred over ARQ

Since power consumption is crucial, we must take Since power consumption is crucial, we must take intointo account encoding and decoding energy account encoding and decoding energy expendituresexpenditures

Coding is profitable only if the encoding and decodingCoding is profitable only if the encoding and decoding power consumption is less than the coding gain.power consumption is less than the coding gain.

Error ControlError Control

71IFA’2004

ERROR CONTROL ERROR CONTROL RESEARCH NEEDSRESEARCH NEEDS

Design of suitable FEC codes with minimal Design of suitable FEC codes with minimal encoding encoding and relatively higher decoding complexitiesand relatively higher decoding complexities

Feasibility of ARQ schemes in multihop sensor Feasibility of ARQ schemes in multihop sensor networks networks (hop by hop ARQ instead of end-to-end). This is (hop by hop ARQ instead of end-to-end). This is needed for needed for reliable communications (data critical)reliable communications (data critical)

Adaptive/Hybrid FEC/ARQ schemes Adaptive/Hybrid FEC/ARQ schemes

Extension to Rayleigh/Rician fading conditions Extension to Rayleigh/Rician fading conditions with mobilewith mobile nodesnodes

72IFA’2004

Optimal Packet Size for Wireless Optimal Packet Size for Wireless Sensor NetworksSensor Networks

Y. Sankarasubramaniam, I. F. Akyildiz, S. McLaughlin, Y. Sankarasubramaniam, I. F. Akyildiz, S. McLaughlin, ”Optimal ”Optimal Packet Size Packet Size

for Wireless Sensor Networks”, IEEE SNPA, May 2003.for Wireless Sensor Networks”, IEEE SNPA, May 2003.

Determining the optimal packet size for sensor networks is necessary to Determining the optimal packet size for sensor networks is necessary to operate at high operate at high energy efficienciesenergy efficiencies..

The The multihop wireless channelmultihop wireless channel and and energy consumption characteristicsenergy consumption characteristics are the two most are the two most important factors that influence choice of packet size. important factors that influence choice of packet size.

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

73IFA’2004

PHYSICAL LAYERPHYSICAL LAYER

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

Explore Antennae Techniques Explore Antennae Techniques

(e.g., Smart Antennaes)(e.g., Smart Antennaes)

Software Radios??Software Radios??

New Modulation SchemesNew Modulation Schemes

SYNCH SchemesSYNCH Schemes

FEC Schemes on the Bit LevelFEC Schemes on the Bit Level

New Data EncryptionNew Data Encryption

Investigate UWB Investigate UWB

74IFA’2004

FINAL REMARKSFINAL REMARKS

75IFA’2004

Basic Research Basic Research NeedsNeeds

• An Analytical Framework for Sensor Networks Find a Basic Generic Architecture and Protocol Development which can be tailored to specific applications. • More theoretical investigations of the Architecture and Protocol developments

• Network Configuration and Planning Schemes

76IFA’2004

FURTHER OPEN RESEARCH FURTHER OPEN RESEARCH ISSUESISSUES

Research to Research to integrate WSN domain into NGWI integrate WSN domain into NGWI (Next Generation Wireless Internet)(Next Generation Wireless Internet)

e.g., interactions of Sensor and AdHoc e.g., interactions of Sensor and AdHoc Networks or Sensor and Satellite or any other Networks or Sensor and Satellite or any other combinations…combinations…

Explore the SENSOR/ACTOR NETWORKSExplore the SENSOR/ACTOR NETWORKS

Explore the SENSOR-ANTISENSOR NETWORKSExplore the SENSOR-ANTISENSOR NETWORKS

SECURITY ISSUESSECURITY ISSUES

77IFA’2004

Some ApplicationsSome Applications

• Clear Demonstration of Testbeds and Realistic Applications

• Not only data or audio but also video as well as integrated traffic.

SOME OF OUR EFFORTS IN BWN LAB @ GaTech

• MAN for Meteorological Observations• SpINet for Mars Surface• Airport Security Sensors/Actors• Sensor Wars• Wide Area Multi-campus Sensor Network

78IFA’2004

FURTHER CHALLENGESFURTHER CHALLENGESProtocol StackProtocol Stack

• Follow the TCP/IP Stack, i.e., keep the Strict Layer Approach ??? • Or Interleave the Layer functionalities???

• Cross Layer Optimization

• Standardization???

79IFA’2004

Commercial Commercial Viability of WSN Viability of WSN ApplicationsApplications

Within the next few years, distributed sensing and Within the next few years, distributed sensing and computing will be everywhere, i.e., homes, offices, computing will be everywhere, i.e., homes, offices, factories, automobiles, shopping centers, super-factories, automobiles, shopping centers, super-markets, farms, forests, rivers and lakes. markets, farms, forests, rivers and lakes.

Some of the immediate commercial applications of Some of the immediate commercial applications of wireless sensor networks are wireless sensor networks are – Industrial automation (Industrial automation (process controlprocess control))– Defense (Defense (unattended sensors, real-time unattended sensors, real-time

monitoringmonitoring))– Utilities (Utilities (automated meter readingautomated meter reading), ), – Weather predictionWeather prediction– Security (Security (environment, building etc.environment, building etc.))– Building automation (Building automation (HVAC controllersHVAC controllers). ). – Disaster relief operationsDisaster relief operations– Medical and health monitoring and instrumentationMedical and health monitoring and instrumentation

80IFA’2004


XSILOGY SolutionsXSILOGY Solutions is a company which provides wireless sensor is a company which provides wireless sensor network solutions for various commercial applications such as tank network solutions for various commercial applications such as tank inventory management, stream distribution systems, commercial inventory management, stream distribution systems, commercial buildings, environmental monitoring, homeland defense etc. buildings, environmental monitoring, homeland defense etc. http://www.xsilogy.com/home/main/index.htmlhttp://www.xsilogy.com/home/main/index.html

In-Q-TelIn-Q-Tel provides distributed data collection solutions with sensor provides distributed data collection solutions with sensor network deployment. network deployment. http://www.in-q-tel.com/tech/dd.htmlhttp://www.in-q-tel.com/tech/dd.html

ENSCO Inc.ENSCO Inc. invests in wireless sensor networks for meteorological invests in wireless sensor networks for meteorological applications. applications. http://www.ensco.com/products/homeland/msis/msis_rnd.htmhttp://www.ensco.com/products/homeland/msis/msis_rnd.htm

EMBEREMBER provides wireless sensor network solutions for industrial provides wireless sensor network solutions for industrial automation, defense, and building automation. automation, defense, and building automation. http://www.ember.comhttp://www.ember.com

81IFA’2004


H900 Wireless SensorNet System(TM)H900 Wireless SensorNet System(TM), the first commercially , the first commercially available end-to-end, low-power, bi-directional, wireless mesh available end-to-end, low-power, bi-directional, wireless mesh networking system for commercial sensors and controls is networking system for commercial sensors and controls is developed by the company called developed by the company called Sensicast SystemsSensicast Systems. The . The company targets wide range of commercial applications from company targets wide range of commercial applications from energy to homeland security. energy to homeland security. http://www.sensicast.comhttp://www.sensicast.com

The Sensor-based Perimeter SecurityThe Sensor-based Perimeter Security product is introduced by a product is introduced by a company called company called SOFLINX Corp.SOFLINX Corp. (a wireless sensor network (a wireless sensor network software company) software company) http://www.soflinx.comhttp://www.soflinx.com

XYZ On A Chip: Integrated Wireless Sensor Networks for the XYZ On A Chip: Integrated Wireless Sensor Networks for the Control of the Indoor Environment In BuildingsControl of the Indoor Environment In Buildings is another is another commercial application project currently performed by Berkeley. commercial application project currently performed by Berkeley. http://www.cbe.berkeley.edu/research/briefs-wirelessxyz.htmhttp://www.cbe.berkeley.edu/research/briefs-wirelessxyz.htm

82IFA’2004


The CrossbowThe Crossbow wireless sensor products and its environmental wireless sensor products and its environmental monitoring and other related industrial applications of such as monitoring and other related industrial applications of such as surveillance, bridges, structures, air quality/food quality, surveillance, bridges, structures, air quality/food quality, industrial automation, process control are introduced. industrial automation, process control are introduced. http://www.xbow.comhttp://www.xbow.com

Japan's Omron CorpJapan's Omron Corp has two wireless sensor projects in the US has two wireless sensor projects in the US that it hopes to commercialize in the near future. that it hopes to commercialize in the near future. Omron's Omron's Hagoromo Wireless Web Sensor projectHagoromo Wireless Web Sensor project consists of wireless consists of wireless nodes equipped with various sensing abilities for providing nodes equipped with various sensing abilities for providing security for major cargo-shipping ports around the world. security for major cargo-shipping ports around the world. http://www.omron.comhttp://www.omron.com

Possible business opportunity with a big home improvement Possible business opportunity with a big home improvement store chain, Home Depot, with Intel and Berkeley using wireless store chain, Home Depot, with Intel and Berkeley using wireless sensor networkssensor networkshttp://www.svbizink.com/otherfeatures/spotlight.asp?iid=314http://www.svbizink.com/otherfeatures/spotlight.asp?iid=314

83IFA’2004


Millennial NetMillennial Net builds wireless networks combining sensor builds wireless networks combining sensor interface endpoints and routers with gateways for industrial interface endpoints and routers with gateways for industrial and building automation, security, and telemetryand building automation, security, and telemetryhttp://www.millennial.nethttp://www.millennial.net

CSEMCSEM provides sensing and actuation solutions provides sensing and actuation solutions http://www.csem.ch/fs/acuating.htmhttp://www.csem.ch/fs/acuating.htm

Dust Inc.Dust Inc. develops the next-generation hardware and software develops the next-generation hardware and software for wireless sensor networks for wireless sensor networks http://www.dust-inc.comhttp://www.dust-inc.com

Integration AssociatesIntegration Associates designs sensors used in medical, designs sensors used in medical, automotive, industrial, and military applications to cost-automotive, industrial, and military applications to cost-effective designs for handheld consumer appliances, barcode effective designs for handheld consumer appliances, barcode readers, and wireless computer input devices readers, and wireless computer input devices http://www.integration.comhttp://www.integration.com

84IFA’2004


MelexisMelexis produces advanced integrated semiconductors, produces advanced integrated semiconductors, sensor ICs, and programmable sensor IC systems. sensor ICs, and programmable sensor IC systems. http://www.melexis.comhttp://www.melexis.com

ZMDZMD designs, manufactures and markets high performance, designs, manufactures and markets high performance, low power mixed signal ASIC and ASSP solutions for low power mixed signal ASIC and ASSP solutions for wireless and sensor integrated circuits.wireless and sensor integrated circuits.http://www.zmd.bizhttp://www.zmd.biz

ChipconChipcon produces low-cost and low-power single-chip 2.4 produces low-cost and low-power single-chip 2.4 GHz ISM band transceiver design for sensors. GHz ISM band transceiver design for sensors. http://www.chipcon.comhttp://www.chipcon.com

ZigBee AllianceZigBee Alliance develops a standard for wireless low-power, develops a standard for wireless low-power, low-rate devices. low-rate devices. http://www.zigbee.comhttp://www.zigbee.com

85IFA’2004

InterPlanetary Internet InterPlanetary Internet ((Deep Space Network)Deep Space Network)::State-of-the-Art and Research State-of-the-Art and Research Challenges*Challenges*

* * I.F. Akyildiz, O. Akan, C.Chen, J. Fang, W. Su, “InterPlanetary Internet: State-of-the-Art and Research Challenges”, Computer Networks Journal, Oct. 2003.

86IFA’2004

InterPlaNetary Internet InterPlaNetary Internet Architecture Architecture

InterPlaNetary Backbone NetworkInterPlaNetary Backbone Network InterPlaNetary External NetworkInterPlaNetary External Network PlaNetary NetworkPlaNetary Network

87IFA’2004

PlaNetary Network PlaNetary Network ArchitectureArchitecture

PlaNetary Satellite NetworkPlaNetary Satellite Network PlaNetary Surface NetworkPlaNetary Surface Network

88IFA’2004

CHALLENGESCHALLENGES

– Extremely long and variable propagation delaysExtremely long and variable propagation delays– Asymmetrical forward and reverse link Asymmetrical forward and reverse link

capacitiescapacities– Extremely high link error rates Extremely high link error rates – Intermittent link connectivity, e.g., BlackoutsIntermittent link connectivity, e.g., Blackouts– Lack of fixed communication infrastructureLack of fixed communication infrastructure– Effects of planetary distances on the signal Effects of planetary distances on the signal

strength and the protocol designstrength and the protocol design– Power, mass, size, and cost constraints for Power, mass, size, and cost constraints for

communication hardware and protocol designcommunication hardware and protocol design– Backward compatibility requirement due to Backward compatibility requirement due to

high cost involved in deployment and launching high cost involved in deployment and launching processesprocesses

89IFA’2004

Planned InterPlaNetary Planned InterPlaNetary Internet MissionsInternet Missions

Mission NameMission Name ScheduleSchedule Description/ObjectiveDescription/ObjectiveGalaxy Evolution Galaxy Evolution ExplorerExplorer

20032003 To measure star formation 11 billion years ago with UV wavelengths.To measure star formation 11 billion years ago with UV wavelengths.

RosettaRosetta February 2004February 2004 Comet orbiter and lander to gather scientific data.Comet orbiter and lander to gather scientific data.

MessengerMessenger March 2004March 2004 To study the characteristics of Mercury, and to search for water ice To study the characteristics of Mercury, and to search for water ice and other frozen volatiles.and other frozen volatiles.

Deep ImpactDeep Impact December December 20042004

To investigate the interior of the comet, the crater formation process, To investigate the interior of the comet, the crater formation process, the resulting crater, and any outgassing from the nucleus.the resulting crater, and any outgassing from the nucleus.

Mars Reconnaissance Mars Reconnaissance OrbiterOrbiter

July 2005July 2005 To study Mars from orbit, perform high-resolution measurements and To study Mars from orbit, perform high-resolution measurements and serve as communications relay for later Mars landers until 2010.serve as communications relay for later Mars landers until 2010.

Venus ExpressVenus Express November November 20052005

To study the atmosphere and plasma environment of Venus.To study the atmosphere and plasma environment of Venus.

New HorizonsNew Horizons January 2006January 2006 To fly by Pluto and its moon Charon and return scientific data/images.To fly by Pluto and its moon Charon and return scientific data/images.

DawnDawn May 2006May 2006 To study two of the largest asteroids, Ceres and Vesta.To study two of the largest asteroids, Ceres and Vesta.

KeplerKepler October 2006October 2006 Search for terrestrial planets, i.e., similar to Earth.Search for terrestrial planets, i.e., similar to Earth.

Europa OrbiterEuropa Orbiter 20082008 To study the Jupiter’s Moon Europa’s icy surface.To study the Jupiter’s Moon Europa’s icy surface.

LISALISA 20072007 To probe the gravity waves emitted by dwarf stars and other objects To probe the gravity waves emitted by dwarf stars and other objects sucked into black holes.sucked into black holes.

Mars 2007Mars 2007 Late 2007Late 2007 To launch a remote sensing orbiter and four small To launch a remote sensing orbiter and four small Netlanders Netlanders to Mars. to Mars.

Mars 2009Mars 2009 Late 2009Late 2009 Smart Lander, Long Range Rover and Communication Satellite.Smart Lander, Long Range Rover and Communication Satellite.

BepiColomboBepiColombo January 2011January 2011 To study Mercury’s form, interior structure, geology, composition, etc.To study Mercury’s form, interior structure, geology, composition, etc.

90IFA’2004

Proposed Consultative Committee Proposed Consultative Committee for Space Data Systems (CCSDS) for Space Data Systems (CCSDS) Protocol StackProtocol Stack

for Mars Exploration Mission Communications

91IFA’2004

Proposed Delay Tolerant Proposed Delay Tolerant Networking (DTN) Protocol Networking (DTN) Protocol StackStack

92IFA’2004

Transport Layer Transport Layer IssuesIssues

– Extremely High Propagation DelaysExtremely High Propagation Delays– High Link Error RatesHigh Link Error Rates– Asymmetrical BandwidthAsymmetrical Bandwidth– BlackoutsBlackouts

93IFA’2004

Extremely Long Propagation Extremely Long Propagation DelaysDelays

PlanetPlanet RTTRTTmin min RTTRTTmax max

MercuryMercury 1.11.1 30.230.2

VenusVenus 5.65.6 35.835.8

MarsMars 99 5555

JupiterJupiter 81.681.6 133.3133.3

SaturnSaturn 165.3165.3 228.4228.4

UranusUranus 356.9356.9 435.6435.6

NeptuneNeptune 594.9594.9 646.7646.7

PlutoPluto 593.3593.3 1044.41044.4

94IFA’2004

Window-BasedWindow-Based TCP’s are not suitable!!! TCP’s are not suitable!!!ForFor RTT = 40 min RTT = 40 min 20B/s 20B/s throughput onthroughput on 1Mb/s 1Mb/s link !!link !!

Performance of Existing TCP Performance of Existing TCP ProtocolsProtocols

O. B. Akan, J. Fang, I. F. Akyildiz, “Performance of TCP Protocols in O. B. Akan, J. Fang, I. F. Akyildiz, “Performance of TCP Protocols in Deep Space Communication Networks”, Deep Space Communication Networks”,

IEEE Communications LettersIEEE Communications Letters, Vol. 6, No. 11, pp. 478-480, , Vol. 6, No. 11, pp. 478-480, November 2002.November 2002.

95IFA’2004

Space Communications Protocol Space Communications Protocol StandardsStandards – – Transport Protocol (SCPS-Transport Protocol (SCPS-TP)TP)

Addresses link errors, asymmetry, and outagesAddresses link errors, asymmetry, and outages SCPS-TP: Combination of existing TCP protocols:SCPS-TP: Combination of existing TCP protocols:

– Window-basedWindow-based– Slow StartSlow Start– Retransmission timeoutRetransmission timeout– TCP-Vegas congestion control schemeTCP-Vegas congestion control scheme – variation – variation

of the RTT value as an indication of congestionof the RTT value as an indication of congestion SCPS-TP Rate-Based:SCPS-TP Rate-Based:

– Does not perform congestion control Does not perform congestion control – Uses fixed transmission rateUses fixed transmission rate

* Space Communications Protocol Specification-Transport Protocol (SCPS-TP)", Recommendation * Space Communications Protocol Specification-Transport Protocol (SCPS-TP)", Recommendation for Space Data Systems Standards, CCSDS 714.0-B-1, May 1999.for Space Data Systems Standards, CCSDS 714.0-B-1, May 1999.

New Transport Protocols are New Transport Protocols are needed !!!needed !!!

96IFA’2004

TP-PlanetTP-Planet*O. B. Akan, J. Fang and I.F. Akyildiz, “TP-Planet: A Reliable *O. B. Akan, J. Fang and I.F. Akyildiz, “TP-Planet: A Reliable Transport Protocol for InterPlaNetary Internet”, Transport Protocol for InterPlaNetary Internet”, to appear in to appear in IEEE Journal of Selected Areas in Communications (JSAC),IEEE Journal of Selected Areas in Communications (JSAC), early early 2004.2004.

Objective:Objective: To address challenges of InterPlaNetary InternetTo address challenges of InterPlaNetary Internet A New A New Initial StateInitial State Algorithm Algorithm A New Congestion Detection Algorithm in A New Congestion Detection Algorithm in Steady StateSteady State A NewA New Rate-BasedRate-Based scheme instead of W scheme instead of Window-Basedindow-Based

Steady State

FollowUPImmediate Immediate

StartStart

Initial State HoldHold

BlackoutBlackout

DecreaseDecrease IncreaseIncrease

Follow UpFollow Up

t=RTT

t=2*RTT

97IFA’2004

Multimedia Transport Multimedia Transport in InterPlaNetary in InterPlaNetary Internet Internet

Additional ChallengesAdditional Challenges

* Bounded Jitter* Bounded Jitter

* Minimum Bandwidth* Minimum Bandwidth

* Smoothness* Smoothness

* Error Control* Error Control

98IFA’2004

RCP-Planet: OverviewRCP-Planet: OverviewJ. Fang and I.F. Akyildiz, “RCP Planet: A Rate Control J. Fang and I.F. Akyildiz, “RCP Planet: A Rate Control Scheme Scheme for Multimedia Traffic in InterPlaNetary Internet”, July for Multimedia Traffic in InterPlaNetary Internet”, July 2003.2003.

BEGIN State

t=RTT

IncreaIncreasese

DecreasDecreasee

BlackoutBlackout

OPERATIONAL State

Objective:Objective: To Address the ChallengesTo Address the Challenges Framework:Framework:

* * A New Packet Level FECA New Packet Level FEC

* A New Rate-Based* A New Rate-Based Approach Approach

* A New * A New BEGIN StateBEGIN State Algorithm Algorithm

* A New Rate Control Algorithm in * A New Rate Control Algorithm in OPERATIONAL StateOPERATIONAL State

99IFA’2004

Transport LayerTransport LayerOpen Research Open Research IssuesIssues

End-to-End Transport:End-to-End Transport:– Feasibility of the end-to-end transport should be Feasibility of the end-to-end transport should be

investigated and new end-to-end transport protocols investigated and new end-to-end transport protocols should be devised accordingly.should be devised accordingly.

Extreme PlaNetary Distances:Extreme PlaNetary Distances:– Deep Space links with extreme delays such as Deep Space links with extreme delays such as

Jupiter, Pluto have intermittent connectivity even Jupiter, Pluto have intermittent connectivity even within an RTT. within an RTT.

Cross-layer Optimization:Cross-layer Optimization:– The interactions between the transport layer and The interactions between the transport layer and

lower/higher layers should be maximized to increase lower/higher layers should be maximized to increase network efficiency for scarce space link resources. network efficiency for scarce space link resources.

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Network Layer Network Layer IssuesIssues

Naming and AddressingNaming and Addressing in the in the InterPlaNetary InternetInterPlaNetary Internet

Routing Routing in the in the InterPlaNetary InterPlaNetary Backbone NetworkBackbone Network

RoutingRouting in in PlaNetary PlaNetary Networks Networks

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Purpose: Purpose: To provide inter-operability To provide inter-operability between different elements in the architecturebetween different elements in the architecture

Influencing Factors:Influencing Factors:– What objects are named?What objects are named? (Typically nodes or data objects)(Typically nodes or data objects)– Whether a name can be directly used by Whether a name can be directly used by

a data router in order to determine the a data router in order to determine the delivery path?delivery path?

– The method by which name/object The method by which name/object binding is managed?binding is managed?

Naming and Naming and Addressing Addressing

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Domain Name System Domain Name System (DNS) Approach in (DNS) Approach in InternetInternet

If an application on a remote planet needs If an application on a remote planet needs to resolve an Earth based name to an to resolve an Earth based name to an address:address:

Problems: Problems: – If query an Earth-resident name serverIf query an Earth-resident name server:: A significant delay of a round-trip time in A significant delay of a round-trip time in

the commencement of communicationthe commencement of communication– If maintain a secondary name server If maintain a secondary name server

locallylocally:: State updates would dominate State updates would dominate communication channel utilizationcommunication channel utilization

– If maintain a static list of host names and If maintain a static list of host names and addressesaddresses::

Not scale well with system’s growthNot scale well with system’s growth

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Tiered Naming and Tiered Naming and AddressingAddressing

Name TupleName Tuple = {region ID, entity ID} = {region ID, entity ID}– Region IDRegion ID identifies the entity’s region and is known identifies the entity’s region and is known

by all regions in the InterPlaNetary Internetby all regions in the InterPlaNetary Internet– Entity IDEntity ID is a name local to its entity’s local region is a name local to its entity’s local region

and treated as opaque data outside this regionand treated as opaque data outside this region

The opacity of entity names outside their local The opacity of entity names outside their local region region

enforces enforces Late Binding:Late Binding: the entity ID of a tuple is not the entity ID of a tuple is not interpreted outside its local region interpreted outside its local region

which avoids a universal name-to-address binding which avoids a universal name-to-address binding space and preserves a significant amount of space and preserves a significant amount of autonomy within each region.autonomy within each region.

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An InterPlaNetary Internet: An InterPlaNetary Internet: Example and Host Name TuplesExample and Host Name Tuples

Earth’s Internet

IPN region: earth.sol

The “Backbone”

IPN region: ipn.sol

Mars’ Internet

IPN region: mars.sol

SRC GW1 GW2 DST

HosHostt

IPN IPN regionsregions

Host name tuplesHost name tuples

SRCSRC earth.solearth.sol {earth.sol, src.jpl.nasa.gov:6769}{earth.sol, src.jpl.nasa.gov:6769}

GW1GW1 earth.solearth.sol

ipn.solipn.sol

{earth.sol, ipngw1.jpl.nasa.gov:6769}{earth.sol, ipngw1.jpl.nasa.gov:6769}

{ipn.sol, ipngw1.jpl.nasa.gov:6769}{ipn.sol, ipngw1.jpl.nasa.gov:6769}

GW2GW2 ipn.solipn.sol

mars.solmars.sol

{ipn.sol, ipngw2.jpl.nasa.gov:6769}{ipn.sol, ipngw2.jpl.nasa.gov:6769}

{mars.sol, ipngw2.jpl.nasa.gov:6769}{mars.sol, ipngw2.jpl.nasa.gov:6769}

DSTDST mars.solmars.sol {mars.sol, dst.jpl.nasa.gov:6769}{mars.sol, dst.jpl.nasa.gov:6769}

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ChallengesChallengesNetwork LayerNetwork Layer

Long and Variable DelaysLong and Variable Delays– Without timely distribution of topology information, Without timely distribution of topology information,

routing computations fail to converge to a common routing computations fail to converge to a common solution, resulting in route inconsistency or solution, resulting in route inconsistency or oscillationoscillation

– The node movement adds to the variability of delaysThe node movement adds to the variability of delays Intermittent ConnectivityIntermittent Connectivity

– Determine the predicted time and duration of Determine the predicted time and duration of intermittent links and the degree of uncertainityintermittent links and the degree of uncertainity

– Obtain knowledge of the state of pending messagesObtain knowledge of the state of pending messages– Schedule transmission of the pending messages Schedule transmission of the pending messages

when links become availablewhen links become available

SCPS-NP SCPS-NP possible solution??? possible solution???

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Open Research Open Research IssuesIssuesNetwork LayerNetwork Layer

Distribution of Topology InformationDistribution of Topology Information– Combination of Combination of link statelink state and and distance vector distance vector

informationinformation exchange exchange– Distribution of trajectory and velocity informationDistribution of trajectory and velocity information

Path CalculationPath Calculation– Hop-by-hop routing is expected using incomplete Hop-by-hop routing is expected using incomplete

topology information and probabilistic estimationtopology information and probabilistic estimation– Adaptive algorithms are needed for rerouting and Adaptive algorithms are needed for rerouting and

caching decisionscaching decisions

Interaction with Transport Layer ProtocolsInteraction with Transport Layer Protocols

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ChallengesChallengesNetwork Layer Network Layer (Planet)(Planet)

Extreme Power ConstraintsExtreme Power Constraints– Space elements mainly depend on rechargeable Space elements mainly depend on rechargeable

battery using solar energybattery using solar energy Frequent Network PartitioningFrequent Network Partitioning

– The network can be partitioned due to harsh The network can be partitioned due to harsh environmental factorsenvironmental factors

Adaptive Routing through Heterogeneous NetworksAdaptive Routing through Heterogeneous Networks– Fixed elements (e.g., landers)Fixed elements (e.g., landers)– Satellites with scheduled movement Satellites with scheduled movement – Mobile elements with slow movement (e.g., Mobile elements with slow movement (e.g.,

rovers)rovers)– Mobile elements with fast movement (e.g., Mobile elements with fast movement (e.g.,

spacecraft)spacecraft)– Low-power sensor nodes in clustersLow-power sensor nodes in clusters

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Medium Access Medium Access Control Control InterPlaNetary Backbone NetworkInterPlaNetary Backbone Network

Challenges:Challenges:– Very Long Propagation Very Long Propagation

DelaysDelays– Physical Design Change Physical Design Change

ConstraintsConstraints– Topological ChangesTopological Changes– Power ConstraintsPower Constraints

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Medium Access Medium Access Control Control InterPlaNetary Backbone NetworkInterPlaNetary Backbone Network

Vastly unexplored research fieldVastly unexplored research field The suitability and performance The suitability and performance

evaluation of fundamental MAC evaluation of fundamental MAC schemes, i.e., schemes, i.e., TDMATDMA, , CDMACDMA, and , and FDMAFDMA, should be investigated, should be investigated

Thus far, Thus far, Packet TelecommandPacket Telecommand, and , and Packet TelemetryPacket Telemetry standards standards developed by CCSDS are used to developed by CCSDS are used to address deep space link layer issuesaddress deep space link layer issues

(Virtual Channelization method!!!)(Virtual Channelization method!!!)

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Error ControlError ControlInterPlaNetary Backbone NetworkInterPlaNetary Backbone Network

Deep space channel is generally Deep space channel is generally modelled as Additive White Gaussian modelled as Additive White Gaussian Noise (AWGN) channelNoise (AWGN) channel

Scientific space missions require bit-Scientific space missions require bit-error rate of 10error rate of 10-5-5 or better after physical or better after physical link layer coding link layer coding

Error control at link layer is necessary Error control at link layer is necessary

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CCSDS Telemetry Standard: (Telemetry Channel CCSDS Telemetry Standard: (Telemetry Channel Coding):Coding):– For Gaussian Channels For Gaussian Channels

½ Rate Convolutional Code½ Rate Convolutional Code– For Bandwidth-Constrained Channels For Bandwidth-Constrained Channels

Punctured Convolutional CodesPunctured Convolutional Codes– For Further Constrained Channels For Further Constrained Channels Concatenated CodesConcatenated Codes (i.e.,Convolutional code as (i.e.,Convolutional code as

the inner code and the RS code as the outer the inner code and the RS code as the outer code)code)

Own Experience Own Experience TORNADO CODES!!! TORNADO CODES!!!

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Advance Orbiting Systems Rec. by Advance Orbiting Systems Rec. by CCSDS CCSDS

Space Link (ARQ) Protocol (SLAP)Space Link (ARQ) Protocol (SLAP)

Packet Telecommand Standard of CCSDS Packet Telecommand Standard of CCSDS

Command Operation Procedure (COP) Command Operation Procedure (COP) (GoBack N)(GoBack N)

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Open Research IssuesOpen Research IssuesLink LayerLink Layer

MAC for InterPlaNetary Backbone MAC for InterPlaNetary Backbone NetworkNetwork

MAC for PlaNetary NetworksMAC for PlaNetary Networks Error Coding SchemesError Coding Schemes Cross-layer OptimizationCross-layer Optimization Optimum Packet SizesOptimum Packet Sizes

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Physical Layer Issues Physical Layer Issues InterPlaNetary Backbone NetworkInterPlaNetary Backbone Network

Possible approach is to increase radiated RF signal energy:Possible approach is to increase radiated RF signal energy:– Use of high power amplifiers such as travelling wave Use of high power amplifiers such as travelling wave

tubes (TWT) or klystrons which can produce output tubes (TWT) or klystrons which can produce output powers up to several thousand wattspowers up to several thousand watts

– This comes with an expense of increased antenna size, This comes with an expense of increased antenna size, cost and also power problems at remote nodescost and also power problems at remote nodes

Current NASA DSN has several 70m antennas for deep space Current NASA DSN has several 70m antennas for deep space missions missions

DSN operates in S-Band and X-Band (2GHz and 8GHz, DSN operates in S-Band and X-Band (2GHz and 8GHz, respectively) for spacecraft telemetry, tracking and respectively) for spacecraft telemetry, tracking and commandcommand– Not adequate to reach high data rates aimed for Not adequate to reach high data rates aimed for

InterPlaNetary Internet InterPlaNetary Internet New 34m antennas are being developed to operate in Ka-New 34m antennas are being developed to operate in Ka-

Band (32 GHz) which will significantly improve data ratesBand (32 GHz) which will significantly improve data rates

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Open Research IssuesOpen Research IssuesPHYSICAL LAYERPHYSICAL LAYER

Signal Power Loss:Signal Power Loss:– Powerful and size-, mass-, and cost-efficient antennas and power Powerful and size-, mass-, and cost-efficient antennas and power

amplifiers need to be developed amplifiers need to be developed Channel Coding:Channel Coding:

– Efficient and powerful channel coding schemes should be investigated Efficient and powerful channel coding schemes should be investigated to achieve reliable and very high rate bit delivery over the long delay to achieve reliable and very high rate bit delivery over the long delay InterPlaNetary Backbone links InterPlaNetary Backbone links

Optical Communications:Optical Communications:– Optical communication technologies should be investigated for Optical communication technologies should be investigated for

possible deployment in InterPlaNetary Backbone linkspossible deployment in InterPlaNetary Backbone links Hardware Design:Hardware Design:

– Low-power low-cost transceiver and antennas should be developed Low-power low-cost transceiver and antennas should be developed Modulation Schemes:Modulation Schemes:

– Simple and low-power modulation schemes should be developed for Simple and low-power modulation schemes should be developed for PlaNetary Surface Network nodes. Ultra-wide Band (UWB) could be PlaNetary Surface Network nodes. Ultra-wide Band (UWB) could be explored for this purposeexplored for this purpose

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Challenges in Deep Space Challenges in Deep Space Time SynchronizationTime Synchronization

Variable and long transmission delaysVariable and long transmission delays– The long and variable delays may cause a The long and variable delays may cause a

fluctuating offset to the clockfluctuating offset to the clock

Variable transmission speedVariable transmission speed– It may produce a fluctuating offset problemIt may produce a fluctuating offset problem

Variable temperatureVariable temperature– It may cause the clock to drift in different rateIt may cause the clock to drift in different rate

Variable electromagnetic interferenceVariable electromagnetic interference– This may cause the clock to drift or even This may cause the clock to drift or even

permanent damage to the crystal if the permanent damage to the crystal if the equipment is not properly shieldedequipment is not properly shielded

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Challenges in Deep Space Challenges in Deep Space Time Synchronization Time Synchronization (cont’d)(cont’d)

Intermittent connectivityIntermittent connectivity– The situation may cause the clock offset to The situation may cause the clock offset to

fluctuate and jumpfluctuate and jump

Impractical transmissionsImpractical transmissions– A time synchronization protocol can not depend A time synchronization protocol can not depend

on message retransmissions to synchronize the on message retransmissions to synchronize the clocks, because the distance between deep clocks, because the distance between deep space equipments are simply too largespace equipments are simply too large

Distributed time serversDistributed time servers– Deep space equipments may require to Deep space equipments may require to

synchronize to their local time servers, and the synchronize to their local time servers, and the time servers have to synchronize among time servers have to synchronize among themselvesthemselves

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Related WorkRelated Work

Network Time ProtocolNetwork Time Protocol– Can not handle mobile servers and clients (variable Can not handle mobile servers and clients (variable

range and range rate with intermittent connectivity)range and range rate with intermittent connectivity)– Has time offset wiggles of few milliseconds of Has time offset wiggles of few milliseconds of

amplitudeamplitude

DSN Frequency and Time SubsystemsDSN Frequency and Time Subsystems– Uses several atomic frequency standards to Uses several atomic frequency standards to

synchronize the devices and provide references for synchronize the devices and provide references for the three DSN sites, i.e., Goldstone, USA; Madrid, the three DSN sites, i.e., Goldstone, USA; Madrid, Spain; Canberra, AustraliaSpain; Canberra, Australia

Recommendation for proximity-1 space link protocolRecommendation for proximity-1 space link protocol– Finds the correlation between the clocks of proximity Finds the correlation between the clocks of proximity

nodes. The correlation data and UTC time are used nodes. The correlation data and UTC time are used to correct the past and project the future UTC valuesto correct the past and project the future UTC values

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ConclusionsConclusions

InterPlaNetary Internet will be the Internet of next InterPlaNetary Internet will be the Internet of next generation deep space networks. generation deep space networks.

There exist many significant challenges for the realization There exist many significant challenges for the realization of InterPlaNetary Internet. of InterPlaNetary Internet.

Many researchers are currently engaged in developing the Many researchers are currently engaged in developing the required technologies for this objective. required technologies for this objective.

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FiNAL WORDSFiNAL WORDSNASA’s VISION:NASA’s VISION: to improve life here, to extend life to there, to find to improve life here, to extend life to there, to find life beyond..life beyond... .

NASA’s MISSION:NASA’s MISSION: to understand and protect our home planet, to explore to understand and protect our home planet, to explore the Universe and search for life, to inspire the Universe and search for life, to inspire the next generation of explorerthe next generation of explorers…s…

OUR AIM:OUR AIM: to point out the research problems and inspire the to point out the research problems and inspire the researchers worldwide to realize these objectiveresearchers worldwide to realize these objectives!!!!!!!!!s!!!!!!!!!

future networking paradigms (sensor networks and interplanetary internet) ian f. akyildiz broadband...

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