wireless sensor networks review professor jack stankovic university of virginia

Wireless Sensor Networks

Review

Professor Jack Stankovic

University of Virginia

Review OutlineReview Outline

• Architecture – Where all this fits

• Clock Sync• Power Management• Database View of WSN• Programming Abstractions• Security and Privacy (questions?)

WSN Architecture ExampleWSN Architecture Example

Clock Sync ProtocolsClock Sync Protocols

• NTP (Network Time Protocol) – for Internet

• RBS (Reference Broadcast Sync)• TPSN (Time-sync Protocol for Sensor

Networks)

• FTSP (Flooding Time Sync Protocol)

NTPNTP• Network Time Protocol (NTP) on Internet

– Included in OS code– Simple NTP (SNTP) exists for PCs– Runs as background process– Get time from “best” servers

• Finds those with lowest jitter/latency• Depends on wired and fast connections

– Use statistical analysis of round trip time to clock servers

– Clock servers get time from GPS

NTPNTP

• Not (directly) usable for WSN– Complex – see 50 page document– Continuous cost– Large code size– Expensive in messages/energy

Clock Sync DelaysClock Sync Delays• Uncertainties of radio message

deliveryApplication

Routing

MAC

RADIO

Application

Routing

MAC

RADIO

Send timehighly non-

determ(100ms)

Access time (ms - s)

Transmission time (10ms)

Propagation time (< 1microsec)

Reception time (10ms)

receive timehighly non-

determ(100ms)

RBSRBS

• Reference message is broadcast• Receivers record their local time when message

is received– Timestamps are ONLY on the receiver side– This eliminates access and send times

• Nodes exchange their recorded times with each other

• No transmitter side non-determinism

RBSRBS

5

6

7

Local Time

Send MSGNo Clock

6,7

5,7

5,6

Exchange AdjustPlus 2

Plus 1

OK

Propagation Time = 0

TPSNTPSN

• Creates a spanning tree• Perform pair-wise sync along edges

of the tree• Must be symmetric links

– Recall radio irregularity paper

• Considers “entire” system– RBS looks at one hop

• Exchange two sync messages with parent node

Synchronization PhaseSynchronization Phase

• Delta = clock drift• P = propagation delay

T1

T2 T3

T4

Node A

Node B

P = ((T2-T1)+(T4-T3))/2 Delta = ((T2-T1)-(T4-T3))/2

Node A corrects its clock by DeltaNote: Sender A corrects to clock of receiver B

T2=T1+P+Delta

(T1) (T1,T2,T3)

ExampleExample

T1= 5.0

T2=5.35 T3=6.0

T4=5.75

Node A

Node B

P = ((T2-T1)+(T4-T3))/2 Delta = ((T2-T1)-(T4-T3))/2P= ((5.35-5.0)+(5.75-6))/2 Delta= ((.35)-(-.25))/2P=((.35)+(-.25))/2 Delta= 0.6/2 =.3P= .1/2=.05

5.3

.05 .05

5.7

So A adds .3 to 5.75 to get 6.05Only need Delta to adjust clocks

5.05

Read Clock in MAC Layer Read Clock in MAC Layer • Uncertainties of radio message

deliveryApplication

Routing

MAC

RADIO

Application

Routing

MAC

RADIO

Send timehighly non-

determ(100ms)

Access time (ms - s)

Transmission time (10ms)

Propagation time (< 1microsec)

Reception time (10ms)

receive timehighly non-

determ(100ms)

Flooding Time Sync Protocol (FTSP)

Flooding Time Sync Protocol (FTSP)

• ~1 Microsec accuracy• MAC-layer timestamp• Skew compensation with linear

regression (accounts for drift)• Handles large scale networks

Remove UncertaintiesRemove Uncertainties

• Eliminate Send Uncertainty– Get time in the MAC layer

• Eliminate Access Time– Get time after the message has access

to the channel

• Eliminate Receive Time– Record local time message received at

the MAC layer

RemainingRemaining

• (Mostly) Deterministic Times– Transmit – Propagation– Reception

Basic IdeaBasic Idea• When to time stamp the message

cpu:

radio:

antenna:

cpu:

radio:

antenna:

radio:

Interrupt handling

encoding

propagation

decoding

byte alignment

Interrupt handling

sender

receiver

Mica2 uncertainties:

Interrupt:5us, 30us(<2%)

Encode+decode:110us -112us

Byte align: 0us – 365us

Propagation: 1us

Get timestamp

Set timestamp

Ready

Basic IdeaBasic Idea• When to time stamp the message

– Radio layer, after the second SYN sent out, 6 timestamps in row, take the average and send only 1 timestamp

RADIO

PreamblesSYNSYNDATACRC

T0Ti

Normalize and then take Average of these

timestamps for 6 bytes of data

Why take 6 samples?Why take 6 samples?

• Because of all the uncertainties as described in a previous slide

FTSPFTSP

• Root maintains global time for system

• All others sync to the root• Nodes form an ad hoc structure

rather than a spanning tree

Clock Drift - Basic IdeaClock Drift - Basic Idea

• 8 entry linear regression table to estimate clock skew (each entry derived from 1 clock sync protocol execution)

Example

1 5 us offset2 5 us offset3 7 us offset4 4 us offset5 4 us offset6 5 us offset7 7 us offset8 5 us offset

5 us overSay a 10 secResync period

Compensate .5 usEach sec

10 seconds

1 sec

Multi-HopRoot/Reference Point

Multi-HopRoot/Reference Point

Root/Reference Point

Step 1

Step 28 sync msgsto performLinear regression

How to handlemessages frommultiple nodes

Root Election ProcessRoot Election Process

• If no sync message for time T, declare myself to be root

• May be multiple roots• Smallest ID wins; so roots will give

up their root status when it eventually gets a sync message from another root with lower ID

Power ManagementPower Management

• Hardware layer• MAC layer - review• Routing layer – review• Localization and Clock Sync - review• Overarching power management

schemes– Sentry service– Tripwire service– Duty cycle– Differentiated surveillance

Power Management- Hardware layer

Power Management- Hardware layer

• Turn off/on– CPU – Memory– Sensors– Radio (most expensive)– Fully awake ………… Deep Sleep– Dynamic voltage scaling also possible

• SW ensures a node/components are awake when needed

ArchitectureArchitecture

Sentry-Based Power Management (SBPM)Sentry-Based Power Management (SBPM)

• Two classes of nodes: sentries and non-sentries

– Sentries are awake – Non-sentries can sleep

• Sentries – Provide coarse monitoring & backbone communication network– Sentries “wake up” non-sentries for finer sensing

• Sentry rotation– Even energy distribution– Prolong system lifetime

• Decentralized Algorithm–See photo

1

4

3

2

Tripwire Service – Scaling to 1000s

Tripwire Service – Scaling to 1000s

10-N dormant sections

...

...

...

...

...

...

...

...

……

……

N Tripwire sections

...

...

...

...

...

.........

...

...

...

...

……

……

……

10 relays

Suggest N = 2

100M

1000m

Network partitioning• 2 tripwire sections• 8 dormant sections• 100 motes, 1 relay

per section• Size and number of

sections reconfigurable

• Rotate sections

Sentries• N% in tripwire

section• Rotate sentries

Sensing Coverage = 100%Sensing Coverage = 100%

Basic design with 100% sensing coverage

Basic design with 100% sensing coverage

• Solution – 100% Grid point sensing coverage– Divide whole network into virtual grids– For each grid point x, guarantee that x is covered by at

least one node’s sensing range at ANY time

r

Decide Working ScheduleDecide Working Schedule

• Schedule example

If we want to provide sensing coverage for point x, we can have either A or B or C awake.

B

A

C

Point x

Node A

Node B

Node C

Waking Sleeping

0 10030 70

10 60

5 45

time

Scheduling example for A, B and C


• Challenge: For each node, how to coordinate with other nodes and decide its own schedule?– Solution - Random Reference Point

Scheduling Algorithm


• Concepts– A node’s working schedule is

determined by a four parameter tuple – (T, Ref, Tfront, Tend)


• Solution – Random Reference Point Scheduling Algorithm1) Each node N chooses a “Reference Point (Ref)”

randomly from [0, 100) and broadcasts its Ref and position.e.g. T = 100, RefA = 40, RefB= 90, RefC = 20

2) For each grid point P in its own sensing area, N sorts all the Refs from nodes (including N) which can also sense P in ascending order.For A according to point P1, we have:Ref(1) = RefC = 20, Ref(2) = RefA = 40, Ref(3) = RefB = 90

B

A

C

Point P10 refC refA refB

20 40 90

100


3) Assuming RefN is the (i)th Ref, N’s four parameter tuple is computed as follows:• TfronN = (Ref(i)- Ref(i-1))/2, 1<i<M• TendN = (Ref(i+1)-Ref(i))/2, 1<i<MTfrontA = (Ref(2)-Ref(1))/2 = (40-20)/2 = 10TendA = (Ref(3)-Ref(2))/2 = (90-40)/2 = 25(T, RefA, TfrontA, TendA) = (100, 40, 10, 25)

4) N’s working period for point P (TwN(P)) is decided by:[T*j + RefN – TfrontN , T*j + RefN + TendN), j = 0, 1, 2, …

TwA(P1) = [100*j+40–10, 100*j+40+25) = [100*j+30, 100*j+65)

0

refC refA refBt

t20 40 90

30 65


5) Calculate the union of TwN(Px) for all grid points within N’s sensing area, choose this union as the final working period of N (TwN).

TwA(P1)TwA(P2)TwA(P3)

TwA(Pn)

TwA

.

.

.

0 1005 65

6545

5 50…

B

A

C

Point P1

Enhanced Design with Differentiation

Enhanced Design with Differentiation

• Goal– provide sensing coverage with DOC = a

• a > 1 or a < 1

• Solution– Extend 4-parameter tuple to 5-

parameter tuple (T, Ref, Tfront, Tend, a)– Determine a node’s working period as

follows:• [T*j + Ref – Tfront*a , T*j + Ref + Tend*a)

An ExampleAn Example

Schedule for Grid Point P1 (a=2)

(T, RefA, TfrontA, TendA, a) = (100, 40, 10, 25, 2)

(T, RefB, TfrontB, TendB, a) = (100, 90, 25, 15, 2)

(T, RefC, TfrontC, TendC, a) = (100, 20, 15, 10, 2)

TwA = [T*j + Ref – Tfront*2,T*j + Ref + Tend*2)

= [100*j + 20, 100*j + 90)

TwB = [100*j + 40, 100*j + 120)

TwC = [100*j -10, 100*j + 40)

A

refC refA refB

20 40 90

C

B

0

30 655

Database ViewDatabase View

• Architectures• GHT• TinyDB• SEAD

Architecture (1)Architecture (1)Base StationData Stored hereQueries performed here

Data

Data

Data Data

Architecture (2) Architecture (2)

Base Station

QueriesFlood

Data Stored Decentralized at Each Node

Architecture (3)Architecture (3)

Base Station

Query toRendezvousPoints

Stargates/Log motes

Hierarchical Network

Architecture (4) Architecture (4) DistantWorkStation

Data Stored Decentralized at Each Node Collected by Data Mules

Disconnected System

Geographic Hash Table (GHT)

Geographic Hash Table (GHT)

• Translate from a attribute to a storage location

• Distribute data evenly over the network

• Example: GHT system (A Geographic Hash Table for Data Centric Storage – see Ch 6.6 in text))

GHTGHT

Base Station

QueryStore Tank Info Here

TAG of TinyDBTAG of TinyDB

Base Station

2 Phases (sleep when possible)• disseminate periodic query• collect data (scheduled)

EpochPipelining

SEAD: Scalable Energy Efficient Asynchronous Dissemination Protocol

SEAD: Scalable Energy Efficient Asynchronous Dissemination Protocol

• An asynchronous content distribution multicast tree is maintained

• Tree is modified when– a sink joins– a sink leaves– a sink moves beyond

some threshold

• Cost of building tree is minimized

r1

r4

r3

r2r4

r2

CachingSteinerpoints

Disseminationto Mobile Sinks

Access node

Mobile node

Forwardingchain

Subscription Query (1)Subscription Query (1)

Source

Sink 1 (access node)


4 Phases 4 Phases

• Subscription Query– Mobile node attaches to nearest node

as access point– Access node sends join query to source

• Second -Gate replica search– Attach new node on current tree at best

gate replica

Gate Replica Search (2)Gate Replica Search (2)

Source


GateReplicas(assume they existfor some currenttree – not shown)

Gate Replica Search (2)Gate Replica Search (2)

Information source

Receivers

Attach to mostappropriate gatereplica

• Saves energy

Adjust ReplicaAdjust Replica

• If node moves and access point is no longer appropriate re-adjust tree in the local area, if necessary

• If new access node can attach without increasing cost then no need for additional replica (i.e., no better neighbors exist)

• If new replica is needed then it is chosen based on minimizing overall cost for this area

4 Phases 4 Phases

• Subscription Query– Mobile node attaches to nearest node

as access point– Access node sends join query to source

• Gate replica search– Attach new node on current tree at best

gate replica

• Third - Replica Placement– Locally adjust the tree to a better

dissemination tree

Gate Replica Placement (3)Gate Replica Placement (3)

Source



GateReplica

Replica PlacementReplica Placement

• Branch cost must reflect the amount of energy spent on communication along the branch

• Tree cost = branch cost

r1

r4

r3

r2r4

r2

Branch Cost?

Branch Cost MetricBranch Cost Metric

Geographic Forwarding

Branch Cost = Distance x Packet_Rate

Distance

Cost Minimizing Replica Placement Example


Source



1. Broadcast replica request

2. Collect replica cost bids



Source



Current cost: Sum of branch

lengths weighted by rate



Source





3. If local cost decreased,

choose least cost child



Source







Process Repeated:



Source







Source







Process Repeated:



Source







Source



Can’t reduce cost further.

Replica placement

terminates

Access nodes are NOT

replicas



Source



Minimum cost replica

placement found

New Replica

Programming AbstractionsProgramming Abstractions

• Nine types of approaches– Component – nesC

– Environment– Middleware– VM

personevent

Base Station

vehicleevent

object type: VEHICLE object ID: vehicle01

method:report location to thebase station every 5seconds

attribute: location

object type: PERSON object ID: person01

method:turn on a nearby micro-phone if current locationis less than 1 mile awayfrom the base station

attribute: location

mapping

EnviroSuite

Middleware APIsMiddleware APIs

• Group Management– Create– Terminate– Merge– Join/Leave– Assign function

• Track target• Classify target• Map temperature region

– Consensus

Group Management - APIGroup Management - API

– Create_Group(name,function,criterion,atleast,accuracy) - implicit and explicit

– Destroy_Group(name)– Join()– Leave()– Merge()– Move_COG()– Expand() -- to gain sensing confidence– Shrink() -- to save power– Commit(grp_ID) - to synchronize group re-

configurations

ArchitectureArchitecture

API for Other ServicesAPI for Other Services

• Naming• Directory• Location• Monitor• Configure• …

User Defined Instructions User Defined Instructions

TinyOS

Mate VM(interprets)

24 Instruction Programs

Code capsules InstructionsUnderstood byMate

User defined

1 2 3 4

1 3

3

1

- Sound alarm

- Write to flash

Mate ArchitectureMate Architecture

0 1 2 3

Subroutines

Clo

ck

Sen

d

Receiv

e

Events

gets/sets

0 1 2 3

Subroutines

Clo

ck

Sen

d

Receiv

e

Events

gets/sets

Co

de

OperandStack

ReturnStack

PC

Co

de

OperandStack

ReturnStack

PC

Stack based architecture Operand stack Return address stack

Three events/execution contexts:•Clock timer•Message reception•Message send

Code Example(1)Code Example(1)

• Display Counter to LEDgets # Push heap variable on stackpushc 1 # Push 1 on stackadd # Pop twice, add, push resultcopy # Copy top of stacksets # Pop, set heappushc 7 # Push 0x0007 onto stackand # Take bottom 3 bits of valueputled # Pop, set LEDs to bit patternhalt #

wireless sensor networks review professor jack stankovic university of virginia

Documents

microsecreception time

mspropagation time

uncertaintyget time

okpropagation time

background processget

timerecord local time

t2t1 t4t32 delta

sync messages