1 Some Issues in Ad Hoc Networks Nitin Vaidya University of Illinois at Urbana-Champaign nhv Keynote...

1

Some Issues in Ad Hoc Networks

Nitin VaidyaUniversity of Illinois at Urbana-Champaign

www.crhc.uiuc.edu/~nhv

Keynote talk presented at the International Workshop onTheoretical Aspects of Wireless Ad Hoc, Sensor, and Peer-to-Peer Networks

Illinois Institute of Technology, Chicago, June 11, 2004

© 2004 Nitin Vaidya

2

Outline

Preliminaries

Advertising

Preaching

3

Ad Hoc Networks

Formed by wireless hosts which may be mobile

Without necessarily using a pre-existing infrastructure

•Hybrid architectures using infrastructure likely in many applications

4

Why Ad Hoc Networks ?

Potential ease of deployment

Decreased dependence on infrastructure

5

Many Potential Applications

Personal area networking cell phone, laptop, ear phone, wrist watch

Military environments soldiers, tanks, planes

Civilian environments taxi cab network meeting rooms sports stadiums boats, small aircraft

Emergency operations search-and-rescue policing and fire fighting

6

Challenges(Opportunities)

Broadcast nature of the wireless medium Limited wireless transmission range

– Hidden terminal problem Packet losses due to transmission errors Mobility-induced route changes Mobility-induced packet losses Battery constraints Potentially frequent network partitions Ease of snooping on wireless transmissions

(security hazard)

7

State of the Art

Lot of research activity on:

Routing Medium access control Quality of service

8

State of the Art

More recently …

Capacity of wireless networks << Information theory community

– Pure wireless networks– Hybrid networks– Delay-throughput trade-off

Graph-theoretic problems << Algorithms/theory community– Topology control– Dominating sets– Connectivity problems – Coverage problems in sensor networks

9

State of the Art

Many more (academic) problems … rich area

(Too) Many conferences MobiHoc SenSys MASS SECON …

10

What’s Lacking?

Real applications still lacking (beyond military)

Hard to evaluate protocols in a vacuum

But there is hope … applications on the horizon

Community networks starting to use ad hoc routing Vehicular networks Sensor networks

11

What’s Lacking

Primitives to build distributed applications

Much work on distributed algorithms on fixed and dynamic networks wherein dynamism comes from “random” link failures

But little on ad hoc networks, where the dynamism comes from node mobility and channel variations

Need to revisit distributed computing problems in the new context

12

Outline

Preliminaries

Advertising

Preaching

13

Our Research Themes

Exploiting physical layer capabilities

Protocols for directional antennas Rate adaptation Power control & Power save mechanisms Multi-channel mechanisms

14

Our Research Themes

Distributed algorithms for ad hoc networks

Address assignment Mutual exclusion Leader election Token circulation

15

Our Research Themes

Misbehavior in Wireless Networks

Protocol design for misbehavior detection

16

Some of our past research …

Weak duplicate address detection Misbehavior detection Mutual exclusion

17

Weak Duplicate Address Detection

18

Address Assignment

Dynamic auto-configuration important for autonomous operation of an ad hoc network

Goal:

Assign each node a unique address

OR

Assign each address to at most one node

Can be viewed as distributed mutual exclusion with an address being a resource

19

Auto-Configuration inAd Hoc Networks

Worst case network delays may be unknown, or highly variable, or unbounded

Partitions may occur, and merge

20

Duplicate Address Detectionin Ad Hoc Networks

Several proposals

One example [Perkins]:

Host picks an address randomly Host performs route discovery for the chosen

address If a route reply is received, address duplication is

detected

21

Example: Initially Partitioned Network

D’s packets for address a routed to A

22

Merged Network

Duplicate address detection (DAD) important to avoid misrouting

23

Strong DAD

Detect duplicate addresses within t seconds

Not possible to guarantee strong DAD in presence of unbounded delays May occur due to partitions Even when delays are bounded, bound may be

difficult to calculate

•Unknown network size

24

DAD

Strong DAD impossible with unbounded delay

How to achieve DAD ?

25

Design Principle

If you cannot solve a problem

Change the problem

26

Weak DAD: Requirement

Packets from a given host to a given address

should be routed to the same destination,

despite duplication of the address

27

Example: Initially Partitioned Network

D’s packets for address a routed to A

28

Merged Network:Acceptable Behavior

with Weak DAD

Packets from Dto address astill routed tohost A

29

Merged Network:Unacceptable behavior

Packets from Dto address arouted tohost K insteadof A

30

Weak DAD: Implementation

Integrate duplicate address detection with route maintenance

31

Weak DAD with Link State Routing

Each host has a unique (with high probability) key May include MAC address, serial number, … May be large in size

In all routing-related packets (link state updates) IP addresses tagged by keys (IP, key) pair

32

Weak DAD with Link State Routing

Address duplication not always detected

Duplication detected before misrouting can occur

Weak DAD Reliable, but potentially delayed

33

Link State Routing (LSR): Example

34

Weak DAD with LSR

35

Weak DAD with LSR

Host X with key K_x joins and choose IP_A

(address duplication)

X

36

Weak DAD with LSR

If host D receives a link state update containing (IP_A, K_x), host D detects duplication of address IP_A

Two pairs with identical IP address but distinct keys imply duplication

37

Just-in-Time DAD

Duplication detected before routing tables could be mis-configured

38

Moral of the Story

Traditionally, address assignment and routing are independent algorithms

Duplicate address detection integrated with route maintenance can provide stronger properties

39

Misbehavior Handling

Joint work with Pradeep Kyasanur

40

Problem Definition

Wireless

channel

Wireless

channel

Access Point

A B

Nodes are required to follow Medium Access Control (MAC) rules

Nodes can benefit by misbehaving

A B

41

IEEE 802.11 overview

Distributed Coordination Function (DCF) Widely used for channel access

DCF is a Carrier Sense Multiple Access/ Collision Avoidance (CSMA/CA) protocol

42

CSMA/CA

Don’t transmit when channel is busy

Defer transmission for a random duration on idle channel

43

Backoff Example

Choose backoff value B in range [0,CW] CW is the Contention Window

Count down backoff by 1 every idle slot

wait

Transmit

Transmit

wait

B2=10

B1=20

B2=10

B1=0

S1

S2

CW=31

B1=15

B2=25

44

Possible Misbehavior

Backoff from biased distribution Example: Always select a small backoff value

Transmit

wait

B1 = 1

B2 = 20

Transmit

wait

B2 = 19

B1 = 1Misbehaving node

Well-behaved node

45

Potential Solutions

Prevent misbehavior

Detect misbehavior

Penalize misbehavior

46

Game Theoretic Solutions [MacKenzie]

Assumes there is some cost for transmitting Nodes independently adjust access probability Under some assumptions, network reaches a

fair equilibrium

Game theoretic solutions to the misbehavior problem so far assume complete knowledge of the channel (difficult to have in multi-hop networks) Not yet clear whether partial information is adequate

47

Charging

Charge for transmitted packets

Transmitting more packets costs more

Disadvantages Per-packet charging can still allow misbehavior that

decreases the user’s delay Need to implement charging mechanism

48

Goals of proposed scheme

Detect misbehavior

Penalize misbehavior

49

Detecting Misbehavior

Observe each node

If a node does not wait long enough before transmitting, then conclude that it is misbehaving

Penalize the misbehaving node

50

Issues

Idle duration is a function of backoff interval chosen by a node

Observer does not know exact backoff value chosen by a sender Sender chooses random backoff

Hard to distinguish between maliciously chosen small values and a legitimate random sequence

Wireless channel introduces uncertainties Channel status seen by sender and receiver may be different

51

Observe backoffs chosen by a sender over multiple packets

Backoff values not from expected distribution Misbehavior

Longer delay in detection, since the distribution ofnon-deterministic backoff must be determined

Potential Solution: Use long-term statistics

52

A Simpler Approach

Remove the non-determinism

53

A Simpler Approach

Receiver provides backoff values to sender

Modification does not significantly change 802.11 behavior

54

Modifications to 802.11

• R provides backoff B to S D

AT

A

Sender S

Receiver R

CTS

AC

K(B

)

RTS

• S uses B for backoff for next packet

RTS

B

55

Detecting deviations

Receiver counts number of idle slots Bobsr

Condition for detecting deviations: Bobsr < B ≤ 1

Sender S

Receiver R

AC

K(B

) RTS

Backoff

Bobsr

56

Misbehavior Detection

The detection would always detect misbehavior IFIF all nodes observe identical channel status at all times

But all nodes do not see same channel status

Hidden terminals Fading

In general, cannot diagnose misbehavior with 100% accuracy

57

Penalizing Misbehavior

AC

K(B

+P

)

CTS D

ATA

Bobsr

Sender S

Receiver R

AC

K(B

)

RTS

Actual backoff < B

When misbehavior is suspected, larger backoff intervals are assigned

penalty mechanism

58

Penalty Scheme

Misbehaving sender has two options Ignore assigned penalty Easier to detect Follow assigned penalty No throughput gain

With penalty, sender has to misbehave more for same throughput gain

59

Diagnosing Misbehavior

If misbehavior suspected for “long enough” duration, conclude that the misbehavior is intentional

Higher layers / administrator can be informed of misbehavior

60

Multiple Observers

Currently, single observer is used (receiver) Data from multiple observers can be combined to

improve diagnosis

S

B

A R•S sends a packet to R

•A, B also monitor S

•Information from A, B, R may be combined

61

Moral of the Story

MAC layer misbehavior can severely affect throughput of well-behaved nodes

Improving predictability improves ability to detect misbehavior

Open issues: Using multiple observers Integrating diagnosis with higher layers

62

Distributed Mutual Exclusion

Joint work with Jennifer Welch and Jennifer Walter

63

Approach 1: implement existing distributed primitives on top of existing ad hoc routing protocols.

User Application

DistributedPrimitive

Routing Protocol

Ad-Hoc Network

Approach 2: modify distributed primitives to be aware of information from lower layers

User Application

Distrib.Primitive

Routing Protocol

Ad-Hoc Network

Why Design New Algorithms for MANETs?

64

Token-based: Only the node possessing the token may enter critical section

Nodes must have a way of sending requests to the token holder

One solution:

Mutual exclusion for fixed topology+

Routing on ad hoc networks

Distributed Mutual Exclusion

65

Link Reversal Algorithm [Gafni81](Routing Protocol)

A FB

C E G

D

66

Link Reversal Algorithm [Gafni81]

A FB

C E G

D

Maintain a directed acyclic graph (DAG) for each destination, with the destinationbeing the only sink

This DAG is for destination node D

Links are bi-directional

But algorithm imposeslogical directions on them

67

Link Reversal Algorithm

Link (G,D) broke

A FB

C E G

D

Any node, other than the destination, that has no outgoing linksreverses all its incoming links.

Node G has no outgoing links

68

Link Reversal Algorithm

A FB

C E G

D

Now nodes E and F have no outgoing links

Represents alink that wasreversed recently

69

Link Reversal Algorithm

A FB

C E G

D

Now nodes B and G have no outgoing links

Represents alink that wasreversed recently

70

Link Reversal Algorithm

A FB

C E G

D

Now nodes A and F have no outgoing links

Represents alink that wasreversed recently

71

Link Reversal Algorithm

A FB

C E G

D

Now all nodes (other than destination D) have an outgoing link

Represents alink that wasreversed recently

72

Link Reversal Algorithm

A FB

C E G

D

DAG has been restored with only the destination as a sink

73

Link Reversal Algorithm

Goal: Maintain DAG pointing to the “destination” despite topology changes

74

E

F

DA

B C

Static topology Spanning tree with edges directed toward the

token holder

Mutual Exclusion in Static Networks [Raymond89]

75

A

B C

ED ED

F

A

B C

ED E

F

76

Raymond’s Algorithm on Ad Hoc Networks

The algorithm can be implemented on top of routing protocol

– Routing algorithms provides abstraction of a fully connected network

Maintain a spanning tree using logical links in the “fully connected” network

“Adjacent” nodes in the spanning tree may be far from each other Potentially poor performance

77

Mutual Exclusion in Ad Hoc Networks

Gafni Variable topology, fixed sink

Raymond Fixed topology, moving sink

Proposed algorithm:

Mutual exclusion in ad hoc networks

Variable topology, moving sink

78

Moral of the Story

Existing algorithms not always appropriate

Algorithms for dynamic networks can be applied to ad hoc networks, but performance may be poor

Taking into consideration lower layer information can help

79

On to the preaching …

80

Abstractions

Of necessity, algorithm designers work with abstractions

Physical layer is messy

Abstractions hide “unnecessary” physical layer details

81

Abstractions

But some details are important.

Many common mistakes.

I am guilty too … but hopefully learning from the mistakes

82

Transmission “Range”

Transmission range R

R

83

Transmission “Range”

Given the thermal noise, beyond a certain distance reliable communication infeasible at a desired rate

Converse often assumed true: Within transmission range, reliable communication is assumed always feasible

This assumption is not accurate•Reliability depends on SINR

Assumption may perhaps be OK for order statistics, but the constants matter in practice

84

Interference “Range”

Interference “range” assumed to be the distance over which a transmission “collides” with another transmission

Assumed that if a host transmits, no other transmission within interference range will succeed

Not accurate: Reliability depends on SINR

85

Interference “Range”

C FA B EDDATA

Interference“range”

Whether A’s interferenceresults in unreliable

reception at Ddepends on SINR at D

86

Graceful Degradation

Transmission “range” (or reliability) depends on SINR and bit rate

Even if transmission at a higher rate fails, low rate transmission may be feasible

Distance

Throughput Modulation schemes providea trade-off betweenthroughput and “range”

87

Energy Consumption

Common assumption:

Energy required to transmit on a hop = k d

k and θ typically assumed to be constants

Proofs relying on constant k, θ may break when they are not constants

θ

88

Energy Consumption

When k,θ = constant, links AC and BD cannot BOTH be on energy efficient routes (considering only transmit energy)

With constant k,θ, energy efficient routes do not need to intersect [Narayanaswamy02]

A

BC

D

89

Energy Consumption

Consider routes AC and BD With fixed k and fixed θ > 2, energy optimal

routes are A-B-C and B-C-D (direct links A-C and B-D are not optimal)

Energy-efficient routes do not intersect

A

B C

D

4

4

335 5

90

Energy Consumption

Let k be much smaller on diagonal links (alternatively, θ ≈ 2 on diagonal links, and 3 on other links)

Diagonal links cheaper than other routes Energy efficient routes must intersect

A

B C

D

4

4

335 5

91

Geographic Location

Many algorithms rely on knowledge of physical location

Location estimates in practice contain some error

The error can affect correctness of geographic routing [Saeda04]

92

Summary

Physical layer characteristics matter

Can affect algorithm performance and correctness

93

End of preaching …

94

Interesting Open Problems

Protocols that achieve “capacity”

Distributed algorithms for ad hoc networks Shared memory Message ordering Group communication …

Complexity as a function of mobility

Applications for ad hoc networks

95

Thanks!

http://www.crhc.uiuc.edu/wireless/

96

Thanks!

http://www.crhc.uiuc.edu/wireless/

97

Handling other misbehavior

Receiver may misbehave by assigning large or small backoff values

Sender can detect receiver assigning small backoff values Backoff assigned by receiver has to follow well-known

distribution Sender uses larger of assigned backoff and expected

backoff

98

Handling other misbehavior

Detecting receiver assigning large backoff values not handled Equivalent to receiver not responding at all Need higher layer mechanisms

Collusion between sender and receiver Harder to detect Requires an observer that can monitor both sender and

receiver