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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
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Outline
Preliminaries
Advertising
Preaching
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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
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Why Ad Hoc Networks ?
Potential ease of deployment
Decreased dependence on infrastructure
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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
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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)
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State of the Art
Lot of research activity on:
Routing Medium access control Quality of service
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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
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State of the Art
Many more (academic) problems … rich area
(Too) Many conferences MobiHoc SenSys MASS SECON …
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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
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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
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Outline
Preliminaries
Advertising
Preaching
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Our Research Themes
Exploiting physical layer capabilities
Protocols for directional antennas Rate adaptation Power control & Power save mechanisms Multi-channel mechanisms
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Our Research Themes
Distributed algorithms for ad hoc networks
Address assignment Mutual exclusion Leader election Token circulation
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Our Research Themes
Misbehavior in Wireless Networks
Protocol design for misbehavior detection
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Some of our past research …
Weak duplicate address detection Misbehavior detection Mutual exclusion
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Weak Duplicate Address Detection
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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
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Auto-Configuration inAd Hoc Networks
Worst case network delays may be unknown, or highly variable, or unbounded
Partitions may occur, and merge
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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
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Example: Initially Partitioned Network
D’s packets for address a routed to A
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Merged Network
Duplicate address detection (DAD) important to avoid misrouting
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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
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DAD
Strong DAD impossible with unbounded delay
How to achieve DAD ?
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Design Principle
If you cannot solve a problem
Change the problem
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Weak DAD: Requirement
Packets from a given host to a given address
should be routed to the same destination,
despite duplication of the address
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Example: Initially Partitioned Network
D’s packets for address a routed to A
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Merged Network:Acceptable Behavior
with Weak DAD
Packets from Dto address astill routed tohost A
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Merged Network:Unacceptable behavior
Packets from Dto address arouted tohost K insteadof A
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Weak DAD: Implementation
Integrate duplicate address detection with route maintenance
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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
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Weak DAD with Link State Routing
Address duplication not always detected
Duplication detected before misrouting can occur
Weak DAD Reliable, but potentially delayed
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Link State Routing (LSR): Example
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Weak DAD with LSR
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Weak DAD with LSR
Host X with key K_x joins and choose IP_A
(address duplication)
X
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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
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Just-in-Time DAD
Duplication detected before routing tables could be mis-configured
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Moral of the Story
Traditionally, address assignment and routing are independent algorithms
Duplicate address detection integrated with route maintenance can provide stronger properties
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Misbehavior Handling
Joint work with Pradeep Kyasanur
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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
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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
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CSMA/CA
Don’t transmit when channel is busy
Defer transmission for a random duration on idle channel
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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
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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
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Potential Solutions
Prevent misbehavior
Detect misbehavior
Penalize misbehavior
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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
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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
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Goals of proposed scheme
Detect misbehavior
Penalize misbehavior
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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
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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
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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
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A Simpler Approach
Remove the non-determinism
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A Simpler Approach
Receiver provides backoff values to sender
Modification does not significantly change 802.11 behavior
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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
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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
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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
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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
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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
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Diagnosing Misbehavior
If misbehavior suspected for “long enough” duration, conclude that the misbehavior is intentional
Higher layers / administrator can be informed of misbehavior
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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
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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
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Distributed Mutual Exclusion
Joint work with Jennifer Welch and Jennifer Walter
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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?
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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
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Link Reversal Algorithm [Gafni81](Routing Protocol)
A FB
C E G
D
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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
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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
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Link Reversal Algorithm
A FB
C E G
D
Now nodes E and F have no outgoing links
Represents alink that wasreversed recently
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Link Reversal Algorithm
A FB
C E G
D
Now nodes B and G have no outgoing links
Represents alink that wasreversed recently
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Link Reversal Algorithm
A FB
C E G
D
Now nodes A and F have no outgoing links
Represents alink that wasreversed recently
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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
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Link Reversal Algorithm
A FB
C E G
D
DAG has been restored with only the destination as a sink
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Link Reversal Algorithm
Goal: Maintain DAG pointing to the “destination” despite topology changes
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E
F
DA
B C
Static topology Spanning tree with edges directed toward the
token holder
Mutual Exclusion in Static Networks [Raymond89]
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A
B C
ED ED
F
A
B C
ED E
F
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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
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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
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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
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On to the preaching …
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Abstractions
Of necessity, algorithm designers work with abstractions
Physical layer is messy
Abstractions hide “unnecessary” physical layer details
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Abstractions
But some details are important.
Many common mistakes.
I am guilty too … but hopefully learning from the mistakes
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Transmission “Range”
Transmission range R
R
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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
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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
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Interference “Range”
C FA B EDDATA
Interference“range”
Whether A’s interferenceresults in unreliable
reception at Ddepends on SINR at D
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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”
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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
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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
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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
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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
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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]
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Summary
Physical layer characteristics matter
Can affect algorithm performance and correctness
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End of preaching …
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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
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Thanks!
http://www.crhc.uiuc.edu/wireless/
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Thanks!
http://www.crhc.uiuc.edu/wireless/
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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
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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