1. Wireless Sensor Networks Routing
Professor Jack Stankovic
University of Virginia
2006

2. Single Hop Networks Diameter = 1 Any real applications? Destination
Source

3. Fixed Deployment
Diameter = 4
Comm.
Range

4. Ad Hoc Deployment Neighbor Discovery
Data Structure
Diameter = ?
ID Location
x,y
a,b
c,d 1 3 2

5. Question Suppose probability of a packet getting to next hop is 95%
What is the probability of a packet making it across 10 hops?
(.95) ~= 60% 10

6. Most WSN Multi-hop Ad hoc deployment
Need “more interesting” routing protocols
Find routes on-demand
Energy issues
Irregular communication range
Interferences
Congestion …

7. Outline – 9 Routing Algorithms
GF (SGF; GPSR)
DSR (supports mobility) (MANET)
AODV (supports mobility) (MANET)
Directed Diffusion
SPEED (RT)
RAP (RT)
Critique: SPEED vs. RAP
IGF (supports mobility, stateless)

8. Other Routing Algorithms (see text)
Perimeter face routing
Trajectory based routing
Cluster head routing
Minimum spanning trees
GEAR
GF plus consider energy
Rumor Routing
(total of 15 routing algorithms)

9. Principles Decentralized Aggregate behavior Minimize state information
Location based (not ID based - usually)
Mobility (possible)
Integration of routing function with “other” functions (e.g., data aggregation)
Specialized patterns (N->1 base station)

10. Sensor Net Routing End-to-end Real-time Collisions Last Mile
Congestion
Power
Security
Mobility
Last Mile
Destination
Source
Base Station
Assumption: Nodes know location (localization)

11. Last Mile Semantics At least 1 - Any At most 1 All
Unicast – exactly which node by ID

12. Geographic Forwarding (GF)
GF always chooses a node that is closest to the destination.
Every node knows its location. s d

13. GF – Information Required
Node i (maintains routing table)
My location
List of neighbors and their locations
Destination location
Find neighbor closest to destination
How? D S

14. GF What if none in the correct direction GF stops
Does not handle voids
GPSR (goes around voids; can even go in opposite direction for awhile)

15. Voids and GPSR
Left Hand Rule
Destination
VOID
Source

16. Summary - GF Destination by geography/location not node ID
Implications
Individual nodes are not important
Location is important
Route to area (all/any nodes in that area)
Many protocols extend basic GF
Example: GPSR, SGF, IGF, SIGF

17. MANET Routing Mobile - nodes move
Ad hoc – no established infrastructure or central administration
DSR – dynamic source routing is a technique where the sender determines the complete sequence of nodes in the route
AODV

18. Dynamic Source Routing (DSR)
Route discovery (dynamic – on demand)
Route reply
Data delivery
Route maintenance (in case Source, Destination, or router node moves out of range)

19. MANET: Dynamic Source Routing (DSR) – Route DiscoveryZ S E F B C M L J A G H D K I N
Represents a node that has received Route Request
Packet (RREQ) for D from S

20. Broadcast transmission
Route Discovery in DSR
Broadcast transmission Y Z
[S] S E
[S] F B
[S] C M L J A G H D K I N
Represents transmission of RREQ
[X,Y] Represents list of identifiers appended to RREQ

21. Route Discovery in DSR Y Z S [S,E] E F B [S,B] C M L J [S,B] A G [S,C]H D K I N

22. Route Discovery in DSR Y Z S E F B [S,E,F] C M L J A G H D K [S,C,G] I
Node C receives RREQ from G and H, but does not forward
it again, because node C has already forwarded RREQ once

23. Question How can a node know not to forward request again?
Detect duplicate requests by keeping a list of
<initiator ID, request ID> for a time period

24. Route Discovery in DSR Y Z S E F [S,E,F,J] B C M L J A G H D K I N
[S,C,G,K]

25. Route Discovery in DSR Y Z S E [S,E,F,J,M] F B C M L J A G H D K I N
Node D does not forward RREQ, because node D
is the intended target of the route discovery

26. Questions Flooding Optimal Route found
Cost (messages, energy, time)
MANET networks => nodes
WSN => 1000s of nodes
WSN also have high density (lots of collisions; more wasted energy)
Optimal Route found
Needed?
Movement rates that can be supported?

27. Route Reply in DSR Y Z S RREP [S,E,F,J,D] E F B C M L J A G H D K I N
Represents Route Reply (RREP)
control message

28. Route Reply Options for replying (routes need not be bi-directional)
Use reverse path (most common choice)
Assumes symmetry in node-node communication capability
Look in node D cache and see if a route to the sender exists and use that route
Find return route using route-discovery

29. Data Delivery in DSR Y Z DATA [S,E,F,J,D] S E F B C M L J A G H D K I
Note: Packet header size grows with route length

30. DSR Once path set up use it for “awhile” On movement of nodes
During this period – no routing overhead
On movement of nodes
Re-establish path
Note: nodes in MANET networks must be willing to act as routers as well as source/destination

31. DSR - Route Maintenance
No periodic updates from neighbors as found in many routing solutions
Consumes too much energy
Instead
Monitor route and inform sender of any routing problems
Hop-by-hop ack – if a message M is not ACKed after N attempts then the original sender is notified

32. Variations in Route Maintenance
Use end-to-end ACKS instead
Fix route from point of bad link instead of starting over

33. Summary - DSR Designed for MANET networks
Sender determines the complete sequence of nodes (only (dynamically) when needed)
No periodic routing table update messages, but size of message increases as size of network grows (OK for small diameter networks)
Saves power
Adapts (quickly?) to routing changes when hosts move
Required little overhead when hosts do not move
Route lengths are close to optimal
Use same path over and over – nodes will die fast?
Various optimizations have been developed

34. Ad Hoc On Demand Distance Vector (AODV)
Loop free routes
Repairs broken links
Does not require global periodic routing advertisements
Nodes not in active paths neither maintain any routing information nor exchange periodic routing tables
Nodes discover routes when needed and then routing tables are used
Avoids path length problem of DSR (scales better)
Used for mobile networks

35. AODV – Route Discovery Y Z S E F B C M L J A G H D K I N
Represents a node that has received RREQ for D from S

36. Route Requests in AODV S ->D ? Y Z S E F B C M L J A G H D K I N
Represents transmission of RREQ (hello messages) –
only when necessary
Keep local routing tables

37. Route Requests in AODV S ->D ? E, C, B Y Z S E F B C M L J A G H DK I N
Represents links on Reverse Path
Created as a packet moves toward destination

38. Reverse Path Setup in AODVY Z S E F B C M L J A G H D K I N
Node C receives RREQ from G and H, but does not forward
it again, because node C has already forwarded RREQ once

39. Reverse Path Setup in AODVY Z S E F B C M L J A G H D K I N

40. Reverse Path Setup in AODVY Z S E F B C M L J A G H D K I N
Node D does not forward RREQ, because node D
is the intended target of the RREQ

41. Forward Path Setup in AODVY
S->D F
S->D E C Z S E F B C M L J A G H D K I N
Forward links are setup when RREP travels along the reverse path
Represents a link on the forward path

42. AODV
Nodes not along the path determined by the RREP will timeout (after about 3 sec) and will delete reverse pointers
Is this a general principle for WSN? For mobile networks?
Expiration time for the route table entry (updated after every message)

43. Route Table Entry Data Destination Next hop Number of hops
Sequence number for destination
To avoid loops
Active neighbors for this route
who will send me packets for this destination (notify them of problem if my link to next hop breaks)
Expiration time for the route table entry
to clean up the table

44. AODV Route Maintenance 2 choices
Periodic hello messages can be used to ensure symmetric links and to detect link failures
Principle?
Upon detection of problem – restart discovery process with increased destination sequence number

45. DSR vs AODV
DSR – all route information is stored in packet itself, bad for long routes
Dynamic
Set up route and then use for a long time
AODV – route information is in temporary routing tables – only on routes currently in existence

46. Directed Diffusion Well known One of first targeted for WSN
Routing and queries intimately tied together
How many people do you observe in area X?
Give me the temperature reading for the next hour in area Y
Diffuse the query into the sensor network
Query is persistent (until time t)
Must amortize cost of finding route over data delivery (learn good routes)

47. Directed Diffusion A Flexible Framework/Paradigm
Allows many choices for various aspects of the “solution”
Remind you of BMAC? (for MAC layer)
This is for routing

48. Directed Diffusion – Main Parts
Node (e.g., base station) requests data by sending an interest for named data
Data centric routing
Data generated by sensors in response to query is sent in attribute-value pairs
Data matching the interest is drawn towards the requester
Gradients

49. Directed Diffusion Attribute-Value Pairs
5 attribute value pairs – cache request
Type =
mammal
Value =
horse
Duration =
3-4 PM
Periodic
Rate = Y
Area =
{a,b;c,d}
Response might be from node A
horse at 3:30 at location x1,y1

50. Directed Diffusion – Other Features
Intermediate nodes can cache or transform data, e.g., performing data aggregation (application dependent)
Now combine routing, queries, and data aggregation
Biological metaphor (ants and chemical trails)
Form of flooding

51. Flooding General Principle When you don’t know where things are
When you need to inform entire network of something
Disseminate code
Disseminate system parameters
Optimize

52. Flooding Restricted Flood Inform all nodes within “n” hops of a node i
How?
TTL (time to live field in packet header)
Principle
In n=3 the neighbors forward packet after decrementing counter to 2, same at the next hop; when counter = 0 stop

53. Flooding A wave propagates/diffuses through the network
What can happen due to MAC layer collisions?
A node may miss the information
Flood
Flood
Collision

54. Back to Directed Diffusion
Yellow nodes have no
interest in data
(iii) B, C and S
activate sensors
for event of
interest S E F B C M L J A G H D K I N
D sends interest for named data – attribute-value pairs
includes area of interest
(ii) Nodes record interest (S, B, C) (may perform data aggregation
on return path)

55. Directed Diffusion S E F B C M L J A G H D K I N 1 1 1 1 1 1 1 1
Gradients set up for return path – to draw data to D
Multiple paths are supported

56. Directed Diffusion S might send 2 of 3 messages to E and 1 of 3 to CB C M L J A G 1 H D K 1 I N 1
After D received data
Reinforce certain paths, e.g., those with lowest delay
Negative reinforcement for unappealing routes

57. Directed Diffusion – Routing Information per NodeB C M L J A G H D K I N
Each node maintains an interest cache
Each entry in cache has a gradient field for each neighbor
Includes a duration field – after which this query terminates

58. Directed Diffusion (4 aspects) – Flexible Framework
Interest Propagation
Flooding, constrained flooding, use previously cached data
Data Propagation
Reinforce single path, multiple paths with different quality, with probabilistic forwarding
Data Caching and Aggregation
Application semantics embedded
Reinforcement
When, how many neighbors, negative reinforcement

59. Directed Diffusion (DD)
Loops prevented “outside” the basic localized DD algorithm (uses a message cache)
Any node can apply reinforcement rules – enables local repair of failed or degraded paths
Many local rules can be applied in context of DD paradigm
Works for multiple sinks and multiple sources

60. Sensor Network Routing
Current routing solutions
Many classical solutions need routing tables the size of the network
Most use single path to destination (DSR, AODV,…)
Many use path finding beacons (DD) - bad for real-time
SPEED
local (neighbor) tables only
utilize multiple paths
no path set-up beacons needed
Real-time addressed

61. SPEED Protocol (7 Aspects)
API (and last mile processing)
Neighbor Beacon Exchange
Delay Estimation Scheme
Neighborhood Feedback Loop (NFL)
Semi-Stateless Non-deterministic Geographic Forwarding (SNGF)
Back-pressure Rerouting
Void Avoidance

62. SPEED Architecture

63. Question Can we convert SPEED to a B-MAC philosophy?
Flexible, highly parameterized, …

64. API (Last Mile Processing)
AreaMulticast
AreaAnyCast
Unicast
Destination
Possible
INTERFERENCE
Source

65. SPEED
USE VELOCITY

66. Nondeterministic Forwarding
Example 1: 1
(7,8) 2 3
(4,7)
(3,4) 7 5
( 1,6) 9
Delay
Position ID
RP: Relay probability
100%
(7,8) 2 RP
Position ID
Compute
Speed
Destination 7 9 2 s 3

67. Nondeterministic Forwarding
Example 2: 3
(7,8) 2 1
(4,7) 6
(3,4) 7
( 1,6) 9
Delay
Position ID
RP: Relay probability
50%
(7,8) 2
( 1,6) 9 RP
Position ID
Compute
Speed 7
Destination 9 s 2 3

68. Nondeterministic Forwarding
Example 3:
Example: Overload situation 2
(7,8) 5
(4,7) 3 4
(3,4) 7 1
( 1,6) 9
Delay
Position ID
15%
Drop
40%
(4,7) 3
45%
(3,4) 7 RP
Position ID
Compute
Speed
Drop ratio is computed according to the Neighborhood feedback control loop

69. Back-pressure re-routing
When all available forwarding nodes are congested, the sending node will drop packets, which will be perceived by previous nodes. Route changes. 3
Congestion Area 2
(7,8)
(4,7) 3
(3,4) 7 1
( 1,6) 9
Delay
Position ID M 7
DROP 9 2

70. Void Avoidance Only guarantees a greedy path (will not go backwards)

71. Evaluation
8-9 hops
6 CBR flows on one side of terrain send to one base station on the other side of terrain
Average number of hops (8-9)
90% CI (within 2-10% of mean)
Miss ratio results – not shown here but much better for SPEED
Under heavy congestion
added flows in center of terrain
Transient performance

72. Evaluation
(Added Congestion)
E2E Delay Energy Consumption

73. Performance Figure A. E2E delay profile of DSR
Figure B. E2E delay profile of AODV

74. Figure. D E2E delay profile of SPEED
Performance
Figure C. E2E delay profile of GF
Figure. D E2E delay profile of SPEED

75. Extensions?
Add power decision, i.e., choose next hop based on “most power” remaining
Add reliable link decision, i.e., compute link quality and use it for choosing next hop 3
(7,8) 2 1
(4,7) 6
(3,4) 7
( 1,6) 9
Delay
Position ID P LQ
1.7
3.0
2.5
3.1

76. RAP Goals Minimize e2e deadline miss ratio
Provide high-level services APIs for distributed micro-sensing applications (similar to DD and SPEED)
Minimize communication and processing overhead

77. RAP Architecture Sensing/Control Application Query/Event Service
Query/Event Service APIs
Query/Event Service
Coordination Service
Location-Addressed Protocol
Geographic Routing
Velocity Monotonic Scheduling
Prioritized MAC

78. BIG ISSUE What are the right interfaces for the protocol stack
MAC
Routing
Internet has TCP/IP
WSN needs Sensor Net Protocol (SP) equivalent!

79. Questions MAC – should MAC contain Routing – should routing contain
Priorities?
Congestion information?
Acks/No Acks decisions?
Multi-frequencies information?
Routing – should routing contain
Power issues
Data aggregation
Gradients
Link quality
Real-time

80. Velocity Monotonic Scheduling
Prioritized MAC
Query/Event Service
Coordination Service
Location-Addressed Protocol
Geographic Forwarding
Query/Event API
High-level abstraction for programming distributed micro-sensing applications
register_event {
virusFound(0,0,100,100), // area to post event
query { // query to be triggered
virus.count, // attribute
period=1.5, deadline=5, // timing info
base=(100,100) // base station location }

81. Velocity Monotonic Scheduling
Prioritized MAC
Query/Event Service
Coordination Service
Location-Addressed Protocol
Geographic Forwarding
Velocity
Timing constraint: deadline
Location constraint: distance to destination
Requested Velocity
Embody both constraints
Reflect local urgency
Velocity = Distance/Deadline
Velocity Monotonic Scheduling (VMS)
Priority = Requested Velocity

82. Example D A C B dis = 90 m; D = 2 s V = 45 m/s HIGH Priority
LOW Priority

83. Velocity Monotonic Scheduling
Static VMS
Fixed velocity on each hop
V=dis(x0,y0,xd,yd)/D
Dynamic VMS
Adapt velocity at intermediate node
Vi = dis(xi,yi,xd,yd)/Si
Slack: Si = D - elapsedTime
F(remaining distance)

84. Overall Deadline Miss Ratios with deadlines (5,10)
Deadline Miss Ratio: FCFS>DS>DVM,SVM
Why SVM better than DVM ??
Overall Deadline Miss Ratios with deadlines (5,10)

85. Critique - SPEED Extensions
No prioritization: uniform speed may not be what applications want
The uniform speed is not guaranteed (soft real-time)
Need periodic beacon to maintain neighbor table (costs energy)
Needs symmetric communication
Extensions
Multiple speeds
Different importance for streams
Consider energy explicitly

86. Critique - RAP
An early paper to provide soft real-time in sensor network
Provides Real-Time communication architecture
Provides VMS
As in SPEED, only soft real-time, no admission control, no guarantee
Difficult to consider congestion, noise, retries, lost packets, etc.
Real-time routing is very difficult because of
congestion, failures, retries, etc.

87. Implicit Geographic Forwarding
Tackle the rapid dynamics found in WSNs
To deal with
Power Down Nodes (Sleep mode)
Node Mobility
Node Failure
Scale
Lazy Binding (to the nth degree)
State Free – no routing tables
Scale – can’t have routing tables

88. Lazy Binding Concept
Fixed – at deployment have all the routes set up; not suitable for WSNs
Proactive – keep routing tables up to date checking for lost links and fixing them proactively
On-demand – wait for a request and then choose route
In IGF – wait until the forwarding operation actually happens
Defer mapping network topologies into volatile states (e.g. route state) as late as this operation allows (last 50 microsec in IGF).

89. IGF IGF is a combined Routing/MAC protocol
Asleep
Moving Away
IGF is a combined Routing/MAC protocol
Eligible nodes - 60 degree cone (shift cone if necessary)
RTS - set timer based on distance and energy remaining

90. Summary of Evaluation Tested for
Ten times improvement in delivery ratio under high dynamics compared to best solutions
Reduces end-to-end delay significantly
Reduces control overhead significantly
Tested for
Static, mobile and power saving networks
Test in presence of voids, localization errors, different densities, toggle and sleep percentages

91. Simulation Evaluation
Performance under mobility
Mobile robots with attached motes searching for mines and reporting results back to a base station
Toggle period is the time interval between consecutive transitions into a sleep state.
Sleep percentage – the percentage of time a node is in sleep mode
Sleep percentage set at 30%for varying toggle periods
Packet Delivery Ratio
Under High mobility
Packet Delivery Ratio
Under Node State Transition

92. Summary Reverse Path AODV DSR DD LAR Neighbor Table GF GPSR SPEED
IGF (none)

93. Summary Routing with global tables not appropriate
ID-based not as appropriate (more for MANET networks)

94. Summary Geographic/Location based
Asymmetries – Symmetric Geographic Forwarding (radio realities)
Voids
Fast dynamics
Real-time
Low cost
Integrate with power management, data aggregation and security (secure IGF)

95. Summary/Ideas Neighbor discovery Geographic location
Flooding (truncated)
Duration field (drop after delta t)
Eliminate duplicates
Biological metaphor – gradients
Velocity
Aggregate Behavior

96. Summary/Ideas Specialized traffic patterns
Optimize for power, congestion, robustness
Integration of functionality
Tailorable via API
Unicast
Broadcast, Area Multicast, Anycast
Use link quality

97. Final Questions Congestion control Interaction with a MAC protocol
Is it needed?
Interaction with a MAC protocol
Reliable message transmission needed?
How/where to support reliability