CMPE 259
Sensor Networks
Katia Obraczka
Winter 2005
Routing Protocols II
1-1
Announcements
 Reading assignment 1 is up.
1-2
Notes on Directed Diffusion
 Multiple paths can be used to forward data
back to the sink.
 Is it the same as multicast?
1-3
Data MULEs
1-4
Target deployments.
 Sparse networks.
 Multi-tiered deployments.
 Sensors.
 Wired access points.
 Mules.
1-5
Approach
 Mobile agents.
 MULEs: mobile ubiquitous LAN extensions.
 Mobility.
 Communication (short range).
• UWB radios? [low power and ability to handle bursts].

Buffering.
1-6
Pros and cons
1-7
Pros and cons
 Pros:

Energy efficiency ?
• Listen for the mule.

Intermittent connectivity.
 Cons:
 Increased latency.
1-8
Alternatives
Approaches
Latency
Base stations
Low
Ad-hoc
MULE
Power
High
Reliability
Infrastructure cost
High
High
Medium M/L
Medium
M/H
High
Medium
Low
Low
1-9
3-tier architecture
 Wired APs.
 Mules.
 Sensors.
1-10
Considerations
 APs have no limitations.
 Mules:
 Storage, mobility, ability to communicate with
sensors and APs.
 Unpredictable movement patterns.
 Can talk to other mules.
• Benefits?
 Robustness.
 Reliability.
1-11
More considerations…
 No routing overhead.
 Mules can transport data for multiple
applications.
 High latency.

Delay bounds?
 Mobility limitations.
1-12
System model
 Simple, discrete.
 Lots of assumptions.
 Realistic?
 Performance metrics:
Reliability.
 Buffer size.
 Delay?

1-13
Main results
 Buffer requirements at sensors inversely
proportional to ratio of number of mules to
grid size.
 Buffer requirement at mule inversely
proportional to ratio of number of mules to
grid size and ratio of APs to grid size.
 Relationship between buffer capacity,
number of mules, and reliability.
1-14
Energy-efficient routing
1-15
[Schurgers et al.]
 Two approaches:
Efficient data collection using aggregation.
 Load balancing: spread traffic uniformly.

1-16
Observations
 Energy-optimal routing needs to consider
future traffic.

Energy limitations.
T1 F sends 100 pkts to B.
B
Load balancing: ADB, ECB, FDB.
C
But, if nodes can only send 100 pkts,
D would no be able to deliver all of
F’s pkts to B.
D
E
T0 A and E send 50 pkts to B.
A
F
In this case, ACB, ECB, FDB.
1-17
Energy-efficient versus
energy-optimal
 Statistically optimal and only considers
causal information.
 Lifetime:worst-case time until node fails.
1-18
Traffic spreading
 Make sure that nodes are used uniformly
by routing.
 Gradient-based routing (GBR):
Directed-diffusion variant.
 Use shortest path (in number of hops) to sink
to forward data.

 Performance metric: ERMS.
 Root mean square of the PDF of energy used by
nodes.
1-19
Traffic spreading approaches
 Stochastic: node picks next-hop randomly
(chosen from neighbors with equal
gradient).
 Energy-based: node increases its “height”
when its energy falls below a certain
threshold. All nodes need to adjust their
height accordingly.
 Stream-based: divert streams from nodes
that are part of paths used b other
streams.
1-20
Results
 Target tracking scenario.
 Stream-based spreading performs the
best.
 Stochastic spreading does better than
energy-based and pure GBR.
1-21
[Krishnamachari et al.]
1-22
Energy-robustness tradeoff in
multipath routing
 Multipath for robustness.

Fault-tolerance through redundancy.
 Alternatively, reduce number of
intermediate nodes.
Single paths.
 Nodes use higher transmit power.

1-23
Considerations
 Energy metric: number of transmissions *
transmit energy.

Independent of number of receivers.
 Robustness metric:
 Probability message reaches sink in the face of
node failures.
 Assume that nodes fail with probability p
independently from other nodes.
 Pareto optimality criteria:
 Routing scheme dominates another iff more
robust with strictly less energy, or
 Iff it uses equal or less energy with strictly
higher robustness.
1-24
Results
 For the simple scenario chosen (with path
loss exponent equal to 2), the Pareto
optimal schemes only include single-path
routing.
 For higher path loss exponent, some
multipath schemes are dominated by single
path routing.
1-25