Title: EnergyEfficient Forwarding Strategies for Geographic Routing in Lossy Wireless Sensor Networks
1Energy-Efficient Forwarding Strategies for
Geographic Routing in Lossy Wireless Sensor
Networks
Karm Seada, Marco Zuniga, Ahmed Helmy, Bhaskar
Krishnamachari Department of Electrical
Engineering University of Southern
California SenSys04
- 2005-09-20
- Kim, Kwang-Soo
2Contents
- Introduction
- Greedy Forwarding
- Model Metric
- Realistic channel model
- Evaluation metric
- Geographic Forwarding strategies
- Distance/Reception based policy
- Blacklisting
- Simulation Results
- Conclusions
3Introduction
- Geographic routing
- Information delivery in wireless sensor networks
- Location information of node
- Nodes know only the location information of their
direct neighbors - Greedy forwarding mechanism
4Greedy Forwarding(1/2)
5Greedy Forwarding(2/2)
- Forwarding a packet to the neighbor that is
closest to the destination - Sufficient network density
- Accurate localization
- High link reliability
- In real world, wireless links can be highly
unreliable - Unreliable links exposes a key weakness in greedy
forwarding
6Proposed method
- Neighbor classification based on link reliability
- Distance
- Loss characteristics
- Blacklisting / neighbor selection
7Realistic channel model for lossy sensor networks
- the transmitter-receiver distance
- the signal to noise ratio(SNR)
- encoding ratio
- the frame length
8Samples from a realistic analytical link loss
model
9Evaluation Metric
- Deliver Rate(r) percentage of packets sent by
the source which reached the sink - Total number of Transmissions(t) total number
of packets sent by the network, to attain the
delivery rate - Energy efficiency(Eeff) number of packets
delivered to the sink for each unit of energy
spent by the network
10Energy efficiency
- r delivery rate
- t the total number of transmissions
- psrc the number of packets sent by the source
- etx and erx the number of energy required by a
node to transmit and receiver a packet - ere the energy used to read only the header of
the packet - n the expected number of neighbors
- K constant including etotal and a conversion
factor for energy unit
11Geographic Forwarding strategies for lossy
networks
- Distance-based policy
- Nodes need to know only the distance to their
neighbors - Reception-based policy
- In addition to the distance, nodes need to know
also the packet reception rates of their
neighbors - Individual nodes can estimating the reception
rate by monitoring the channel and observing
packet success and loss events
12Blacklisting
- To avoid weak links
- Blacklisting a set of neighbors based on a
certain criteria, and then forward to the node
closest to the destination among the remaining
neighbors - Distance-based blacklisting
- Neighbors above a certain distance are likely to
have weak links. - Reception-based blacklisting
- Classifying nodes based on the quality of their
links absolute reception blacklisting, relative
reception blacklisting
13Distance-based Forwarding(1/2)
14Distance-based Forwarding(2/2)
Threshold 20
Blacklist Region
15Reception-based Forwarding (1/3)
16Reception-based Forwarding(2/3)
Threshold 20
Blacklist Region
17Reception-based Forwarding(3/3)
D
S
18Experimental Environment
- Network size 100 to 1000 nodes having the same
radio characteristic - Density 25, 50, 100, 200
- Radio range 40m
- Random distribution
- Retransmissions 10
19Distance-based Blacklisting Scheme
20Absolute Reception-based Blacklisting Scheme
21Relative Reception-based Blacklisting Scheme
22Performance of Geographic Forwarding Strategies
at Different Densities
23Conclusions
- Several geographic forwarding strategies
- Blacklisting / neighbor selection
- Distance/reception-based policy
- Reception-based strategies are more efficient
than distance-based strategies - Proposed geographic forwarding approaches
- Energy-efficiency
- Minimizing route disconnections