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Efficient Geographic Routing in Multihop Wireless Networks. Seungjoon Lee*, Bobby Bhattacharjee*, and Suman Banerjee** *Department of Computer Science University of Maryland **Department of Computer Sciences University of Wisconsin-Madison. Proceedings of the 6th ACM international symposium - PowerPoint PPT Presentation
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Efficient Geographic Routing in Multihop Wireless Networks
Seungjoon Lee*, Bobby Bhattacharjee*,and Suman Banerjee**
*Department of Computer Science University of Maryland**Department of Computer Sciences University of Wisconsi
n-Madison
Proceedings of the 6th ACM international symposiumProceedings of the 6th ACM international symposiumon Mobile ad hoc networking and computingon Mobile ad hoc networking and computing
(MobiHoc '05)(MobiHoc '05)
Chien-Ku Lai
Outline
Introduction New Link Metric for Geographic Routing Link Cost Types and Estimation Simulation Conclusions and Future Work
Introduction- Geographic Routing (Position-based Routing)
This kind of routings uses location information for packet delivery
Neighbors locally exchange location information
Neither route establishment nor per-destination state is required
Introduction- Normalized Advance (NADV)
Instead of the neighbor closest to the destination, NADV lets users select the neighbor with the best trade-off between link cost and proximity
Introduction- about this paper
For the effective use of NADV, this work presents techniques for efficient and adaptive link cost estimation
Providing multiple techniques thus enabling nodes to choose the best scheme for the current network and system setting
New Link Metric for Geographic Routing
1. Background
2. Normalized Advance
Background
Link cost the power consumption required for a packet
transmission over the link
Link metric “degree of preference” in path selection
Background (cont.)
In many geographic routing protocols The current node S greedily selects the neighbor that is
closest to destination T
Background- Goal
To gain as large advance as possible for fast and efficient packet delivery
To balance the trade-off, so that we can select a neighbor with both large advance and good link quality
Normalized Advance (NADV)
Link Cost Types and Estimation
1. Packet Error Rate (PER)
2. Delay
3. Power Consumption
Packet Error Rate (PER)
Packet Error Rate (PER)
Using Probe Messages for PER Estimation
Using Signal-to-Noise Ratio for PER Estimation
Neighborhood Monitoring for PER Estimation
Self Monitoring for PER Estimation
Packet Error Rate (PER)- Using Probe Messages for PER Estimation
Packet Error Rate (PER)- Using Signal-to-Noise Ratio for PER Estimation
Assuming an AWGN (Additive White Gaussian Noise) channel, in the case of BPSK (Binary Phase Shift Keying), the bit error rate is given by
: the received power
: the channel bandwidth : the noise power
: the transmission bit rate
: the complementary error function
Packet Error Rate (PER)- Neighborhood Monitoring for PER Estimation
In IEEE 802.11 networks using the MAC sequence number A can count how ma
ny frames from neighbor B it has missed
The quality of two directional links may differ
Packet Error Rate (PER)- Self Monitoring for PER Estimation
Aging multiply PERs of unused links by 0.9 every 30 seconds
Delay
Two types of link delay medium time total delay – future work
Power Consumption
Simulation
1. Model
2. Results
Simulation Model
Simulator : ns-2 Deployment : uniform Region : 1000m x 1000m Nodes : 100 Maximum transmission range : 250m
Simulation Results- Number of transmissions/delivery
Simulation Results- Average Path Length
Simulation Results- Latency
Simulation Results- Using Delay as Link Cost
Simulation Results- Power Consumption
Conclusions and Future Work
Conclusions
This work has introduced NADV as link metric for geographic routing
Geographic routing with NADV provides an adaptive routing strategy is general can be used for various link cost types
This work presented techniques for link cost estimation
NADV also finds paths whose cost is close to the optimum
Future Work
To design a link cost model that balances multiple cost criteria
To implement the NADV framework on real testbeds and evaluate the performance in practice
Question?
Thank you.Thank you.
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