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.