MESH-BASED GEOCAST ROUTING PROTOCOLS IN

AN AD HOC NETWORK

指導教授：許子衡 教授報告學生：翁偉傑

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0-7695-0990-8/01/$10.00 (C) 2001 IEEE

OUTLINE Introduction

Geocast via a Mesh

Simulation Environment

Simulation Results

Observations

Random Waypoint Model

Conclusions 2

INTRODUCTION

The goal of a geocasting protocol is to deliver a packet to a set of nodes within a specified geographical area.

In this paper, we present three different approaches for delivering packets to a geocast group and simulation.

we consider the effect the random waypoint mobility model has on the performance an ad hoc network protocol .

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GEOCAST VIA A MESH (1/3)

Protocols that use a mesh for multicasting in an ad hoc environment have been proposed in order to provide redundant paths between the source and the group members.

Use JOIN-DEMAND packets, instead of the conventional JOIN-REQUEST packets of multicast protocols, to insist that all MNs in the geocast region join the geocast group.

A JOIN-DEMAND packet is forwarded in the ad hoc network until it reaches an MN in the geocast region.

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GEOCAST VIA A MESH (2/3)

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Once the JOIN-DEMAND packet reaches an MN in the geocast region, a JOIN-TABLE is unicast back to the source following the reverse route taken by the JOIN-DEMAND.

MNs on the edge of the geocast region become a part of the mesh.

These nodes then use a localized flooding algorithm to transmit each geocast data packet to all reachable nodes within the geocast region.

we propose using a mesh-based approach to provide geocast communication, and we evaluate the performance of this approach via simulation.

GEOCAST VIA A MESH (3/3)

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SIMULATION ENVIRONMENT (1/2)

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Consider the following performance metrics: protocol overhead, network-wide data load, end-to-end delay, and goodput ratio.

Simulation environment is a 500 * 500 meter region.

Geocast region is a 100 * 100 meter region.

The geocast source transmits 20 data packets to the geocast region every second for 500 seconds

Each simulation trial has 300 MNs whose initial locations are randomly chosen from a uniform distribution Node mobility uses the random waypoint model

SIMULATION ENVIRONMENT (2/2) MN's speed from an average of 0 to 20 m/s in increments

of 5 m/s.

MN's pause time from an average of 0 to 20 seconds in increments of 5 seconds.

The average amount of data generated is approximately 9,750 packets in one simulation trial.

The average number of hops from the source to the geocast region was 2.54.

The average number of neighbors for each MN was approximately 16.

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SIMULATION RESULTS (1/5)

Overhead/Load

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the FLOOD approach has the largest number of redundant paths between the source and the geocast region, the BOX approach has the second largest number of redundant paths, and the CONE approach has the least number of redundant paths.

SIMULATION RESULTS (2/5)

Overhead/Load

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the control overhead that exists in the FLOOD approach is much larger than thecontrol overhead in our BOX and CONE approaches.

since the forwarding zone in the BOX approach is larger than the forwarding zone in the CONE approach, the BOX approach has more control overhead.

SIMULATION RESULTS (3/5)

Overhead/Load

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Regardless of pause time and speed, the FLOOD approach transmits the largest number of data packets, the BOX approach transmits the second largest number of data packets, and the CONE approach transmits the least number of data packets.

SIMULATION RESULTS (4/5)

Performance

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the CONE approach has lower end-to-end delay than the BOX and FLOOD approach for all mobility speeds.

the forwarding zone in the BOX approach is smaller than the forwarding zone in the FLOOD approach, the BOX approach has lower end-to-end delay than the FLOOD approach.

SIMULATION RESULTS (5/5)

Performance

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the FLOOD approach has a larger number of redundant paths in its geocast mesh. a larger percentage of packets are delivered in the FLOOD approach than in the BOX and CONE approaches.

OBSERVATIONS

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Observation 1 : Reducing the area of the forwarding zone reduces control overhead, network-wide data load, end-to-end delay, and network reliability.

Observation 2 : increasing average node speed results in decreased control overhead and decreased network-wide data load ； increasing average node speed results in decreased end-to-end delay ； increasing average node speed results in decreased network reliability

At one fixed average pause time：

Observation 3 : At one fixed average speed, increasing average node pause time results in increased network reliability.

RANDOM WAYPOINT MODEL

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顯示了所有的秒數 MN 的spend traveling

RANDOM WAYPOINT MODEL

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顯示所有的秒數 MN 的spend paused during the simulation.

RANDOM WAYPOINT MODEL

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我們定義一個 MN在移動 ad hoc網絡中的 dimensionless parameter:

CONCLUSIONS

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The FLOOD approach has the highest amount of control overhead and network-wide data load, but provides the highest level of reliability.

The CONE approach has the smallest amount of control overhead and network-wide data load, but provides the smallest level of reliability.

The CONE approach has the smallest end-to-end delay.

The FLOOD approach has the largest end-to-end delay.

The BOX approach fall between the FLOOD and CONE.