universität stuttgart institute of parallel and distributed systems (ipvs) universitätsstraße 38...

Universität Stuttgart

Institute of Parallel and Distributed Systems (IPVS)

Universitätsstraße 38D-70569 Stuttgart

Hypergossiping: A Generalized Broadcast Strategy for Mobile Ad Hoc Networks

A. Khelil, P.J. Marrón, C. Becker, K. Rothermel


IPVS

Research Group

“Distributed Systems” 2

Overview

• Motivation

• Related Work

• System Model

• Hypergossiping

• Evaluation

• Conclusion and Future Work


IPVS

Research Group


Motivation (1)

• Ad hoc communication

◦ WLAN, Bluetooth, UMTS (UTRA-TDD)

Mobile Ad Hoc Networks (MANET)

• Examples of applications

◦ Vehicle ad hoc network

◦ Rescue scenarios

• MANETs may show

◦ significant variation in node spatial distribution

◦ significant variation in node movement

• Broadcasting is widely used in MANETs

◦ Flooding is a common approach


IPVS

Research Group


Motivation (2)

• Flooding encounters two main problems:

◦ In dense MANETs: broadcast storms

▪Collision, contention and redundancy

◦ In sparse MANETs: network partitioning

▪Flooding reaches only nodes of one partition

• Gossiping is probabilistic flooding

◦ Nodes forward messages with a certain probability to all neighbors, using MAC broadcast

◦ Variation in node density we adapted gossip probability to number of neighbors reduces broadcast storms

◦ Gossip still reaches only nodes of one partition

• Broadcast repetition strategy is needed


IPVS

Research Group


Overview

• Motivation

• Related Work

• System Model

• Hypergossiping

◦ Partition Join Detection

◦ Rebroadcasting

• Evaluation



IPVS

Research Group


Related Work

density

mobility

repeat forwarding restrict forwarding

sparse (partitioned) dense

low mobile (e.g. pedestrians)

highly mobile (e.g. vehicles)

Integrated Flooding (IF)

scoped flooding

hyper flooding

plain flooding

non-partition-aware protocols, e.g. adaptive gossiping

negotiation-based protocols

Goal: a generalized strategy that supports

a wide range of densities and

mobilities


IPVS

Research Group


System Model

• MANET

◦ N mobile nodes populating a fixed area A (density: d=N/A)

◦ Mobility is required to overcome partitioning

• Assumptions

◦ Fixed communication range R

◦ Nodes do not need

▪Location information

▪Velocity information

• Hello beaconing to acquire neighborhood information

• Broadcast data is relevant up to lifetime

◦ Source sets the initial lifetime

◦ Nodes decrement lifetime

• Messages are uniquely identified by “source.seqNum”

+

+

+

+

+

+

+

+

+

RA

+

+


IPVS

Research Group


Overview

• Motivation

• Related Work

• System Model

• Hypergossiping


◦ Rebroadcasting

• Evaluation



IPVS

Research Group


Our Approach: Hyper-Gossiping (HG)

• Goal: maximize reachability efficiently within the given max delay (lifetime)

• MANET:= set of partitions that split or join over time.

• Approach: we combine two strategies

◦ Gossiping for intra-partition forwarding

◦ Broadcast Repetition

Gossiping (forwarding)

Repetition (rebroadcasting)

Gossiping (rebroadcasting)


IPVS

Research Group


5

Broadcast Repetition: Basic Idea

1

3

5

47

6

2

3

2

47

6

1

3

2

3

2

partition join detectionMANET is partitioned

1

3

74

7

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2

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2

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6

rebroadcasting

m1

m1

m1

m5

m5

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m1

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5

47

647

6m5

m5

m5

m5

m1m5

m1m5

m1m5

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1

broadcast repetition


IPVS

Research Group


Partition Join Detection Heuristic

LBR_ownID1

ID2

..

IDk

LBR_recv

• Nodes maintain a list of the IDs of Last Broadcast packets Received ( LBR)

• Nodes share LBRs with neighbors using existing HELLO beacons

• Detection heuristic

If

then partition join is detected

• Heuristic parameters

◦ Max LBR list size: maxLBRlength

◦ Max tolerated intersection of LBR lists: IS_threshold

thresholdISownLBR

recvLBRownLBR_

_

__

A B


IPVS

Research Group


Rebroadcasting

• If a node detects a partition join, it sends the IDs of all (still relevant) received packets

• Receiver sends missed packets A

DATA

Buffer (node A)

P4

P5

P6

P7

time

B

Node A Node BP1

P2

P3

P4

P5

P6P7

P1

P2

P3

P4

P5


IPVS

Research Group


Overview

• Motivation

• Related Work

• System Model

• Hypergossiping


◦ Rebroadcasting

• Evaluation



IPVS

Research Group


Simulation Parameters

Area 1Km x 1Km

Number of nodes N = 50 .. 500

Communication range R = 100 m

Bandwidth r = 1 Mbps

Data size 280 Bytes

Mobility model Random waypoint

- Max speed v in {3, 12.5, 20, 30} m/s

- Pause 2 s

HELLO beaconing Random in [0.75 , 1.25] s

Wide density range

Wide mobility range

Lifetime 600 s

Buffer_size infinity

Simulation time 650 s

Simulation runs 10

ns-2 simulator


IPVS

Research Group


Hypergossiping Reachability

Reachability = number_of_reached_nodes / total_number_of_nodes


IPVS

Research Group


Hypergossiping MNFR

MNFR: Mean Number of Forwards and Rebroadcasts per node and per message


IPVS

Research Group


Integrated Flooding (IF)

• IMAHN project

• Integration of

◦ Plain flooding: every node forwards a newly received message once

◦ Scoped flooding: nodes forward a newly received message, only if a certain ratio of neighbors is not covered by the sender

◦ Hyper flooding: Nodes buffer all packets for a fixed time (=60s), and on discovering new neighbor rebroadcast all buffered packets

• Switch depending on relative speed

relative speed to node‘s neighbors

low_threshold high_threshold

Hyper Flooding

Plain Flooding

Scoped Flooding

(10 m/s) (25 m/s)


IPVS

Research Group


Comparison to Integrated Flooding (IF): Reachability

Reachability = number_of_reached_nodes / total_number_of_nodes


IPVS

Research Group


Comparison to Integrated Flooding (IF): MNFR

MNFR: Mean Number of Forwards and Rebroadcasts per node and per message


IPVS

Research Group


Conclusion and Future Work

• Hypergossiping is a generalized broadcast strategy for MANETs

◦ Adaptive gossiping for intra-partition forwarding

◦ Efficient broadcast repetition strategy on partition join

• Hypergossiping covers

◦ a wide range of node densities, and

◦ a wide range of node mobility levels

• Future Work

◦ Investigate different buffering strategies

◦ Adapt buffering parameters to node mobility


Institute of Parallel and Distributed Systems (IPVS)

Universitätsstraße 38D-70569 Stuttgart

Q&A

{khelil, marron, becker, rothermel}@informatik.uni-stuttgart.de

universität stuttgart institute of parallel and distributed systems (ipvs) universitätsstraße 38...

Documents

stuttgart hypergossiping

future work slide

manets flooding

partition gossiping

mobilities slide

rothermel slide

probabilistic flooding

scoped flooding hyper