Post on 14-Dec-2015
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
Universität Stuttgart
IPVS
Research Group
“Distributed Systems” 2
Overview
• Motivation
• Related Work
• System Model
• Hypergossiping
• Evaluation
• Conclusion and Future Work
Universität Stuttgart
IPVS
Research Group
“Distributed Systems” 3
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
Universität Stuttgart
IPVS
Research Group
“Distributed Systems” 4
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
Universität Stuttgart
IPVS
Research Group
“Distributed Systems” 5
Overview
• Motivation
• Related Work
• System Model
• Hypergossiping
◦ Partition Join Detection
◦ Rebroadcasting
• Evaluation
• Conclusion and Future Work
Universität Stuttgart
IPVS
Research Group
“Distributed Systems” 6
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
Universität Stuttgart
IPVS
Research Group
“Distributed Systems” 7
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”
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RA
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Universität Stuttgart
IPVS
Research Group
“Distributed Systems” 8
Overview
• Motivation
• Related Work
• System Model
• Hypergossiping
◦ Partition Join Detection
◦ Rebroadcasting
• Evaluation
• Conclusion and Future Work
Universität Stuttgart
IPVS
Research Group
“Distributed Systems” 9
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)
Universität Stuttgart
IPVS
Research Group
“Distributed Systems” 10
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
6
2
3
2
4
5
6
rebroadcasting
m1
m1
m1
m5
m5
m5
m5
m1
m1
m1
5
47
647
6m5
m5
m5
m5
m1m5
m1m5
m1m5
m5m1
m5m1
m5m1
m5m1
1
broadcast repetition
Universität Stuttgart
IPVS
Research Group
“Distributed Systems” 11
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
Universität Stuttgart
IPVS
Research Group
“Distributed Systems” 12
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
Universität Stuttgart
IPVS
Research Group
“Distributed Systems” 13
Overview
• Motivation
• Related Work
• System Model
• Hypergossiping
◦ Partition Join Detection
◦ Rebroadcasting
• Evaluation
• Conclusion and Future Work
Universität Stuttgart
IPVS
Research Group
“Distributed Systems” 14
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
Universität Stuttgart
IPVS
Research Group
“Distributed Systems” 15
Hypergossiping Reachability
Reachability = number_of_reached_nodes / total_number_of_nodes
Universität Stuttgart
IPVS
Research Group
“Distributed Systems” 16
Hypergossiping MNFR
MNFR: Mean Number of Forwards and Rebroadcasts per node and per message
Universität Stuttgart
IPVS
Research Group
“Distributed Systems” 17
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)
Universität Stuttgart
IPVS
Research Group
“Distributed Systems” 18
Comparison to Integrated Flooding (IF): Reachability
Reachability = number_of_reached_nodes / total_number_of_nodes
Universität Stuttgart
IPVS
Research Group
“Distributed Systems” 19
Comparison to Integrated Flooding (IF): MNFR
MNFR: Mean Number of Forwards and Rebroadcasts per node and per message
Universität Stuttgart
IPVS
Research Group
“Distributed Systems” 20
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
Universität Stuttgart
Institute of Parallel and Distributed Systems (IPVS)
Universitätsstraße 38D-70569 Stuttgart
Q&A
{khelil, marron, becker, rothermel}@informatik.uni-stuttgart.de