Evaluating Mobility Pattern Space Routing for DTNs Jérémie Leguay Thales Communications/U. P&M Curie co-authors: Timur Friedman (U. P&M Curie), Vania Conan (Thales Communications) Barcelona, 27 April 2006
Outline Main Contribution Euclidean virtual space for DTN (Delay Tolerant Networks) routing Space built on mobility patterns Evaluation using “real” mobility traces
Outline Problem statement Routing proposition Dartmouth data Simulation results INFOCOM – April 2006
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Evaluating Mobility Pattern Space Routing for DTNs
Problem statement Problem of routing
Routing is a challenge in DTNs (Delay Tolerant Networks) [Lindgren, Burgess, Wang, Widmer, …]. Regular ad hoc routing protocols fail because topology suffers from connectivity disruptions:
Partitions Long-delay links
Example:
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Location X
3
Location Y
Location Z
Evaluating Mobility Pattern Space Routing for DTNs
Routing decisions are taken using nodes’ mobility patterns.
Give bundles to nodes that we believe are more likely to deliver them.
Use of a virtual Euclidean space to make routing decisions.
MobySpace usage A node’s mobility pattern defines its position in the virtual Euclidean space.
To route a bundle, a node passes the bundle to the neighbor whose position is closest to the destination’s.
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Evaluating Mobility Pattern Space Routing for DTNs
MobySpace concept A MobySpace is defined by: The number of dimensions The meaning of the dimensions (a probability, a frequency, etc…) A distance function
Examples of MobySpace:
Frequency of visit based: Each dimension in the MobySpace represents a physical location. Each coordinate corresponds to the probability of finding the node at that location. 1
B
D
Y
C 1
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A
5
0
E
1
Contact based: Each dimension in the MobySpace represents the frequency of contacts between two given nodes.
Evaluating Mobility Pattern Space Routing for DTNs
X
Possible limits Dissemination of mobility patterns
The mobility pattern of the destination needs to be known.
Mobility patterns may be difficult to share between nodes.
Nature of mobility patterns
Mobility pattern of nodes may change too rapidly.
The mobility pattern might not capture some essential information.
E.g. time of day
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Single copy scheme
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May suffer in a lossy environment.
Evaluating Mobility Pattern Space Routing for DTNs
MobySpace evaluated The frequency of visit based MobySpace
Each dimension in the MobySpace represents a physical location. Each coordinate corresponds to the probability of finding the node at that location. (≠ geographical routing)
Motivation Nodes’ frequencies of visits to locations have been observed to follow a power-law distribution in a certain number of cases. [Dartmouth,UCSD].
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Evaluating Mobility Pattern Space Routing for DTNs
Dartmouth data Dartmouth Wi-Fi access network [Kotz] One of the largest data collection efforts Between 2001 to 2004
13,000 MAC addresses 550 APs (academic buildings, library, sport infrastructures, administrative buildings, student residences, etc…)
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Mobility data used
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Users’ sessions (pre-processed by Song et al.)
January 26th 2004 and March 11th 2004 (Spring semester prior to spring break)
Hypotheses to obtain DTN-like data
APs considered to be locations Connection to a same AP = contact
Evaluating Mobility Pattern Space Routing for DTNs
Simulation parameters General settings: 45 days of Dartmouth traces replayed 300 mobile nodes sampled from 5545 (computational reasons) 536 locations (No sampling)
Traffic generation: 100 random mobile nodes are active (i.e., generate traffic) Each active node sends 5 bundles to different destinations Active nodes are present the first week Nodes have knowledge of their mobility patterns
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5 global runs
Student t distribution to compute 90% confidence intervals
Evaluating Mobility Pattern Space Routing for DTNs
Routing comparisons Epidemic routing
Bundles are flooded in the network. It is the optimum in terms of delays and delivery but leads to high buffer and radio utilization.
Opportunistic routing
A source waits to meet the destination in order to transfer its bundle. It involves only one transmission per bundle.
Random routing
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Like MobySpace but random node preferences as opposed to preferences defined by mobility patterns.
Hot potato routing
At any time, a node may transfer the bundle to a neighbor chosen at random. Loops are avoided.
Evaluating Mobility Pattern Space Routing for DTNs
Simulation results Summary: Delivery ratio (%)
Delay (days)
Route length (hops)
Epidemic
82.0
12.5
7.1
Opportunistic
4.9
15.9
1.0
Random
7.2
16.6
3.12
Potato
10.7
19.1
72.7
MobySpace
14.9
18.9
3.8
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Lessons:
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MobySpace outperforms the other single copy protocols in delivery ratio
Potato engenders many more transmissions
MobySpace is next to Epidemic in delivery ratio, while only using selected contact opportunities
Evaluating Mobility Pattern Space Routing for DTNs
Simulation results With “most active” users: Users that are present all 45 days (835 users) Summary:
Delivery ratio (%)
Delay (days)
Route length (hops)
Epidemic
96.7
3.1
7.9
Opportunistic
10.7
17.6
1.0
Random
14.0
17.9
3.5
Potato
38.9
19.1
317.0
MobySpace
50.4
19.5
5.1
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Lessons:
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Results are globally improved
MobySpace far outperforms other single copy protocols
Evaluating Mobility Pattern Space Routing for DTNs
Conclusion and future work Conclusion Proposition of MobySpace, a routing scheme for DTN that uses a virtual space constructed upon nodes’ mobility patterns. Evaluation with real mobility traces MobySpace outperforms the other single copy schemes we evaluated in delivery ratio while keeping a low number of transmissions
Ongoing and future work
Introduction of controlled flooding mechanisms
we expect a gain in delay and delivery ratio
Definition of other kinds of MobySpace Study using other data sets INFOCOM – April 2006
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Evaluating Mobility Pattern Space Routing for DTNs
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