MobySpace : Mobility Pattern Space Routing for DTNs - Jeremie Leguay
Routing is a challenge in DTNs (Delay Tolerant Networks). Regular ad- hoc routing protocols fail because the topology suffers from connectivity disruptions.
MobySpace : Mobility Pattern Space Routing for DTNs Jérémie Leguay1,2, Timur Friedman1, Vania Conan2
Basic concept Problem:
B wants to send a bundle to E, but B and E are not at the same location.
A
?
• Routing is a challenge in DTNs (Delay Tolerant Networks). Regular adhoc routing protocols fail because the topology suffers from connectivity disruptions.
B
Proposition:
Location Z
• We propose to use mobility patterns of nodes, i.e. regularities in nodes contacts or movements, to define their position in a virtual Euclidean space used for routing. This space is called the MobySpace. • Each node’s position in the MobySpace (its MobyPoint) is flooded throughout the network. Other nodes use this information for routing.
? D
E
B has 3 possibilities: • keep the bundle. • give it to D.
C
• To route a bundle, a node chooses among its physical neighbors. It passes the bundle to the neighbor whose MobyPoint is closest to the destination’s. • The MobySpace can be defined in many ways, e.g. type/number of dimensions, distance function. This poster describes preliminary work.
• give it to A.
Location X
B uses the MobySpace to decide what to do.
Location Y
Fig. 1 : example scenario
A MobySpace • Let’s consider users with power-law based mobility patterns. Their frequency of visits to locations follows a power-law distribution. This behavior has often been observed in reality. • Each dimension in the MobySpace represents a location in the physical space. Each coordinate corresponds to the probability of finding the node at that location. We assume that these probabilities are known.
B decides to transfer the bundle to A, the closest to E in the MobySpace.
Z 1
B
D C
• Euclidean distance is used. p 1
p 1 0
X YZ
A
0
p 1
p 1
X YZ
B
0
X YZ
C
0
p 1
X YZ
D
0
Y
1
A In the MobySpace X YZ
E
0
E
Fig. 2 : node mobility patterns
Fig. 3 : MobySpace
1
X
Simulation results We simulated nodes with power-law based mobility patterns (d, the power-law exponent). We compared MobySpace routing to:
d
1.1
1.5
2
Epidemic
10.9
13.2
16.2
• Epidemic routing: Bundles are flooded in the network. It is the optimum in terms of delays but leads to high buffer and radio utilization.
Opportunistic
123.3
287.4
550.2
Random
117.8
160
203.3
• Opportunistic routing: A node waits to meet the destination in order to transfer its bundle. It involves only one transmission per bundle.
MobySpace
103
59.1
54.6
• Random routing: At any time, a node may transfer the bundle to a neighbor chosen at random. Loops are avoided. Preliminary simulations have shown promising results: • Low delays compared to Random and Opportunistic. • Low route lengths compared to Epidemic and Random.
Simulation parameters: 50 mobile nodes, 25 locations, pause time at each location is uniformly distributed on [5s,15s], nodes generate bundles every 30s toward each of the others during the first 500s, simulation time is 4000s.
Average bundle delay (s) d
1.1
1.5
2
Epidemic
3.7
3.7
3.8
Opportunistic
1
1
1
Random
44.5
55.9
69.8
3.3
3.2
3.2
MobySpace
Average route length (hops) This work has been funded by the ANRT through a CIFRE grant, and by EuronetLab, and was conducted at the Université Pierre et Marie Curie (1) and Thales Communications (2).
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