Compact Routing with Minimum Stretch. Kei Takahashi. Introduction. In distributed networks, message relaying is inevitable Alltoall connections are physically impossible Nodes can dynamically appear, move, and disappear Some routing tactics are possible Broadcast Random relaying
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Kei Takahashi
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V3
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Message
To V3
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Port 1
Port 0
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Port 1
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V1 : Port 0
V2 : Port 1
V3 : Port 1
V0 : Port 0
V1 : Port 1
V3 : Port 2
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Message
To V3
log(n)
V1 : Port 0
V2 : Port 1
V3 : Port 1
V4 : Port 0
V5 : Port 1
V6 : Port 1
…
Port 0
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n1
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Stretch = 2
Cost = 5
5
6
Cost = 10
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4
Port V2
Problem definitionA302
A301
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NG
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OK
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A303
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port
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V1 :
Landmarks
Near nodes
Basic idea (1) : landmarksLandmark
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Landmark
v5
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v12
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label
port
v0,v3
v0
v1,v3
v7,v10
v8,v10
v1
v7
v8
(V3, V3, ):
(V10,V10,):

(V1,V3,) :
V3 :
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V1 :
Landmarks
v2,v3
v4,v3
v2
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v4
v9
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v11
v3,v3

v9,v10
v11,v10
v10,v10

Near nodes
v5,v3
v6,v3
v6
v5
v12
v13
v12,v10
v13,v10
v0,v3
v1,v3
v7,v10
v8,v10
(v3, v3, ):
(v10,v10,):

(v1,v3,) :
v2,v3
v3,v3

v6,v3
v9,v10
v10,v10

v11,v10
v5,v3
v6,v3
v12,v10
v13,v10
v0,v3
v1,v3
v7,v10
v8,v10
v2,v3
v3,v3

v6,v3
v9,v10
v10,v10

v11,v10
Optimal route
v5,v3
v6,v3
v12,v10
v13,v10
Obtained route
From v2
Costs : {v1 => 1, v3 => 3}
Take v1
Costs : {v0 => 2, v3 => 3}
Take v0
Costs : {v3 => 3}
Take v3
V0
4
1
V1
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1
3
V0
nα = 3
2
1
3
V1
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V3
1
Not suitable for a landmark
V3 :
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V0 :
V1 :
V2 :
V4 :
V5 :
V6 :
v1
v0
v7
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v4
v9
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v5
v6
v12
v13
nα = 3
V = {v0, v1, v2, v3}
D = {v2}
D = 1
Bv0 ∩ D = v2
Bv1 ∩ D = v2
Bv2 ∩ D = v2
Bv3 ∩ D = v2
V0
2
1
3
V1
V2
V3
1
nα = 3
V = {v0, v1, v2, v3}
C = {v1, v2}
Rv1 = 4 > 3.6 = n(1+α)/2
Rv2 = 4 > 3.6 = n(1+α)/2
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1
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Landmarks
1
// Calculate paths to nαshortest nodes from v
For each v ∈ V, perform truncatedDijkstra(nα)
// Here, less than nα nodes are nearer than u from v
For each u reached from v:// If ↓ is true, the best route is given by using that landmark
If no landmark is on the path from v to u:
store(v, eu(v)) at u
// Calculate shortest paths from landmarks to every node
For each l ∈ L, perform fullDijkstra(nα)
// v appearedFor each v ∈ V
Store (l, eu(l)) at u
Table size = size(label of node) * size(columns)
Size(label of node) = O(log(n))
Size(columns) ≤ L + nα = O(n1α log n + n(1+α)/2 + nα)
∴ Table size = O((n1α log n + n(1+α)/2 + nα) log n)
Search α which minimizes table size, and get α = 1/3 + (2 log log n) / (3 log n)Table size = O(n2/3 log4/3 (n))
Proof : table size = O(n2/3 log4/3 (n))(As a result, route(u, v) is always optimal in this case)
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