Übersicht
Untersuchte Netzstruktur und Problemstellungen
Topologie-basierte Routingprotokolle
• Destination-Sequenced Distance-Vector Routing (DSDV)
• Optimized Link State Routing (OLSR)
• Ad-Hoc On-Demand Distance Vector Routing (AODV)
• Dynamic Source Routing (DSR)
Geographische Routingprotokolle
Proactive protocols – OLSR
Combine link-state protocol & topology control
Optimized Link State Routing (OLSR)
Topology control component: Each node selects a minimal dominating set for its two-hop
neighborhood
• Called the multipoint relays
• Only these nodes are used for packet forwarding
• Allows for efficient flooding
Link-state component: Essentially a standard link-state algorithm on this reduced topology
• Observation: Key idea is to reduce flooding overhead
(here by modifying topology)
Multipoint Relays
MPR Concept
• Subset M of neighbors of given node S which covers all 2-hop neighbors of S
• Node A is covered if it can receive message from S either directly or via 1-hop neighbor
• Nodes in subset M are called relay point
Minimum-size multipoint relay is of interest for energy efficient broadcasting
• Reduce number of broadcast relays but
• Cover all nodes by the broadcast
Example for node S
• 1-hop neighbors: A, B, C, D, E, F
• 2-hop neighbors: U, V, W, X
• A multipoint relay: {A, B, D, E}
• A minimum-size multipoint relay: {C, F}
F U
X
D B
A
E V
W
S C
Multipoint Relays
Greedy approximation
• Repeat selecting node B which maximizes set of not so far covered nodes
Example
• (1) Maximum provided either by C or F; select C
• (2) Maximum provided then by F
• (3) All nodes covered; result {C, F}
F U
X B
A
E V
S
Übersicht
Untersuchte Netzstruktur und Problemstellungen
Topologie-basierte Routingprotokolle
• Destination-Sequenced Distance-Vector Routing (DSDV)
• Optimized Link State Routing (OLSR)
• Ad-Hoc On-Demand Distance Vector Routing (AODV)
• Dynamic Source Routing (DSR)
Geographische Routingprotokolle
AODV: Main Idea
S
D
RREQ
RREQ
RREQ
RREQ
RREQ RREQ
AODV: Main Idea
S
D RREQRREP
AODV: Main Idea
S
D 1
2 3
1 2 3
1 2 3
AODV: Node Mobility
S
D
RREQ RREQ RREQ
Übersicht
Untersuchte Netzstruktur und Problemstellungen
Topologie-basierte Routingprotokolle
• Destination-Sequenced Distance-Vector Routing (DSDV)
• Optimized Link State Routing (OLSR)
• Ad-Hoc On-Demand Distance Vector Routing (AODV)
• Dynamic Source Routing (DSR)
Geographische Routingprotokolle
DSR route discovery procedure
Search for route from 1 to 5
1
7
6
5 4 3
2
[1]
[1] 1
7
6
5 4 3
2
[1,7]
[1,7]
[1,4]
1
7
5 4 3
2 [1,7,2]
[1,4,6]
1
7
6
5 4 3
2
Übersicht
Untersuchte Netzstruktur und Problemstellungen
Topologie-basierte Routingprotokolle
Geographische Routingprotokolle
• Greedy-Routing und Planar-Graph-Routing
• Konstruktion von planaren Graphen
• Lokales Multicasting
• Beispiel MSTEAM
Localized Geographic Unicast Forwarding
Assumptions:
Localization system
Nodes know position of
• Themselves
• Their neighbors
• The destination source node
destination node
Geographic Greedy Routing
T S
A
(a)
F B
D C
E
Strategy: select from nodes closer to the destination the one which minimizes a local cost metric
B
E T S
(b)
?
A
C
D F
G
Problem: greedy routing failure
Recovery based on Planar-Graph Routing
source node
destination node
Planar Graph Routing Example
T S
P
F
Planar Graph Routing Example
T S
Q
F
P
Planar Graph Routing Example
T S
F
P
Planar Graph Routing Example
T S
P
F
Übersicht
Untersuchte Netzstruktur und Problemstellungen
Topologie-basierte Routingprotokolle
Geographische Routingprotokolle
• Greedy-Routing und Planar-Graph-Routing
• Konstruktion von planaren Graphen
• Lokales Multicasting
• Beispiel MSTEAM
We need a Planar Graph
U V U V
Gabriel Graph (GG) Relative Neighborhood Graph (RNG)
W
U
V
Delaunay
Triangulation (DT)
We need a UDG or QUDG
UDG: Localized GG and RNG versions based on 1-hop neighbors
UDG: Localized DT version based on 2-hop neighbors (and less) Quasi unit disk graph (QUDG)
U V
Unit disk graph (UDG)
rmin rmax
U
Problems and Limitations
Locally constructing a planar graph in arbitrary networks is impossible
Even worse: localized unicast routing is impossible in arbitrary graphs
Localized single path algorithms deviation from shortest paths
• Let k be the hop/Euclidean length of the shortest path connecting s and t
• Localized single path algorithms may produce paths of length O(k2)
• Some even worse but some exist which are upper bounded by O(k2) u
x v
y
t s
Localized Unicast Routing in Practice!
Wireless network graph has structure!
Aim at localized unicast approaches with high delivery rate
arbitrary graph wireless network graph
Geographic Clustering
Geographic Clustering
Geographic Clustering
Geographic Clustering
K-Hop Clustering
K-Hop Clustering
K-Hop Clustering
K-Hop Clustering
Übersicht
Untersuchte Netzstruktur und Problemstellungen
Topologie-basierte Routingprotokolle
Geographische Routingprotokolle
• Greedy-Routing und Planar-Graph-Routing
• Konstruktion von planaren Graphen
• Lokales Multicasting
• Beispiel MSTEAM
Localized Multicast Forwarding Problem
Assumptions:
Location system
Nodes know position of
• Themselves
• Their neighbors source node
destination node destination node
destination node
Building Blocks
T1
T3
T2 S
B A
D C
Building Blocks – Message Split
T1
T3
T2 S
B A
D C
Building Blocks – Next Hop Selection
T1
T3
T2 S
B A
D C
?
Building Blocks – Recovery
T1
T3
T2 S
B A
D C
?
?
Übersicht
Untersuchte Netzstruktur und Problemstellungen
Topologie-basierte Routingprotokolle
Geographische Routingprotokolle
• Greedy-Routing und Planar-Graph-Routing
• Konstruktion von planaren Graphen
• Lokales Multicasting
• Beispiel MSTEAM
EMST Backbone Assisted Localized Routing
T9
T7
T6
T1
T3 S
T8
T5
T2 T1,…,T9
EMST Backbone Assisted Localized Routing
T8 T9
T7
T6
T5
T1
T2
T3 S
EMST(S,T1,…,T9)
EMST Backbone Assisted Localized Routing
T8 T9
T7
T6
T5
T1
T2
T3
D1
D2 D3
S
EMST Backbone Assisted Localized Routing
T8 T9
T7
T6
T5
T1
T2
T3 A
B
C
S
T7,T8,T9
T1,T2,T3 T4,T5,T6
The Cost over Progress Framework
T3
T1
W V
T2 S
Which one is the better next hop node?
T1,T2,T3
The Cost over Progress Framework
Approximate expected number of hops H(S,V)
H(S,V) |EMST(S,T1,T2,T3)| / (|EMST(S,T1,T2,T3)| - |EMST(V,T1,T2,T3)|)
Approximate expected cost C(S,V) = cost(S,V) * H(S,V)
T3
T1
W V
T2 S
MSTEAM & MFACE
S T6
T5
T4
T1
T2
F1
F2
MSTEAM & MFACE
S T6
T5
T4
T1
T2
F1
F2
MSTEAM & MFACE
S
U
V W
F1 F2
F3
T1
T2 T3
MSTEAM & MFACE
S
U
V W
F1 F2
F3
T1
T2 T3
MSTEAM & MFACE
S
U
V W
F1 F2
F3
T1
T2 T3
MSTEAM & MFACE
S
U
V W
F1 F2
F3
T1
T2 T3 p
MSTEAM & MFACE
S
U
V W
F1 F2
F3
T1
T2
MSTEAM & MFACE
S
U
V W
F1 F2
F3
T2
Zusammenfassung
Untersuchte Netzstruktur und Problemstellungen
Topologie-basierte Routingprotokolle
Geographische Routingprotokolle
Zusammenfassung
Wir betrachteten hier: drahtlose Vernetzung ohne aufwendige (und kostenpflichtige) Infrastruktur
Abdeckung größerer Gebiete trotz limitierter Kommunikationsreichweite Multihop-Kommunikation
Wir haben es hier somit hauptsächlich mit einem Netzwerkproblem zu tun
Wesentliche Probleme: Routing und Topologiekontrolle
Anpassung traditioneller Routing-Verfahren: Topologie-basiertes Routing
Neuer Routing-Ansatz auf der Basis von Knotenkoordinaten
Dieser Ansatz erlaubt ganz neue Formen der Datenkommunikation und generell ganz neue Formen von Netzorganisation
Generelles Paradigma, um mit der Dynamik solcher infrastrukturlosen Multihop- Netze umzugehen: lokale Algorithmen/Verfahren
Dieses Paradigma ist auch zur Beherrschung von komplexen und dynamischen Internet-Overlay-Topologien anwendbar
Mit den hier behandelten lokalen Verfahren wurde nur ein kleiner Ausschnitt eines interessanten Forschungsfeldes betrachtet