an and d Im Impl plementa ementation tion (01 0120 20442 - - PowerPoint PPT Presentation

Net etwork work Ke Kerne nel l Ar Archi chitect tectures ures an and d Im Impl plementa ementation tion (01 0120 20442 4423) ) Ro Routing uting

Chaiporn Jaikaeo chaiporn.j@ku.ac.th Department of Computer Engineering Kasetsart University

Materials taken from lecture slides by Karl and Willig

2

Ov Overv rvie iew



Uni nicast ast rout utin ing g in in MA MANETs NETs



Energy efficiency & unicast routing



Multi-/broadcast routing



Geographical routing

3

Un Unic icast, ast, ID ID-Cent ntric ric Ro Routing uting



Given: a network/a graph

• Each node has a unique identifier (ID)



Goal: Send a packet from one node to another

• The routing & forwarding problem
• Routing:

ing: Construct a table telling how can reach a given destination

• Fo

Forw rwardi rding: ng: Consult this table to forward a given packet to its next hop



Challenges

4

Cha hallen llenges ges in in WS WSNs Ns/MANETs MANETs



Nodes may move around, neighborhood relations change



Optimization metrics may be more complicated

• Not just “smallest hop count”

A B C

5

Ad ho Ad hoc c Ro Routing uting Pro rotocols tocols



Because of challenges, standard routing approaches not really applicable

• Too big an overhead, too slow in reacting to

changes

• Examples: Dijkstra, Bellman-Ford



Simple solution: Flo loodin ing

• No routing table needed
• Packets are usually delivered to destination
• But: overhead is prohibitive
• Usually not acceptable in most cases

6

Go Gossiping siping



Needs no routing table

• Similar to flooding



Nodes forward packets with some probability



Haas et al. studies gossiping behavior and found that

• There is a critical probability, x
• p < x: gossip dies out very quickly
• p > x: gossip reaches most nodes

7

Ro Routing uting Pro rotocol tocol Cla lassif ification ication



Main question: Wh When does the routing protocol operate?



Option 1: Alw lways ays tries to keep routing data up-to-date

• Protocol is proa
• act

ctive ive / tabl ble-drive driven



Option 2: Route is only determined when actu tually ally ne needed

• Protocol operates on
• n demand

nd



Option 3: Combine these behaviors

• Hybr

brid protocols

8

Ro Routing uting Pro rotocol tocol Cla lassif ification ication



Which data is used to identify nodes?

• An arbitrary identifier?
• The pos
• sition
• n of a node?
• Can be used to assist in ge

geogr graphi hic c routing protocols

• Identifiers that are not arbitrary, but carry

some structure?

• As in traditional routing
• Structure akin to position, on a logical level?

9

Pro roactiv active e Pro rotocols tocols – Ex Exam ample ple



Fisheye State Routing (FSR)

• Basic observation: When destination is far

away, details about path are not relevant

• Look at the graph as if through a fisheye lens
• Regions of different accuracy of routing

information

• LS information about closer nodes is

exchanged more frequently

10

Re React active ive Pro rotocols tocols – Ex Exam ample ple



Recall reactive routing protocols

• Initially, no information about next hop is

available at all

• One possibility: Send packet to everyone
• ne
• Hope: At some point, packet will reach

destination and an answer is sent pack – use this answer for ba back ckward learni ning ng the route from destination to source



Examples

• Ad

Ad ho hoc O c On-dem emand and Distance nce Vect ctor

• r (AO

AODV)

• Dynamic

amic Sou

• urce

ce Rou

• uting (DSR)

11

DS DSR



Dynamic Source Routing protocol



Use separate rout ute requ quest st/rou route te reply ly packets to discover route

• Data packets only sent once route has been

established

• Discovery packets smaller than data packets



Store routing information in the discovery packets

12

DS DSR R Ro Rout ute e Di Disco covery very

Search for route from 1 to 5

1 7 6 5 3 4 2

[1] [1]

1 7 6 5 3 4 2

[1,7] [1,7] [1,4]

1 7 6 5 3 4 2

[1,7,2] [1,4,6] [1,7,3]

1 7 6 5 3 4 2

Node 5 uses route information recorded in RREQ to send back, via source routing, a route reply [5,3,7,1]

13

AOD AODV V



Ad hoc On-demand Distance Vector



Very popular routing protocol



Same basic idea as DSR for discovery procedure



Nodes maintain routing tables instead of source routing

14

Al Alte ternative rnative - Ru Rumo mor r Ro Routing uting



Think of an “agent” wandering through the network, looking for data/events

?



Agent initially perform random walk



Leave “traces” in the network



Later agents can use these traces to find data

15

Ov Overv rvie iew



Unicast routing in MANETs



En Energy gy effic icie ienc ncy y & uni unicast st rout uting ing



Multi-/broadcast routing



Geographical routing

16

En Energy rgy-Efficient Efficient Un Unic icast: ast: Go Goal als

C 1 4 A 2 G 3 D 4 H 4 F 2 E 2 B 1 1 1 2 2 2 2 2 3 3



Minimize energy/bit

• Eg., A-B-E-H



Maximize network "lifetime"

• Time until first

node failure

• loss of coverage
• partitioning

Example: Send data from node A to node H

17

Ba Basic ic opt ptio ions ns fo for path r path me metr trics ics



Max total available battery capacity

• Sum of batt. levels

without needless detours

• Example: A-C-F-H



Min battery cost

• Sum of reciprocal

battery levels

• Example: A-D-H



Min-Max batt. cost

• Largest reciprocal

level of all nodes in path



Minimize variance in power levels

C 1 4 A 2 G 3 D 4 H 4 F 2 E 2 B 1 1 1 2 2 2 2 2 3 3

18

Ov Overv rvie iew



Unicast routing in MANETs



Energy efficiency & unicast routing



Mul ulti ticast/ cast/broadcast broadcast rout utin ing



Geographical routing

19

Br Broadcas

• adcast

t & Mu & Mult lticas icast



Distribute a packet to all reachable nodes (br broadcas dcast) or to a subgroup (mul ulticast icast)



Basic options

• Source-based tree: one tree per source
• Minimize total cost
• Minimize maximum cost to each destination
• Shared, core-based trees
• Mesh
• Provides redundancy in data transfer

20

Go Goals als fo for So r Sourc urce-Based Based Tr Trees



For each source, minimize total al cost st

• The Steiner tree problem



For each source, minimize max axim imum um cost st to each destination

• Obtained by overlapping

the individu idual al shortest paths

Steiner tree Src Dest 1 Dest 2 2 2 1 Src Dest 1 Dest 2 2 2 1 Shortest-path tree

21

Br Broa

• adc

dcast/Multic ast/Multicast ast Cla lassification ssification

Broadcast Multicast Mesh Shared tree (core-based tree) Single core Multiple core One tree per source Minimize total cost (Steiner tree) Minimize cost to each node (e.g., Dijkstra)

22

Wi Wire reless less Mu Mult lticas icast t Adv Advan antag tage



Wires

• Locally distributing a packet to n neighbors
• n times the cost of a unicast packet



Wireless: sending to n neighbors can incur costs

= tx to a single neighbor – if receive costs are ignored = One tx, n rx – if receives are correctly tuned = send n unicasts – if multicast not supported by MAC



If local multicast is cheaper, then wireles ess mul ulticast cast advantage ntage is present

• Can be assumed realistically

23

Ste teine iner r Tr Tree App Appro roximations imations



Computing Steiner tree is NP complete



A simple approximation

• Pick some arbitrary order of all destination

nodes + source node

• Successively add these nodes to the tree
• For every next node, construct a shortest path to

some other node already on the tree

• Performs reasonably well in practice

24

Ste teine iner r Tr Tree App Appro roximations imations



Takahashi Matsuyama heuristic

• Similar, but let algorithm decide which is the

next node to be added

• Start with source node, add that destination

node to the tree which has shortest path

• Iterate, picking that destination node which

has the shortest path to some node already on the tree



Problem: Wireless multicast advantage not exploited!

• And does not really fit to the Steiner tree

formulation

25

Br Broadcas

• adcast

t In Incr creme mental ntal Powe wer



Or BIP



Exploits multicast wireless advantage

• Goal: use as little transmission power as

possible



Based on Prim's MST algorithm



Once a node transmits and reaches some neighbors, it becomes cheaper to reach additional neighbors

26

BI BIP – Ex Exam ample ple

S (3) A B C (1) D 2 3 6 7 Round 4: S (5) A B C (1) D 3 7 10 Round 5: S A B C D 1 5 3 7 3 1 10 Round 1: S (1) A B C D 4 3 7 2 1 9 Round 2: S (3) A B C D 2 3 7 1 7 Round 3:

27

Mu Multic lticast ast In Incr cremental mental Powe wer



Or MIP



Start with broadcast tree construction, then prune unnecessary edges out of the tree

S A B C D 3 7 10 S A B C D 3 7 10

28

Me Mesh-Based Based Mu Mult lticas icast



Example – ODMRP (On-Demand Multicast Routing Protocol)

F A B E D G H I

Sender NextHop H C Sender NextHop H D Sender NextHop H H

C

29

Ov Overv rvie iew



Unicast routing in MANETs



Energy efficiency & unicast routing



Multi-/broadcast routing



Geo eogr graph aphic ical al rou

• utin

ing

• Position-based routing
• Geocasting

30

Ge Geographic graphic Ro Rout uting ing



Implicitly infer routing information from physical placement of nodes

• E.g., position of current node, current neighbors,

destination known

• Send to a neighbor in the right direction as next hop
• Ge

Geogr graphic phic ro routing ng



Pos

• sitio

ion-bas based ed rou

• uting

 Use position information to aid in routing



Geoc

• cas

asting ting

 Send to any node in a given area

31

Ov Overv rvie iew



Unicast routing in MANETs



Energy efficiency & unicast routing



Multi-/broadcast routing



Geo eogr graph aphic ical al rou

• utin

ing

• Pos
• sitio

ion-bas based ed rou

• uting
• Geocasting

32

Position sition-Based Based Ro Rout uting ing



“Most forward within range r” strategy

• Send to that neighbor that

realizes the most forward progress towards destination



Nearest node with forward progress

• Idea: Minimize transmission power



Directional routing

• Choose next hop that is angularly closest to

destination

• Choose next hop that is closest to the connecting line

to destination

• Problem: Might result in loops!

33

Pro roblem: blem: De Dead ad En Ends ds



Simple strategies might send a packet into a dead end

34

Ri Right ght Han Hand d Ru Rule le



Basic idea to get out of a dead end: Put right hand to the wall, follow the wall

• Does not work if on some inner wall – will walk

in circles

• Need some additional rules to detect such

circles

35

Ri Right ght Han Hand d Ru Rule le – GP GPSR R



Greedy edy Pe Perim imete eter r Statel teless ss Rout utin ing

• Use greedy, “most forward” routing as long as

possible

• If no progress possible: Switch to “face” routing
• Face: largest possible region of the plane that is not

cut by any edge of the graph

• Send packet around the face using right-hand rule
• Use position where face was entered and

destination position to determine when face can be left again, switch back to greedy routing

• Requires: planar graph! (topology control can

ensure that)

36

Fac Face Ro Routing uting Ex Exam ample ple

37

GP GPSR R – Ex Exam ample ple



Route packet from node A to node Z

A Z D C B E F G I H J K L

Enter face routing Enter next face

38

Ov Overv rvie iew



Unicast routing in MANETs



Energy efficiency & unicast routing



Multi-/broadcast routing



Geo eogr graph aphic ical al rou

• utin

ing

• Position-based routing
• Geoc
• cas

asting ting

39

Lo Locat cation ion-base based d Mu Mult lticas icast t (LB (LBM) M)



Geocasting by geographically restricted flooding



Define a “forwarding” zone – nodes in this zone will forward the packet to make it reach the destination zone



Packet is always forwarded by nodes within the destination zone itself

40

De Dete termining rmining Ne Next t Ho Hops ps



Use Voronoi diagram

S A B C D Destination Zone

41

De Dete termining rmining Ne Next t Ho Hops ps



Use convex hulls

S A B C E Destination Zone D

42

Conclusion nclusion



Routing exploit various sources of information to find destination of a packet



Routing can make some difference for network lifetime



Non-standard routing tasks (multicasting, geocasting) require adapted protocols