Local Data Communication

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Local Network Structures

Local Data Communication

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MOTIVATION

Anwendung von schnittfeien Teilgraphen zur lokalen Lösung von netzwerkweiten Aufgaben

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Beispiele und ausgewählte Arbeiten (1)

 Unicast

[1] P. Bose, P. Morin, I. Stojmenovic, and J. Urrutia, “Routing with Guaranteed Delivery in Ad Hoc Wireless Networks,”Wireless Networks, vol. 7, no. 6, pp. 609–

616, nov 2001.

[2] B. Karp and H. T. Kung, “Gpsr: Greedy perimeter stateless routingfor wireless networks,” in Proceedings of the 6th Annual International Conference on Mobile Computing and Networking, 2000, pp. 243–254.

[3] F. Kuhn, R. Wattenhofer, and A. Zollinger, “An algorithmic approach to

geographic routing in ad hoc and sensor networks,” IEEE/ACM Transactions on Networking, vol. 16, no. 1, pp. 51–62, Feb 2008.

 Multicast

[4] H. Frey, F. Ingelrest, and D. Simplot-Ryl, “Localized minimum spanning tree based multicast routing with energy-efficient guaranteed delivery in ad hoc and sensor networks,” in 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks, June 2008, pp.1–8.

[5] J. A. Sanchez, P. M. Ruiz, J. Liu, and I. Stojmenovic, “Bandwidth-Efficient Geographic Multicast Routing Protocol for Wireless Sensor Networks,” IEEE Sensors Journal, vol. 7, no. 5, pp. 627–636, may 2007.

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Beispiele und ausgewählte Arbeiten (2)

 Geocast

[6] I. Stojmenovic, “Geocasting with guaranteed delivery in sensor net-works,” IEEE Wireless Communications, vol. 11, no. 6, pp. 29–37, Dec 2004.

 Anycast

[7] N. Mitton, D. Simplot-Ryl, and I. Stojmenovic, “Guaranteed delivery

forgeographical anycasting in wireless multi-sink sensor and sensor-actornetworks,”

in IEEE INFOCOM 2009, April 2009, pp. 2691–2695.

 Mobicast

[8] Q. Huang, C. Lu, and G. C. Roman, “Reliable mobicast via face-aware routing,” in IEEE INFOCOM 2004, vol. 3, March 2004, pp. 2108–2118 vol.3.

 Broadcast

[9] M. Seddigh, J. S. Gonzalez, and I. Stojmenovic, “RNG and internal node based broadcasting algorithms for wireless one-to-one networks,” SIGMOBILE Mobile Computing and Communications Review, vol. 5,no. 2, pp. 37–44, Apr. 2001.

[10] I. Stojmenovic, M. Seddigh, and J. Zunic, “Dominating Sets and Neighbor Elimination-Based Broadcasting Algorithms in Wireless Networks,” IEEE

Transactions on Parallel and Distributed Systems, vol. 13, no. 1,pp. 14–25, 2002.

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Beispiele und ausgewählte Arbeiten (3)

 Void- und Boundary-Detection

[11] Q. Fang, J. Gao, and L. J. Guibas, “Locating and bypassing routing holes in sensor networks,” in IEEE INFOCOM 2004, vol. 4, March 2004, pp.2458–2468 vol.

4.

 Distributed Data-Storage

[12] S. Rathnasamy, B. Krap, S. Shenker, D. Estrin, R. Govindan, L. Yin, and F. Yu,

“Data-centric storage in sensornets with GHT, a geographic hashtable,” Mobile Networks and Applications, vol. 8, no. 4, pp. 427–442,Aug 2003.

[13] Y. Deng and I. Stojmenovic, “Partial delaunay triangulations based data-centric storage and routing with guaranteed delivery in wireless ad hoc and sensor

networks,” in 2009 Mexican International Conference on Computer Science, Sept 2009, pp. 24–32

.

 Mobile-Object tracking

[14] H.-W. Tsai, C.-P. Chu, and T.-S. Chen, “Mobile object tracking in wireless sensor networks,” Computer Communications, vol. 30, no. 8,pp. 1811–1825, Jun.

2007.

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Beispiele und ausgewählte Arbeiten (4)

 Lokale Adress-Autokonfiguration

[15] X. Li, Y. Deng, V. Narasimhan, A. Nayak, and I. Stojmenovic, “Localized address auto configuration in wireless ad hoc networks,” in2010 International

Conference on Wireless Communications Signal Processing (WCSP), Oct 2010, pp.

1–6.

 Koordination von mobilen Sensoren

[16] J. Tan, A Scalable Graph Model and Coordination Algorithms for Mobile Sensor Networks. Boston, MA: Springer US, 2008, pp. 65–83.

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We consider exemplarily Unicast and Multicast

Ad-Hoc Routing Protocols

Proactive

Topology-based Geographic

Reactive Basic Greedy

Partial Flooding DFS-based

Stateless

Energy aware Remark 1: Topology control is typically

achieved by a localized algorithm.

Remark 2: Topology-based routing will be covered in the lecture DraKo

(Drahtlose Kommunikation)

non-localized localized

7 A Classification of Wireless Network Routing in general

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Discussion

 However correctness of localized routing strategies requires some structuring of the underlying network.

• There exists no local Routing algorithm which works for any underlying connected graph.

• See Durocher, S., Kirkpatrick, D., & Narayanan, L. (2008). On Routing with Guaranteed Delivery in Three-Dimensional Ad Hoc Wireless

Networks. In Proceedings of the Ninth International Conference on Distributed Computing and Networking (ICDCN 2008) (pp. 546–557).

 A sufficient condition for correctness of some local routing strategies is exactly that the underlying graph has no intersecting links

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GEOGRAPHISCHES UNICAST- FORWARDING

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10 Localized Geographic Unicast Forwarding

Assumptions:

 Localization system

 Nodes know position of

• Themselves

• Their neighbors

• The destination source node

destination node

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Data Communication

Localized Geographic Greedy Packet Forwarding

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Localized Geographic Routing

 Determine own location

 Acquire destination’s location

• Unicast and Multicast

• Geocast

• Anycast

 Routing message

• Constant Size

• Stores destination position

 Localized forwarding decision

Destination

Source

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Greedy Packet Forwarding

 Select neighbor with the “best” location regarding the metric being optimized

 Each node applies this greedy principle until destination is eventually reached

T S

A B

F

D C

E

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Basic Single-Path Strategies

 Produce nearly the same path

 If successful performance close to SP

 Delivery rate decreases significantly in sparse networks

MFR GREEDY

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Basic Single Path Strategies

 Rationale: try to minimize Euclidean path length a packet has to travel DIR

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Loop-Freedom of Greedy Routing

 The discussed forwarding based on distance and progress consider nodes in forward direction only to provide loop-free operation (see Fig. (a))

 Direction-based strategies do not guarantee loop-free operation (see Fig. (b))

S

A B

D

(a) (b)

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Greedy Routing Failure

 Choosing node in backward direction may lead to packet loops

 Nevertheless, there may exist a path from S to D (S may also be an intermediate node)

 Loop-freedom and delivery rate are conflicting goals

 Solutions?

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Motivation

 Many greedy routing schemes perform well in dense networks

 Greedy routing has a small communication overhead

 Desirable to run greedy routing as long as possible

 However, greedy routing might fail in sparse networks

 Guaranteed delivery is a desirable property as well

 In case of failure

• run a recovery mechanism which requires memorizing past routing information

• in the message

• in the visited node

• run a stateless recovery mechanism

• does such strategy exist at all??

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MEMORYLESS MESSAGE DELIVERY WITH

GUARANTEED DELIVERY?

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44 Recovery based on Planar-Graph Routing

source node

destination node

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45 Planar Graph Routing Example

T S

P

F

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46 Planar Graph Routing Example

T S

Q

F

P

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47 Planar Graph Routing Example

T S

F

P

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48 Planar Graph Routing Example

T S

P

F

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Data Communication

Localized Geographic Multicasting

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69 EMST Backbone Assisted Localized Routing

T9

T7

T6

T4

T1

T3 S

T8

T5

T2

T1,…,T9

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70 EMST Backbone Assisted Localized Routing

T8 T9

T7

T6

T5

T4

T1

T2

T3 S

EMST(S,T1,…,T9)

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71 EMST Backbone Assisted Localized Routing

T8 T9

T7

T6

T5

T4

T1

T2

T3

D1

D2 D3

S

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72 EMST Backbone Assisted Localized Routing

T8 T9

T7

T6

T5

T4

T1

T2

T3 A

B

C

S

T7,T8,T9

T1,T2,T3

80 MSTEAM & MFACE

S

U

V W

F1 F2

F3

T1

T2

T3

p

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81 MSTEAM & MFACE

S

U

V W

F1 F2

F3

T1

T2

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82 MSTEAM & MFACE

S

U

V W

F1 F2

F3

T2

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Summary

 We considered here: wireless networking without complex infrastructure

 Coverage of larger areas and limited communication range

 Multi-hop communication

 So we're mainly dealing with a network problem

 Major problems: routing and topology control

 Adaptation of traditional routing procedures: topology-based routing

 New routing approach based on node coordinates

 This approach allows completely new forms of data communication and generally completely new forms of network organization

 General paradigm to deal with the dynamics of such multihop networks without infrastructure: local algorithms / procedures

 (This paradigm can also be used to master complex and dynamic Internet overlay topologies)

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Summary

 We considered construction of intersection free graphs as one important feature

 In addition to that, other graph related problems can be studied

• Maximal Connected Dominating Sets

• Maximal Independent Sets

• Clustering

• Spectral Graph theory (e.g. for Consensus)

86 Thank you for your interest!

If you like graphs and algorithms – and the principle idea of localized algorithm design – joint the AG UniKoRN. We have interesting master and bachelor