1

Complex network

Speaker: Ao Weng ChonAdvisor: Kwang-Cheng Chen

2

Outline Interference control Epidemics Bio-inspired networking

Particle Swarm Optimization Ant Colony Optimization

Further directions Reference

3

Interference control

Coexistence of primary users and secondary users

4

Interference control

SUs should defer their transmission activities when located in the inference ranges of PUs.

5

Interference control

When the deferred SUs acted as cooperative relays, they facilitate PUs transmissions, reduce the interference ranges of PUs and expose extra spectrum opportunities.

6

Interference control

Cooperative relays: Energy efficient 2 2 2

1 2d d d

7

Interference control

A way to capture interference range

8

Interference control

Interference range reduces after cooperation

9

Interference control

The necessary condition of existence of an infinite connected component in the SUs is the interference balls of PUs (wall width is rp) do not form an infinite connected component

2

1

I

PS r

10

Epidemics

Internet

Suspect UE

Suspect UE

Suspect UE

BT virus

BT virus

SMS virus

Infected UE

11

Epidemics

I

S

S

S

S

S

S

S

S

S

S

SS

S

S

S

S

S

Random Geometric Graph

E-R Model

12

Epidemics

The one hop BT motif can be replaced by a complete graph with 4 or more vertices

13

Epidemics

Epidemic is possible when TC satisfies

2 2

2

( 1) ( )( 1) ( )

( )( )

2 (1 ) 0

SMS SMS BT SMSSMS SMS

SMS BT BT BTBT BT

SMS SMS SMS SMSSMS

SMS SMSBT

BT

C Cn t n tC Cn t n t

k k k kT T n tk k

n tT T T P

1det 0

1SMS SMS BT SMS

SMS BT BT BT

C CC C

14

Bio-inspired networking Biomimicry: studies designs and processes in

nature and then mimics them in order to solve human problems

A number of principles and mechanisms in large scale biological systems Self-organization: Patterns emerge, regulated by

feedback loops, without existence of leader Autonomous actions based on local

information/interaction: Distributed computing with simple rule of thumb

Birth and death as expected events: Systems equip with self-regulation

Natural selection and evolution Optimal solution in some sense

15

Particle Swarm Optimization

16

Particle Swarm Optimization

17

Ant Colony Optimization Interaction between ants is built on trail

pheromone Behaviors:

Lay pheromone in both directions between food source and nest

Amount of pheromone when go back to nest is according to richness of food source (explore richest resource)

Pheromone intensity decreases over time due to evaporation

18

Others Network resilience Search in social network Evolutionary game

19

Further directions Economorphic Networking

Competition in Communication Networks Nodes can be viewed as economic agents, each

seeking to maximize its own utility (e.g., energy/spectral efficiency): Non-cooperative games: nodes compete for radio

resources Auctions: nodes bid for network resources Coalition games: incentives to nodes for good behavior

This view provides new understanding of network behavior, new design tools, and is based on individualized node behavior

20

Further directions Sociomorphic Networking

Collaboration in Networks Network nodes work together

Collaboration: nodes work together for a common goal Cooperation: nodes help each other to achieve

individual goals This view provides

new algorithms, new protocols, and is based on collective behavior of nodes

21

Further directions Bio-inspired networking

Devices are mobile and autonomous, and must adapt to the surrounding environment in a distributed way.

To discover and adapt biological methods to technical solutions that are showing similarly high stability, adaptability, and scalability as biological entities often have.

22

References [1] Newman, M. E. J., Random graphs with Clustering, Phys. Rev. L 103, 058701 (2009) [2] Joel C. Miller, Percolation in clustered networks, Arxiv preprint arXiv:0904.3253v2, 2009. [3] W. Ren, Q. Zhao, and A.Swami, “Connectivity of Heterogeneous Wireless Networks”, Arxiv preprint

arXiv:0903.1684v5, 2009. [4] Vince Poor, Lecture presented in First School of Information Theory, State Collega, PA, June 5, 2008.