Organic Sensor Networks

Jakob Salzmann, Ralf Behnke, Dirk Timmermann

SPP 1183 9th Colloquium Organic Computing

20.-21.09.2009, Augsburg

Institute of Applied Microelectronicsand Computer Engineering

University of Rostock

DFG 1183 Organic Computing 2

Outline

• Project Overview

• Clustering Algorithms– Localization-based algorithms– Localization-free algorithms

• Routing Algorithms– Scale-free inspired routing– Anticipatory routing

• Conclusion

DFG 1183 Organic Computing 3

Task:• Collect sensor data at

many locations

• Transmit collected data to sink

Scenarios:

Sensor Network

Network properties:

Node properties:

DFG 1183 Organic Computing 4

Typical problems:

• Limited energy

• Missing global information

• Dynamic events impact network

structure

Project Overview

Overall goal: Increase lifetime and robustnessof sensor networks by using OC

Resulting properties:

• Centralized control infeasible

• Required self-organization

• Required energy awareness

5

ProjectOverview

Erroneous nodedetectionErroneous nodedetection

ClusteringClustering

RoutingRouting

Deployed Sensor NetworkDeployed Sensor Network

• Establish connection tothe sink• Healing of failed links

• Hierarchic layer• Redundancy detection• Healing of failed nodes

• Reduced communication• Altruism of nodes withdefect senors

DFG 1183 Organic Computing 6

Outline

• Project Overview

• Clustering Algorithms– Localization-based algorithms– Localization-free algorithms

• Routing Algorithms– Scale-free inspired routing – Anticipatory routing

• Conclusion

Switched-off node

sor node Clusterhead

al XGAF cell

• Subdivision into square cells

• Dimension of cells guarantees

coverage of a cell by each of its

nodes

• Cluster emergence in each cell

• Possibility to save energy by

switching-off all nodes but one

per cell

GAF* [Sal07a]

• Subdivision into square cells

• Reduced cell dimension

guarantees partial coverage of

adjacent cells

• Possibility to save energy by

switching-off half of all cells

• Clustering behavior like XGAF

• Simple self-healing algorithm

available

MASCLE* [Sal07d]

ched-off node

or node

terhead

Virtual 2-MASCLE cell

Switched-off cell

MASCLE* [Sal09a]• Subdivision into square cells

• Further reduction of cell size leads to

increased covered area

• Possibility to save energy by

switching-off three quarter of all cells

• Clustering behavior like XGAF

• Complex energy aware

self-healing algorithm available

ed-off node

node

rhead

Virtual 4-MASCLE cell

Switched-off cell

Evaluation Active nodes

DFG 1183 Organic Computing 10

Simulation environment:Area to observe: 1km² , working range: 56 m, 500 simulations Deployed Nodes: 10000

XGAF

2-MASCLE

4-MASCLE

All nodes active

Evaluation Lifetime

DFG 1183 Organic Computing 11

Simulation environment:Area to observe: 1km² , working range: 56 m, 500 simulations Deployed Nodes: 10000

XGAF

2-MASCLE

4-MASCLE

All nodes active

DFG 1183 Organic Computing 12

Outline

• Project Overview

• Clustering Algorithms– Localization-based algorithms– Localization-free algorithms

• Routing Algorithms– Scale-free inspired routing – Anticipatory routing

• Conclusion

Free-GAF* [Sal08a]

*Localization Free - Geographic Adaptive Fidelity 13

• Cluster determination via broadcast

with reduced transmission range

• Detection of adjacent clusterhead

via broadcast

• Refinement of clusterhead choice

via broadcast of cluster members

• New clusterhead repeats procedure

• Cluster emergence in the whole

network

• Clustering behavior like XGAF

Switched-off node

Sensor node

Possible Clusterhead(High probability)

Clusterhead

Possible Clusterhead(Low probability)

Free-CLASH* [Sal09c]

*Localization Free – Clustering with Approximation to Symmetric Hexagons 14

• Cluster emergence similar to

Free-GAF

• Start with 2 clusterheads

• Only nodes with two neighbour cluster

become possible clusterheads

• Approximation to (regular) hexagon

structure

• Improved coverage and regularity

• Clustering behavior like XGAF

Switched-off node

Sensor node

Possible Clusterhead

Clusterhead

aluation tive nodesation environment:o observe: 0.1km² , working range: 56 m, 500 simulations

Better:Better:

aluation hieved functionalityation environment:o observe: 0.1km² , working range: 56 m, 500 simulations

Better:Better:

DFG 1183 Organic Computing 17

Outline

• Project Overview

• Clustering Algorithms– Localization-based algorithms– Localization-free algorithms

• Routing Algorithms– Scale-free inspired routing– Anticipatory routing

• Conclusion

Scale-Free inspired Routing

18

• Network results from preferred connection

• High robustness againstrandom failures

Vizualisation of the internet [Barabási04]

Scale-Free inspired Routing [Sal07a]

19

Sensor node

Sink

Clusterhead

Switched-off node

• Emerging of clusters with different lifetimes

• Routing approach:• Starting with the sink• After attending the network,

nodes connect with all unconnected nodes in range

• Establish a network with scale-free similar behavior

• Optimizations:• Range Reduction• Limited Connectivity• Wait and See

• Well populated clusters become hubs

Lowly populated Cluster

Well populated Cluster

Evaluation Lifetime

DFG 1183 Organic Computing 20

• Lifetime balancing • Lifetime increase by 130%

Lifetime/ shortestlifetime of a onenode cell [%]

Average lifetimewithout energy-awareness

Average lifetimewith appliedoptimizations

DFG 1183 Organic Computing 21

Outline

• Project Overview

• Clustering Algorithms– Localization-based algorithms– Localization-free algorithms

• Routing Algorithms– Scale-free inspired routing, – Anticipatory routing

• Conclusion

rrent work – Anticipatory Routing [Sal09b]pletion of the 2. Period)

• After node loss via dynamic event, unconnected nodes

choose new routing path autonomously

• Afterwards, adjacent routing path structure changes

• Affected routing path is balanced

Advantages:

• Less probability of further failures (in the same region)

• Increased network lifetime

• Combination with Scale-free inspired routing

Challenges

F i l ti f ti l d

node

ode

d route

hed connection

tline

roject Overview

lustering Algorithms– Localization-based algorithms– Localization-free algorithms

Routing Algorithms– Scale-free inspired routing, – Anticipatory routing

onclusion

nclusion

uccessful development of self-organized energy-aware algorithms– Localization-based algortihms– Localization-free algorithms

gorithms base on each other– Extendable via cluster-based self-healing algorithms– Scale-free inspired routing utilizes emerged cluster structure

elf-Healing in three hierarchic layers– Intra-Cluster, Inter-Cluster, Routing layer

4 international and national publications (2 more planned)

blications

l09c] Jakob Salzmann, Ralf Behnke, Jiaxi You, Dirk Timmermann:

e-CLASH – Improved Localization Free Clustering in Large Wireless Sensor Networkse International Workshop on Scalable Ad Hoc and Sensor Networks, St. Petersburg, Deutschland, Oktober 2009

l09b]Jakob Salzmann, Ralf Behnke, Dirk Timmermann:

ticipatory Route Change Algorithm for Robust Self-Organized Sensor NetworksInternational Forum Life Science Automation, Rostock, Deutschland, Oktober 2009

l09a] Jakob Salzmann, Ralf Behnke, Martin Gag, Dirk Timmermann:

MASCLE - Improved Coverage Aware Clustering with Self Healing Abilitiese International Symposium on Multidisciplinary Autonomous Networks and Systems (MANS 2009), pp. 537-543, ISBN: 978-0-

95-3737-5/09, Brisbane, Australien, Juli 2009

u09b] Jiaxi You, Dominik Lieckfeldt, Qi Han, Jakob Salzmann, Dirk Timmermann:

ok-ahead Geographic Routing for Sensor NetworksIEEE International Workshop on Sensor Networks and Systems for Pervasive Computing (PerSeNS 2009), ISBN: 978-1-4244-

04-9, Galveston, Texas, USA, März 2009

h09] Ralf Behnke, Jakob Salzmann, Dominik Lieckfeldt, Frank Golatowski, Dirk Timmermann, Kerstin Thurow:

blications

u09a] J. You, D. Lieckfeldt, J. Salzmann, D. Timmermann,

F&Co: Connectivity Aware Topology Management for Sensor Networks, 20th IEE International Symposium on Personal,

oor and Mobile Radio Communications, Tokyo, Japan, 2009

r09] Claas Cornelius, Frank Sill, Hagen Sämrow, Jakob Salzmann, Dirk Timmermann, Diógenes da Silva:

countering gate oxide breakdown with shadow transistors to increase reliabilityt Symposium on Integrated Circuits and Systems Design (SBCCI), S. 111-116, ISBN: 978-1-60558-231-3, Gramado, Brasilien,

ptember 2008

l08b] Jakob Salzmann, Ralf Behnke, Dirk Timmermann:

ocalization-Free Wireless Sensor Network Clustering Approach with Convergence to Uniformityernational Forum Life Science Automation, p. 81, ISBN: 978-3-938042-17-5, Rostock, Deutschland, September 2008

l08a] Jakob Salzmann, Ralf Behnke, Dirk Timmermann:

Self-Organized Localization-Free Clustering Approach for Redundancy Exploitation in Large Wireless Sensor NetworksJahrestagung, Workshop: Adaptive und organische Systeme, pp. 747-754, ISBN: 978-3-88579-228-4, München, Deutschland,

ptember 2008

blications

l07c] Jakob Salzmann, Ralf Behnke, Dirk Timmermann:

alyse regelmäßiger Clusterformen in SensornetzwerkenSymposium Maritime Elektrotechnik, Elektronik und Informationstechnik, S. 375 - 380, Rostock, Deutschland, Oktober 2007

l07b] Jakob Salzmann, Ralf Behnke, Dirk Timmermann:

ographical Clustering with Coars-Grained LocalizationInternational Forum ''Life Science Automation'', ISBN: 978-3-938042-12-0, Landsdowne, Virginia, USA, Oktober 2007

l07a] Jakob Salzmann, Stephan Kubisch, Frank Reichenbach, Dirk Timmermann:

ergy and Coverage Aware Routing Algorithm in Self Organized Sensor Networksceedings of Fourth International Conference on Networked Sensing Systems, pp. 77-80, ISBN: 1-4244-1231-5, Braunschweig,

utschland, Juni 2007

i06] Frank Reichenbach, Andreas Bobek, Philipp Hagen, Dirk Timmermann:

reasing Lifetime of Wireless Sensor Networks with Energy-Aware Role-ChangingProceedings of the 2nd IEEE International Workshop on Self-Managed Networks, Systems & Services (SelfMan 2006), LNCS

96, pp. 157-170, ISBN: 978-3-540-34739-2, Dublin, Ireland, Juni 2006

estions?

ckup

lf-Organized Role Changingei06]

Sink initiated role changing

• Sink polls each node periodically

• Sink assigns new roles to sensor nodes

Self-organized role changing

• If energy level of a node drops below a

certain value node informs its

clusterhead autonomously

• Clusterhead assigns new roles to

remaining energy rich nodes

aluation

Self-organized role changingSink initiated role changing

al Problems:

mited energy

ssing global information

namic events impact network

ucture

ntralized control infeasible

quired self-organization

quired energy awareness

ject Overview

Overall goal: Increase lifetime and robustness ofsensor networks by using OC

Phase 1:

Research of applicableOC principles for sensor networks

Research of self-organizedcommunication

Phase 2:

Utilization of OC principles foremergence of network structures

Utilization of OC principles toh dl d i t

tlook (3. Project Phase)

ttacks on self-organized networks– Analyzing the efficiency of different attack scenarios– Develop threat which exploit the self-organizing behavior

elf-protecting sensor networks– Research of possibilities of attack detection– Energy-aware attack reaction

tlook (3. Project Phase)

Organic adaptation to real world challenges– Realistic channel model

• Shadowing• Reflection• Fading

– Multiple medium access• Overhearing• Idle Listening• Unsynchronized clocks

– Range-based clustering ► Connectivity-based clustering– Utilization of mass of nodes

• Utilization of birthday paradoxon