Attention to self-organization
Paradigm shift of control process

Differences in Robustness of Self-OrganizedControl and Centralized Control in Sensor Networks
Caused by Differences in Control Dependence
Masashi Sugano(Osaka Prefecture University)
Yuichi Kiri , Masayuki Murata(Osaka University)

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Distributed
Control

Simplicity
Effectiveness
Determinism

Adaptability
Scalability
Robustness

Self-organized
control

Self-organization
Is “emergence of system-wide adaptive structure andfunctionality from simple local interactions between individualentities” [Prehofer and Bettstetter, 2005]
Attracts considerable attention from the view point of theapplicability to sensor networks
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CentralizedControl

Motivations

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What is WSN
Wireless Sensor Network (WSN)

Robustness
Is “a property that allows a system to maintain its functions despite
external and internal perturbations”
Is extremely important especially for networks in variable environment

Composed of a number of sensor nodes
Have miniature sensing devices
Ex., Moisture, temperature, acceleration
Communicate with neighboring nodes via wireless channel
Sense their ambient surroundings
Send the data to a sink

Good robustness of self-organized control is widely reported but:
This is certainly nontrivial
Why self-organized control is robust?
What factors yield robustness?

Compare robustness of self-organized control and centralized control
Using sensor network scenario
Quantitatively demonstrate the advantage of robustness
Yield insight why and how self-organized control achieve good robustness

Collect data over a large area
Sensor nodes

Perturbations WSN faces

Data serverTransmission error
Sensor node failures

Sinks

Monitoring region
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Robustness in sensor network

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Cluster-based approach

Property which allows a system to maintain its functionality despite
perturbations

Robustness in sensor networks
Packet loss, link disconnection, node & sink failure
Sensor network
Data collection

Not robustTime
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Control station manages network

clustersinknodes

Gather and integrate control information from each node
Positions, residual power, etc. of nodes.
Draw a whole picture of the network
Manage clusters and routes based on the picture
Each node periodically transmits hello message
A node detects failure if a node cannot receive the message fromanother node for a predefined time
Failure indication is sent to the control station

Robust (Resilient)
RobustData collection
capability

Sensor nodes are divided into
as many clusters as sinks
Routing is performed in each cluster

Countermeasures against node failures

Perturbation

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Centralized control in our comparison

Robustness

Perturbation:
System:Function:

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Self-organization in NatureSelf-organized control in our comparison

Ants or Bees

Cluster-based approach
Same as the centralized control

Each agent is simple and unintelligent
Interacts with neighboring agents
Obeys the local rules it has as a species

Sensor nodes are divided into some clusters
Routing is performed in each cluster

Combination of two swarm intelligence of ants

Their collective action creates biological order

Ant-based clustering for clustering
Ant colony optimization (ACO) for routing

Allocating tasks
Finding shortest path to their foodGroupingby their havesize tried to derive
Manyeggs
researchers

These are mediated by “pheromone”
Fault management

advantageous properties from biological system:

Failure detection is same as that of centralized control
There is no explicit failure indication

Bio-inspired ControlICSNC2008

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Simulation settings

Self-organized control

Adjacent node detects sinkfailure
Form of clusters change graduallyCentralized control

Control station detects failure
immediately
Clusters' reconstruction starts

100 m

Metric of robustness(75, 25)

100 m

Sinks

Data-collection rate: r/s
where• r : Number of packets received by sinks• s : Number of packets transmittedNodes

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Influence of link disconnection

Concentrated control recovers
performance quickly

Large BER:

Error of each node
does not influence thewhole network

Self-organizing control(plink=0.01,0.05,0.10)
Data-collection rate

Self-organized control

1plink=0.01

0.8

plink=0.05

0.6

centralized: BER=1e-5
centralized BER=1e-4

0.4
0.20sink failure
0200

400600Time [s]800

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1000

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DependenceTerm used by Fault Management
Error of a certain object causes the error of other objects.

Centralizedcontrol

Information exchanged between entities for cooperation

Problem about control information
Control information does not arrive at control station
Contents of the control information itself are erroneous

plink=0.10

0.4
0.2
0

self-organizing: BER=1e-5self-organizing: BER=1e-4

0.6

Control information

C

Centralized control
Controlstationperforms control based
ontheerroneousinformation

Node B hasfailed.

B

Node B isfine.

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Dependence on control information

Link of the rate of plink was disconnected for 100 seconds
to 500 seconds at random

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Small BER:

Performance recovery ofconcentrated control becomesslow

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If a sink fails…

10m transmission range
Data packets is transmitted
every 10 seconds to a sinkUsing network simulator ns-2

(75, 75)(25, 25)ICSNC2008

Recovery from sink failure

100x100m2 monitoring region
300 nodes
4 sinks(25, 75)

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Data-collection rate

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link-disconnection duration
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Time [s]

800

1000
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Dependence is major factor of the difference in therobustness between self-organized and centralized control
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Influence of incorrect information

False-recovery information
160 sec: A node near the sink (25, 25) fails
200 sec: Injection of incorrect information“Node has recovered !”Errors are contained in the control
information obtained from each nodeCentralized control

Self-organized control
Centralized control

Self-organized control
No performance degradation
resulting from incorrect
information

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Control station understands the stateof the whole network based on theinformation from each node

Performancedegradation byincorrect informationICSNC2008

100%

Reliability of each node is not so highCannot recognize change of network
composition precisely
The control information from a nodeinfluences only in the neighborhood

Performance deteriorates
for the control based onincorrect information

Self-organized control

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0%

Centralized control
100%0%

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Conclusion and future work
Characteristic of self-organized control and centralized
control was compared
Evaluated by simulations for sensor network system

Robustness of self-organized control

Control information is exchanged locally
Influence of erroneous information is small

Thank you !

Fragility of centralized control

Control station integrates individual control information andunderstands the state of the whole network
Erroneous information affects the whole system

Future work

Quantification of dependency strength
Generalization of results

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