unequal clustering
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Transcript unequal clustering
Resilient Approach for Energy Management
on Hot Spots in WSNs
Fernando Henrique Gielow
Michele Nogueira
Aldri Luiz dos Santos
{fhgielow,michele,aldri}@inf.ufpr.br
NR2 – Federal University of Paraná
IFIP/IEEE IM2011
Dublin, May 23th, 2011
Outline
Introduction and motivation
Related work
CEA – Cluster-based Energy Architecture
RRUCR
Definition of scopes
Clustering
Initial backbone creation
Cluster-heads rotations
Data gathering & Routes maintenance
Evaluation
Conclusion
Introduction and motivation
Sensor nodes: constrained resources
Low processing and storage capabilities
Limited lifetime
Applications
Surveillance/monitoring systems
Data gathering applications
Introduction and motivation
Traffic patterns
n to n
n to 1
Unequal traffic distribution
Data gathering applications
Areas burdened with higher traffic rates
Introduction and motivation
Hot Spots
There are more important nodes in the network
Unequal traffic distribution
Areas burdened with higher traffic rates
Mitigation through sink mobility, biased
deployment, unequal clustering
Related work
Hot Spot mitigation
Sink mobility
Biased deployment
The nodes close to the sink will change eventually
Unpractical in the majority of scenarios
E.g. [Thanigaivelu and Murugan, 2009]
Manually deploying more nodes near the sink
Unpractical in the majority of scenarios
E.g. [Wu and Chen, 2006]
Unequal clustering
Smaller clusters near the sink
More routes to reach the sink
E.g. [Chen et al, 2009]
CEA: Cluster-based Energy Architecture
Generic behavior
Cluster-based
Hot spot mitigation
Intra/inter clusters
energy management
Route management
The RRUCR protocol
Rotation Reactive Unequal Cluster based Routing
Cluster-based multi-hop protocol for networks with
n to 1 traffic pattern
Data gathering applications
Unequal clusters to mitigate hot spots
Dynamic maintenance of routes
Operations of RRUCR
Definition of scopes
Clustering
Initial backbone creation
Cluster-heads rotations
Data gathering & Routes maintenance
RRUCR
Definition of scopes
Transmission powers ordered and indexed
The sink covers those powers
4
4
3
4
2
3
4
3
2
2
1
Potence
indexused
used
Potence indexPotence
used index
2 to cover
by
the sink
by the 3sink toby
cover
current
node to
nearest
node
Potence
most distant node
reach
the
sink index limit
to this operation
RRUCR
Clustering
Unequal sized
Hot spot mitigation
(funneling of routes)
Previously defined
scope power
Balanced quantity
Avoids dense areas
Still cover all nodes
RRUCR
Initial backbone creation
Process initialized by the sink
Process carried by cluster-heads
Update route and forward message once
RRUCR
Cluster-heads rotations
Balance internal energy consumption
Prolong network lifetime
Generate broken links when selecting farther nodes
Force route update of the node that rotated
(
)
and of the nodes which used the previous CH
(
)
RRUCR
Data gathering & Routes maintenance
CHs route the data to the sink in a multi-hop way
That message carries a field which indicates the
distance from the node up to the sink
Used to update routes
If obligatory and a node with shorter distance found
Reactive approach, with low overhead
Evaluation
Parameters
1000x1000m
700 nodes
Initial energy between 0.9 and 1.1 J
1% prob. of generating 32 bytes of data at each 0.1s
5000s
Radio parameters set according to Mica2
3 scenarios
Without failures
With failures close to the sink
With failures far from the sink
ns-2.30 simulator
35 simulations – interval of confidence of 95%
Compared to UCR
700
650
600
550
500
450
400
350
300
250
200
RRUCR
UCR
4500
Death of the first node (s)
Total energy
Evaluation
0
1000
2000
3000
4000
RRUCR
UCR
4000
17%
3500
13%
3000
2500
2000
1500
5000
Close
Far
None
Failures
Time (s)
24
70
RRUCR
UCR
60
Number of clusters
Number of rotations
21%
50
40
30
20
10
RRUCR
UCR
21
18
15
12
9
6
3
0
0
0
1000
2000
3000
Time (s)
4000
5000
1
2
3
4
5
Hops to the sink
6
7
Evaluation
RRUCR
30
25
20
Number of dead nodes
Number of dead nodes
UCR
DS <= 40
40 < DS <= 80
80 < DS <= 160
160 < DS
15
10
5
0
3000
4000
Time (s)
5000
30
25
20
DS <= 40
40 < DS <= 80
80 < DS <= 160
160 < DS
15
10
5
0
3000
4000
Time (s)
5000
Evaluation
Data delivery rate (%)
RRUCR
RRUCR
UCR
60
50
0.9
0.8
None
Close
Far
0.7
0
5
10
15
20
25
20
25
Rotations
40
30
UCR
20
10
0
0
1000
2000
3000
Time (s)
4000
5000
Data delivery rate (%)
Number of rotations
70
1
1
0.9
0.8
None
Close
Far
0.7
0
5
10
15
Rotations
Conclusion
Address the Hot spot impacts on WSN
RRUCR
Less deaths close to the sink
Improve network lifetime
Balanced quantity of clusters
Increased network lifetime in 21.36%, when
compared to UCR
Increased data delivery rates
Work extended to a generic architecture (CEA)
Future work
Operations that check the integrity on WSN links
More complex route maintenance
A TinyOS implementation of RRUCR
Project page with more information
www.nr2.ufpr.br/~fernando/rrucr/
Source code available under LGPL
ns-2.30 simulation
Installation script
Doubts?
Email for contact: [email protected]