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: fhgielow@inf.ufpr.br