Bounded relay hop mobile data gathering in wireless

sensor networks

Miao Zhao and Yuanyuan YangDepartment of Electrical and Computer Engineering

State University of New York

IEEE MASS 2009

Outline Introduction Goal BRH-MDC Problem Centralized Algorithm for BRH-MDC Problem Distributed Algorithm for BRH-MDC Problem Performance Evaluation Conclusion

Introduction Data gathering in WSN

Multi-hop relay High energy consumption

Introduction Employing mobile collectors

Low energy consumption

High collection latencytradeoff

Energy saving

Collection latency

Goal Proposing a polling-based approach that pursues a tradeoff

between the energy saving and data collection latency

Achieves a balance between the relay hop count for local data aggregation and the moving tour length of the mobile collector.

BRH-MDC Problem Network assumption

The mobile collector has the freedom to move to any place in the sensing field

Basic idea Find a set of special nodes referred to as polling points (PPs) in th

e network The PPs are compactly distributed and close to the data sink. The number of the PPs is the smallest

BRH-MDC Problem

Polling point

Sensor

Static data sink

Relay routing path

Mobile collector tourd-hop bound

BRH-MDC Problem Relay hop count should be bounded ( d-hop )

A sensor network may expect to achieve a certain level of systematic energy efficiency.

Eg. If each transmission costs one unit of energy and the energy efficiency of 0.33 packet/energy_unit is expected

3 energy_unit/packet4 energy_unit/packet

3 energy_unit/packet2-hop bound

The bound is necessary due to buffer constraint on the sensors.

Centralized Algorithm for BRH-MDC Problem Shortest Path Tree based Data Collection Algorithm (SPT-DCA)

Energy saving and data collection latency Constraint of the relay hop bound (d-hop)

The sensors selected as the PPs are compactly distributed and close to the data sink. The number of the PPs is the smallest under the constraint of the relay hop bound.

Centralized Algorithm for BRH-MDC Problem Shortest Path Tree based Data Collection Algorithm (SPT-DCA)

Energy saving and data collection latency Constraint of the relay hop bound (d-hop) The sensors selected as the PPs are compactly distributed and close to the data sink. The number of the PPs is the smallest under the constraint of the relay hop bound.

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d-hop = 2-hop

Iteration 1

Centralized Algorithm for BRH-MDC Problem Shortest Path Tree based Data Collection Algorithm (SPT-DCA)

Energy saving and data collection latency Constraint of the relay hop bound (d-hop) The sensors selected as the PPs are compactly distributed and close to the data sink. The number of the PPs is the smallest under the constraint of the relay hop bound.

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d-hop = 2-hop

= 1-hop

Iteration 2

Centralized Algorithm for BRH-MDC Problem Shortest Path Tree based Data Collection Algorithm (SPT-DCA)

Energy saving and data collection latency Constraint of the relay hop bound (d-hop) The sensors selected as the PPs are compactly distributed and close to the data sink. The number of the PPs is the smallest under the constraint of the relay hop bound.

16 14

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d-hop = 2-hop

Final result

Distributed Algorithm for BRH-MDC Problem Priority based PP selection algorithm (PB-PSA)

Energy saving and data collection latency

The primary parameter is the number of d-hop neighbors, which are the sensors in its d-hop range.

The secondary parameter is the minimum hop count to the data sink.

TENTA_ PP

TENTA_PP.ID

TENTA_PP.d_Nbrs

TENTA_PP.Hop

Priority based PP selection algorithm (PB-PSA) Energy saving and data collection latency

The primary parameter is the number of d-hop neighbors, which are the sensors in its d-hop range.

The secondary parameter is the minimum hop count to the data sink.

TENTA_ PP

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3

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4 5

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TENTA_ PP = 5TENTA_ PP = 5,4,6

TENTA_PP.ID TENTA_PP.d_Nbrs TENTA_PP.Hop

5 2 2

4 3 2

6 2 1

TENTA_ PP =4

Round 1

TENTA_ PP =4

TENTA_ PP =3

TENTA_ PP =3

TENTA_ PP =3

TENTA_ PP =3

d-hop=2-hop

Priority based PP selection algorithm (PB-PSA) Energy saving and data collection latency

The primary parameter is the number of d-hop neighbors, which are the sensors in its d-hop range.

The secondary parameter is the minimum hop count to the data sink.

TENTA_ PP

1

3

2

4 5

6

TENTA_PP.ID TENTA_PP.d_Nbrs TENTA_PP.Hop

4 3 2

3 3 1

TENTA_ PP =4

Round 2

TENTA_ PP =4

TENTA_ PP =3

TENTA_ PP =3

TENTA_ PP =3

TENTA_ PP =3

TENTA_ PP =4,3TENTA_ PP =3

TENTA_ PP =3

d-hop=2-hop

Priority based PP selection algorithm (PB-PSA) Energy saving and data collection latency

The primary parameter is the number of d-hop neighbors, which are the sensors in its d-hop range.

The secondary parameter is the minimum hop count to the data sink.

d-hop=2-hop

TENTA_ PP =1

1 2 3 4 5

TENTA_ PP =2 TENTA_ PP =3 TENTA_ PP =4 TENTA_ PP =5

Round = 1 TENTA_ PP =2 TENTA_ PP =3 TENTA_ PP =4 TENTA_ PP =5 TENTA_ PP =5

Round =2 TENTA_ PP =3 TENTA_ PP =4 TENTA_ PP =5 TENTA_ PP =5 TENTA_ PP =5

Priority based PP selection algorithm (PB-PSA) Energy saving and data collection latency

The primary parameter is the number of d-hop neighbors, which are the sensors in its d-hop range.

The secondary parameter is the minimum hop count to the data sink.

1

3

2

4 5

6

TENTA_ PP =3

Declar

TENTA_ PP =3

TENTA_ PP =3

TENTA_ PP =3

TENTA_ PP =3

Priority based PP selection algorithm (PB-PSA) Energy saving and data collection latency

The primary parameter is the number of d-hop neighbors, which are the sensors in its d-hop range.

The secondary parameter is the minimum hop count to the data sink.

1

3

2

4 5

6Declar

PP =3

PP =3

PP =3

PP =3

PP =3

Declar

Performance Evaluation Simulation Parameter

A network with 30 sensors scattered over a 70m x 70m square area. d is set to 2.(2-hop bound)

Performance Evaluation Comparison with the Optimal Solution

Performance Evaluation Performance of SPT-DCA and PB-PSA

Increasing relay hop bound d

Performance Evaluation Performance of SPT-DCA and PB-PSA

Increasing transmission range Rs

Performance Evaluation Comparison with SHDG and CME

"Data gathering in wireless sensor networks with mobile collectors," IEEE IPDPS, 2008.

"Multiple controlled mobile elements (data mules) for data collection in sensor networks,“ IEEE DCOSS 2005.

Performance Evaluation Comparison with SHDG and CME

Increasing the number of sensors

Performance Evaluation Comparison with SHDG and CME

Increasing the side length of the area (L)

Conclusion The paper have studied mobile data gathering in wireless

sensor networks by exploring the tradeoff between the relay hop count of sensors for local data aggregation and the tour length of the mobile collector.

Then presented two efficient algorithms to give practically good solutions.

The results demonstrate that the proposed algorithms can greatly shorten the data collection tour length with a small relay hop bound

Thank you very much~