A Decentralized Method for Maximizingk-coverage Lifetime in WSNs

Ryo Katsuma*, Yoshihiro Murata**, Naoki Shibata†,

Keiichi Yasumoto‡, Minoru Ito‡

1 ICMU2012 04/13/2023

* Osaka Prefecture University, 　 ** Hiroshima City University, † Shiga University, 　　　　 ‡ Nara Institute of Science and Technology

Overview of Our Study Goal

To maximize lifetime of wireless sensor networks (WSNs)

Approach Sleep scheduling for each node by decentralized algorithm

Divide the field into grids and choose leader node for each grid Periodically make each leader node calculate the minimal set of

active nodes in its grid Periodically change the leader for each grid

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Outline

1. Outline of our study

2. Research background

3. Related work

4. Proposed method

5. Evaluation

6. Conclusion

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Target WSNs WSNs for Data Collection

Many small sensor nodes are deployed in the field Sensor nodes periodically sense environmental

information Nodes send data to sink node by multi-hop

communication

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sink

Target field

20℃21℃ 21℃

18℃22℃20℃

23℃

21℃

21℃

20℃ MICA mote

Example of sensor node

Two Big Problems Problem to maximize lifetime

WSNs are expected to operate for a long time Sleep scheduling for each node is required

Activating minimum number of nodes required for WSN operation

Other nodes sleep in order to save energy

　　　 Nodes are activated in turn

k-coverage problem A sensor node covers a circular area for sensing k-covering the entire field by active sensors

Any point in the field is covered by at least k sensors Adjust k to monitor the area with required accuracy

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2-covered

Sensor node

Challenge

Maximizing k-coverage lifetime Lifetime is the time while the entire field is k-

covered

Battery energy is consumed in each node optimal set of active nodes changes

According to remaining battery energy

We need periodical reclculation

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Outline

1. Outline of our study

2. Research background

3. Related work

4. Proposed method

5. Evaluation

6. Conclusion

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Our Previous Work (1/3)

Sleep scheduling method Sufficient number of nodes are deployed Deciding minimal set of active nodes for k-covering

the field When battery is exhausted for some node Recalculate a set of active nodes

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sink

batteryexhauste

d

activate

field

Our Previous Work (2/3) Sequential activation algorithm

For deciding minimal set of active nodes Activate a node with the largest contribution area

one after another until the field is k-covered Contribution area

The area newly covered when the node is activatede.g. If A is active, contribution area of D is larger than C

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A

B

C

D

ED Active node

CA

Our Previous Work (3/3) Centralized calculation by sink node

Collects sensor node information Remaining energy Position

Calculates the minimal set of active nodes Sends the result to every node

WSNs with a large number of nodes Long calculation time High overhead for sending result

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We propose a decentralized method

Outline

1. Outline of our study

2. Research background

3. Related work

4. Proposed method

5. Evaluation

6. Conclusion

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Assumptions Deployed nodes

Enough number of sensor nodes for k-coverage Only one sink node

Sensor nodes Limited battery energy Sensing range radius is rs

Maximum communicable range radius is rc ( rs < rc )

Sensor node can save battery by sleeping and waking up by timer

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rs

rc

Initial Configuration Dividing field into grids

k-covering entire field by k-covering each grid Side length of grid should be shorter than

To guarantee that a node can communicate every node in the surrounding 8 grids

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rc

Leader Node Selection Selecting leader node for each grid

Calculate minimal set of active nodes for k-covering its grid by sequential activation algorithm

Collect all sensing data in its grid and send to sink

Periodically selects the node with highest remaining battery as the leader node A set of active nodes is calculated after the leader node

is selected

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Excessive Coverage Problem If active nodes are independently selected in each grid

Number of coverage exceeds k near the grid border

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A

B

C

D

E

F

G

H

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J

K

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Grid Ci Grid Cj

Excessive Coverage Problem If active nodes are independently selected in each grid

Number of coverage exceeds k near the grid border

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A

B

C

D

E

F

G

H

I

J

K

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Grid Ci Grid Cj

Excessive Coverage Problem If active nodes are independently selected in each grid

Number of coverage exceeds k near the grid border

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A

B

C

D

E

F

G

H

I

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Grid Ci Grid Cj

Excessively covered

Our Idea Deciding the minimal set of active nodes for adjoined

grids in multiple steps Considering the area already covered by the nodes in the

adjoined grids

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A

C

D

F

G

I

Grid Ci Grid Cj

A. We need only 2 steps

P

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N

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HB E

Coverage informationQ. How many steps do we need to complete the entire calculation?

Bi-coloring Classifying all grids into two

groups White and black, like a checkerboard Any two adjoining grids have different

colors Active nodes are chosen in white grids

Computation in black grids is performed after computation in neighboring white grids

Prevent excessive coverage Complete computation in 2 steps

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① ①

① ① ①

① ① ①

① ①

① ①

② ②

② ② ②

② ②

② ② ②

② ② ②

Data Collection Each sensor node sends sensed data to leader node Leader nodes send the data to the sink

Constructing DAG Connecting other leader nodes that are closer to the sink

Sending data to the node with the largest remaining energy

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sink

Leader node

Outline

1. Outline of our study

2. Research background

3. Related work

4. Proposed method

5. Evaluation

6. Conclusion

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Simulation Evaluate k-coverage lifetime by the proposed method Compared proposed method with centralized method

WSN parameters Field size: 50[m] × 50[m] Number of nodes: 600 － 1000, random deployment Requested coverage: k = 1 and 3 Sensing frequency: 0.1[Hz] Recalculation interval: 1000[s]

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Result k-coverage lifetime

Proposed method is only 14% less than centralized method Calculation time (1000 nodes)

Proposed method: 0.1 second, centralized method: 1.2 second

23 ICMU2012 04/13/20231-coverage 3-coverage

Conclusion Target problem

Maximizing k-coverage lifetime by sleep scheduling Proposed method

Dividing the field into two-colored grids like a checkerboard

Deciding the minimal set of active nodes taking into account the coverage already decided by neighbor grids

Simulation result k-coverage lifetime is only 14% less than centralized

method Shorter computation time

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