Athanasios Kinalis ∗, Sotiris Nikoletseas ∗, Dimitra Patroumpa ∗, Jose Rolim† ∗ University...
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Transcript of Athanasios Kinalis ∗, Sotiris Nikoletseas ∗, Dimitra Patroumpa ∗, Jose Rolim† ∗ University...
Athanasios Kinalis , Sotiris Nikoletseas , ∗ ∗Dimitra Patroumpa , Jose Rolim†∗
∗University of Patras and Computer Technology Institute, Patras, Greece
†Centre Universitaire d’ Informatique, Geneva, Switzerland
IEEE Globecom2009
Biased Sink Mobility with Adaptive Stop Times forLow Latency Data Collection in Sensor Networks
Outline
Introduction Network modelThe proposed schemeSimulation Conclusion
Introduction
As the sensed data are forwarded to the sink node in the WSNSettings have increased implementation complexitySensor devices consume significant amounts of energy
Sensor node
Sink node
Introduction
A approach has been introduced that shifts the burden of acquiring the data, from the sensor nodes to the sink.Help conserve energy since data is transmitted over
fewer hops.
Many apparent difficulties arise as well since traversing the network in a timely and efficient way is critical.high density of sensors in an areasome sensors have recorded a significant amount of data
Introduction
High delivery delaysEven data loss
A
B
Goal
They propose biased sink mobility with adaptive stop times, as a method for efficient data collection in wireless sensor networks.reduces latencydelivery success rate
Network model
The sink can accurately calculate its positionThe sink can aware of the dimensions and boundaries of the network
areaThe sensor of sensing range R
D
D
j
j
2
Dj
R
Sensor node
Sink node
Scheme
Network TraversalDeterministic WalkBiased Random Walk
Calculation of Stop Time
Deterministic Walk
j
j
ASensor node
Sink node
Biased Random Walk The probability p(f)v of visiting a neighboring vertex v
2 2 1
1 42 2
2 3 3 0
2 32 3
1
A B
C
D
E
1 1 / 8 7( )
3 24bp f
1 2 / 8 6( )
3 24cp f
1 2 / 8 6( )
3 24dp f
1 3 / 8 5( )
3 24dp f
2
Sensor node
Sink node
Etotal is the total initial energy of all the sensors in the network
Ttotal_stop represents the maximum total amount of time the sink can remain stationary.
n is the number of sensors of the network
Calculation of Stop Time
εi the initial energy of each sensor i.
Tsim is the total time that the experiment is performedEtotal
the maximum amount of energy consumed when sending a messagethe average event generation rate
the energy spent when the sensors remain idle
Ttotal_stop_round is the maximum amount of time that the sink will remain static in each round.
__ _
Ttotal stopTtotal stop round
r
represents the maximum total amount of time the sink can remain stationary
Calculation of Stop Time
the algorithm evolves in r rounds
Constant stop time.
Adaptive stop time.
the maximum amount of time that the sink will remain static in each round
Calculation of Stop Time
the density in cell i
Calculation of Stop Time
Example
A B
CD
10iTcell
d = 1
dA = 1.5dB = 1.2dC = 0.5dD = 0.8
1.5 1.2
0.50.81.5
10 151adapAT
1.210 12
1adapBT
0.510 5
1adapCT
0.810 8
1adapDT
Simulation
Simulator ns − 2
the size of the network area 200m × 200m
sensor nodes 300
the speed of the mobile sink s {4, 8, 10, 20}m/s∈
The initial energy reserves of the nodes 5.5 Joules
The data is generated at an average rate 1 message/10 sec
Simulation SCD (Stop to Collect Data), one of the algorithms proposed in [6]. In SCD, the
mobile sink stops when receiving new data.
A. Kansal, A. Somasundara, D. Jea, M. Srivastava, and D. Estrin, “Intelligent fluid infrastructure for embedded networks,” in 2nd ACM/USENIX International Conference on Mobile Systems, Applications, and Services (MobiSys04), 2004.
Simulation SCD (Stop to Collect Data), one of the algorithms proposed in [6]. In SCD, the
mobile sink stops when receiving new data.
A. Kansal, A. Somasundara, D. Jea, M. Srivastava, and D. Estrin, “Intelligent fluid infrastructure for embedded networks,” in 2nd ACM/USENIX International Conference on Mobile Systems, Applications, and Services (MobiSys04), 2004.
Conclusion They propose both randomized mobility and
deterministic traversals.They adaptive stop times lead to significantly reduced
latency and keeping the delivery success rate.
Thank you ~