An Integrated Approach to Sensor Role Selection

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An Integrated Approach to Sensor Role Selection

• by Mark Perillo and Wendi Heinzelman

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Outline

• Motivation
• Background
• Modeling
• Solution (DAPR)
• Analysis
• Comparison
• Conclusion

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1. MOTIVATION (WSN Energy Efficiency)

• Limited energy supply VS long network lifetimes
• Hardware, Operating System, Low-level protocol
  design
• Balance/reduce energy consumption
• Reduce redundancy but ensure QoS requirement
• dynamic sensor selection, in-network aggregation,
  distributed source coding

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Example for Power reduction

• Operation System eg. TinyOS
• to put microcontroller to sleep
• to put radio to sleep
• Low-level Protocol
• low-level listening on physical layer
• SMAC TMAC on link-layer
• Reduce idle listening, overheads (collision,
  overhearing, protocol overheads)

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BACKGROUND

• Abundant data
• Filter sensors
• Multi-hopping
• Design routing
• Diverse importance
• Assign duties

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• WHAT HAVE BEEN DONE ?

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Relevant Work -- Sensor Selection(I)

• Principle desired coverage
• PEAS
• activeness probing/querying
• Gur game paradigm
• state switching according to base station
• Sensing coverage protocol
• sleep/wake time scheduling according to
  neighbors with differentiated surveillance
• neighbor redundancy, coverage redundancy
• CCP
• coverage and connectivity

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Relevant Work -- Sensor Selection(II)

• Principle Considering routing
• less sensors some routings short path
  desired coverage

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Relevant Work Routing Protocols(I)

• Principle Shortest path
• Table-driven routing protocol
• destination-sequenced distance vector routing
• clusterhead gateway switch routing
• the wireless routing protocol

• Source-initiated on-demand routing
• ad hoc on-demand distance vector routing
• dynamic source routing
• temporally ordered routing algorithm
• associativity-based routing
• signal stability routing

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Relevant Work Routing Protocols(II)

• Principle considering energy efficiency
• Power-aware MAC layer routing
• route through nodes with sufficient remaining
  power
• route through lightly-loaded nodes

• Maximizing the network lifetime
• minimize the energy consumed every packet

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PROPOSAL Sensor selection Energy conserved
routing PRINCIPLE To use the sensors not as
important as data generators more liberally as
routers
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Critical NodesThe sensors in the sparsest
regions
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MODELING Assumptions

• Power consumption largely from traffic
  transmitted and received
• Portion or entirety of an area A needs to be
  monitored by any one or multiple sensors
• There may be one or several data sink locations

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MODELING -- Varianbles
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MODELING Formalization(I)
Coverage
Number of nodes Nt Ns Nsink
Data flow
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MODELING Formalization(II)
Energy consumption
Scheduling
Lifetime
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MODELING Coverage-Aware Routing Cost
Common cost (energy-aware cost)
Total energy in a subset area x
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MODELING Worst Coverage-Based Cost
Finds out the least-covered subregion
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E(Xa) 2 E(Xb) 3 E(Xc) 2 E(Xd)
1 Cwc(S1) ½ Cwc(S2) ½ Cwc(S3) 1
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MODELING Comprehensive Coverage-Based Cost
Weighted sum (in terms of area of subregion) of
1/E(x) It provides a more balanced view of a
nodes importance to the sensing task.
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E(Xa) 2 E(Xb) 3 E(Xc) 2 E(Xd)
1 Ccc(S1) area(A)/2 area(B)/2 Ccc(S2)
area(A)/2 area(B)/3are(C)/2 Ccc(S3)
area(B)/3 area(C)/2are(D)/1
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MODELING Combining Cost Functions
Most effective in extending lifetime with 100
percent coverage
Effective in providing long network lifetimes
with graceful degradation
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SOLUTION DAPR (Distributed Activation with
Predetermined Routers)
The decision made in sensor selection and route
discovery are influenced each other.
Procedure Route Discovery Phase Sensor
Selection Phase Sensor query
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DAPR Route Discovery Phase(I)

• Assumption
• Nodes have location information of neighbors with
  redundant coverage regions
• Low power wakeup system

Cost of a link routing cost nodei x energy for
transmission routing cost nodej x energy for
reception
Cost of a route sum of links in the route
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DAPR Route Discovery Phase(II)
Data Sink
Node
Initiate query
flood query
receive query
Calculate link cost
Update query packet
forward query (delay scheme) proportional to
Clink(Si)
Next Node
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DAPR Sensor Selection Phase
Initial be inactive to sense and generate data

• Assign activation delay (proportional to the
  route cost)
• Check received activation beacon
• check if the neighborhood is already covered
• Send activation beacon
• send activation beacon to neighbors if possible
• (Send deactivation beacon)
• send deactivation beacon if in high redundancy
  and in the highest cost route
• DAPR A Protocol for Wireless Sensor Networks
  Utilizing an Application-based Routing Cost

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DAPR (Contd)

• Awareness of neighbors
• Location
• Redundant coverage
• Given highest priority
• Nodes along highest route
• Reserving opt-out/deactivation beacon
• Sending beacon
• In single hop (Dtransmission_range gtgt
  Dsensing_range)
• Forwarding (no guarantee)

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SIMULATIONANALYSIS Simulation result
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SIMULATIONANALYSIS Experiment Result
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SIMULATIONANALYSIS Experiment Result for
Sensor Selection

• Configuring activation/backoff delay in Worst
  Coverage-Coverage Routing Cost

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SIMULATIONANALYSIS Experiment Result for
Combing routing cost

• Worst coverage-based energy-aware routing cost

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COMPARISON to Centralized Approach

• Assuming subject to these conditions
• data flow, energy consumption constraints and
  scheduling constraints, we try to maximize the
  operation time of the system

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COMPARISON to Centralized Approach
Uniform scenario worst coverage energy-aware
cost with DAPR gains 14 over the nonintegrated
approach. 56 closer to centralized solution.
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COMPARISON to Centralized Approach (Condt)
In clustered scenario Worst coverage routing
cost with DAPR improves lifetime by 56. 77
closer to centralized solution, Due to use of the
coverage-aware routing cost.
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COMPARISON to Centralized Approach (Condt)
In video scenario DAPR with the combined worst
coverage and energy-aware cost makes lifetime
gain 50,Closing gap by 76, Because the
selection of sensors based on the cumulative
route cost.
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CONCLUSION

• Contribution
• Incorporation of coverage information into the
  routing protocol and the priority for sensor
  selection
• Worst coverage-based cost maintaining 100
  coverage for the maximum lifetime
• Comprehensive coveraged-based cost giving a
  more balanced interpretation of a nodes value to
  the sensing task

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Thank You