Sprinkler: A Reliable and Energy Efficient Data Dissemination Service in Extreme Scale Wireless Networks of Embedded Devices

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Sprinkler A Reliable and Energy Efficient Data
Dissemination Service in Extreme Scale Wireless
Networks of Embedded Devices

• Vinayak Naik, Anish Arora,
• Prasun Sinha, and Hongwei Zhang
• Dependable Distributed and Networked Systems
• December 7, 2005

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Project ExScal Concept of Operation
Put tripwires anywherein deserts, other areas
where physical terrain does not constrain troop
or vehicle movementto detect, classify track
intruders in real time over a long, linear region
Envisioned ExScal customer applications
Hide Site
IED
Gas pipeline
Border patrol
Convoy protection
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ExScal Highlights

• Demonstrated in December 2004 in Florida
• Deployment area 1,260m x 288m
• 1000 XSMs
• 200 XSSs, forming an 802.11b mesh network
• Design, development, integration time 15 months
• Field setup experimentation time 2 weeks
• Team 50 people
• Budget 5M, 10,000 nodes manufactured
• Current status
• Software classified as secret by US Government
• Technology transfer to Northrup Grumman in
  progress
• 10,000 node experiment in near future using
  ExScal software

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Hierarchy of ExScal Network
Tier 3 PC
Tier 2 200 XSS
Tier 1 20-50 XSMs per XSS
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Planned Topology at Tier 1 ? Optimized Coverage
1,260m
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• Thick line
• XSMs in hexagonal grid
• Thin line
• XSMs in single line

90 m
? ? ... ?
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Base Station
288 m
90 m
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90 m
Asset being secured
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Tier 2 ? Real Time Operation
1,260m

• XSS for ExScal
• Application
• XSS for Tier-2
• Experiments

45 m



45 m
Base Station
45 m
288 m



45 m
45 m
45 m
Asset being secured
45 m
45 m
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New Model due to Extreme Scale Wireless Embedded
Devices

• Embedded devices are constrained in following
  resources
• CPU
• Memory
• Power
• Characteristics of wireless medium
• Spatial and Temporal variation in link quality
• Hidden terminal effect
• Extreme scale demands sub-linear time complexity
• O(n) isnt good enough for resource constrained
  devices
• Different model as compared to that of the
  Internet
• Existing network services may not work

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Outline

1. Motivation and Requirements
2. Insight behind Solution
3. Formal Problem Statement and Algorithms
4. Analysis and Comparison
5. Conclusion

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ExScal

• Demonstrated in December 2004 in Florida
• Deployment area 1,260m x 288m
• 1000 XSMs
• 200 XSSs, forming an 802.11b mesh network

XSM
XSS
The 11th International Conference on Embedded
and Real-Time Computing Systems and Applications
at Hong Kong, 2005
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Irrigating ExScal

• Motivation behind data dissemination service
• Reprogramming in the field (hundreds of packets)
• System reconfiguration (tens of packets)
• Health monitoring (lt ten packets)
• Problem of bulk data dissemination service
• 100 Reliability
• Energy efficiency
• Low latency

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Outline

1. Motivation and Requirements
2. Insight behind Solution
3. Formal Problem Statement and Algorithms
4. Analysis and Comparison
5. Conclusion

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Energy Saved is Energy Generated
Operation Current Draw Current Draw
Operation Mote Stargate
Microprocessor and Idle Radio 8 mA 330 mA
Packet Reception 16 mA 280 mA
Packet Transmission 24 mA 650 mA

• Load shedding
• Packet Transmissions
• Microprocessor and Idle Radio (Not covered in
  this talk)

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Unit Disk Model
R
B
R
A
R Transmission Radius
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Connected Dominating Set
Fewer number of senders
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Hidden Terminal Effect
B
C
A
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Time Division Multiple Access
D
C
B
A
Schedule transmissions
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Outline

1. Motivation and Requirements
2. Insight behind Solution
3. Formal Problem Statement and Algorithms
4. Analysis and Comparison
5. Conclusion

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Formal Problem Statement

• Divide-n-Conquer
• An algorithm to compute a CDS, of size O(1) times
  the minimum, in O(1) time
• An algorithm to compute a distance-2 vertex
  coloring, with O(1) times the minimum of
  colors, in O(1) time
• A reliable data dissemination protocol that
  utilizes a CDS and a corresponding distance-2
  vertex coloring
• Assumptions
• Minimum density 1 node per square of length
• Location information

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Algorithm to Compute CDS

• Division of network into disjoint square-shaped
  clusters,each of length
• Election of a cluster-head in each cluster
• Decision whether a cluster-head belongs to CDS or
  not
• Variables
• r be the total number of cluster-heads in X axis
• c be the total number of cluster-heads in Y axis
  
• u(i,j) be any cluster-head and (i,j) be its (X,Y)
  coordinates
• Program A node u(i,j) ? M, where 0 i r-1 and
  0 j c-1, if
• r mod 3 0 i mod 3 1 ? (i mod 3 1) ? (0
  lt i lt r-1) ? (j 0)
• r mod 3 1 i mod 3 0 ? (i mod 3 0) ? (j
  0)
• r mod 3 2 i mod 3 1 ? (i mod 3 1) ? (i
  0) ? (j 0)

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CDS Computation
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D-2 Vertex Coloring
lt 2R
R
8
9
10
11
12
13
R
Numbers indicate colors.
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Data Dissemination Protocol

• Streaming phase
• Only CDS nodes transmit
• Transmissions in TDMA slots
• Results in reliable data dissemination to all CDS
  nodes
• Recovery phase
• Any node can transmit
• Unscheduled transmissions
• Results in reliable data dissemination to all the
  nodes

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Streaming Phase
A
B
C
D
R ? 2
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Recovery Phase
R
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Models for Real Radio

• Radio models in real environment are more complex
  than unit disk model
• Packet delivery rate for XSS in an outdoor
  environment
• Similarly, for indoor testbeds

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Adapting Sprinkler to Real Radio Models

• Variables
• Let be the reliable communication range
• Let be the communication range that results
  in minimum number of packet transmissions (via
  in-field measurements)
• Procedure
• Set for CDS computation and D-2 vertex
  coloring algorithms
• Density assumption still holds
• Since every square of length contains at
  least one node, every square of length also
  contains at least one node

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Adapting Sprinkler to Real Radio Models

• Input parameter
• Transmission radius ( )
• Procedure
• Initialize , where is the reliable
  communication range (100 packet delivery)
• Keep incrementing till the number of
  transmissions for the test broadcast are reducing
• Density assumption still holds
• Since every square of length contains at
  least one node, every square of length also
  contains at least one node

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Adapting Sprinkler to an Outdoor Environment

• Reliable communication range 270m
• Minimum number of packet transmissions at 315m

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Outline

1. Motivation and Requirements
2. Insight behind Solution
3. Formal Problem Statement and Algorithms
4. Analysis and Comparison
5. Conclusion

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Sprinkler Implementation
EmStar

• Powered by
• Debugging utilities
• For testbed setup EmView
• For deployment setup
• CDS monitoring and reporting of breakage to the
  base station
• Status devices to read parentID, current phase,
  etc
• Applications using Sprinkler
• File broadcast for stargate
• Command broadcast for stargate

• Application using Sprinklers CDS and TDMA
  algorithms
• Pursuer and Evader tracking service for XSM
  (demonstrated at NEST Final Experiment05 ,
  Berkeley) in TinyOS

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Anatomy of XSS

• XSS Extreme Scaling Stargate
• Stargate
• SMC 2532W-B High Power IEEE 802.11b PCMCIA card
• BU-303 GPS mouse via USB
• External antenna connection

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Form Factor Comparison
iPod nano
Stargate
3.5'
1.6'
2.49'
1.42 oz
1.5 oz
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Kansei The 2nd TinyOS Technology Exchange at
Berkeley, 2005

• A testbed containing 200 pairs of XSSs and XSMs
• A multi-hop IEEE 802.11 network
• Using attenuators and S/W Tx power control
• Applications
• Debugging
• Measuring performances of protocols
• Web interface for experimentations
• http//exscal.nullcode.org/kansei

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Scalability of Sprinkler
Hops ?
Density ?
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Scalability of Sprinkler Density ?
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Comparison

• Existing reliable bulk data dissemination
  services
• Deluge
• Infuse
• MNP
• PSFQ
• Deluge protocol
• Doesnt uses CDS and TDMA
• Uses sender suppression technique to reduce
  number of packet transmissions
• Commonly used service for mote reprogramming
• Simulation and experiment setup
• A 7x7 network with a base station at a corner
• Payload of 240 packets

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Performance Packet Transmissions
Deluge
Sprinkler
Source
Source
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Performance Latency
Deluge
Sprinkler
Source
Source
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Outline

1. Motivation and Requirements
2. Insight behind Solution
3. Formal Problem Statement and Algorithms
4. Analysis and Comparison
5. Conclusion

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Conclusion

• Sprinkler Reliable and energy efficient data
  dissemination service The 26th IEEE Real-Time
  Systems Symposium at Miami, 2005
• Energy efficient
• Reduces packet transmissions
• Scalable
• Constant time algorithms
• Low latency
• Pipelines transmissions in space
• Future work
• Use of hexagon-shaped clusters instead of
  square-shaped clusters
• CDS and D-2 vertex coloring in the presence of
  holes of bounded size and regular shape