Robust Gridbased Deployment Schemes for Underwater Optical Sensor Networks

1
Robust Grid-based Deployment Schemes for
Underwater Optical Sensor Networks

• Abdullah Reza
• Department of Computing Science
• University of Alberta
• Edmonton, Alberta, Canada

2
Underwater Sensor Networks (UWSN)

• Allows us to monitor underwater environment which
  constitutes 70 of earths surface
• A new and evolving field of research
• Acoustic communication has been considered mostly
  for UWSN

3
Problems of Underwater Acoustic Communication

• Very low bandwidth (5 Kbps 2)
• Very slow propagation (1500 m/s 3)
• High error rate 4, 5
• High cost of acoustic modems 2
• unsuitable for applications with stringent b/w
  requirement (e.g., real-time and multimedia
  applications)

4
Optical Communication An Alternative of
Acoustic Communication

• We consider nodes with optical transceivers
• Low-cost and light LEDs and photodiodes
• Operation in blue/green visible ranges
• Point-to-point communication
• Advantage High bandwidth and fast propagation
  2, 9 ,10
• Disadvantage Shorter range and line of sight
  requirement 2, 9 ,10

5
Optical UWSN Design Challenges

• Intelligent Deployment (expensive nodes)
• Connectivity is not inherent
• Cost of Deployment (directional transceivers)

6
Problem Definition

• Design Goals
• 1) Robustness
• Deterministic (2-edge-connected)
• Probabilistic
• 2) Path Quality
• 3) Interface-count
• Per node constraint (Maximum 1, 2 and 3
  interfaces per node)
• Minimum total interface in the network

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Optical Interface Model 2

• Maximum 1 interface per node
• 2 or more interfaces per node

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Robust Deployment Maximum 1 Interface per Node

• One Hamiltonian Cycle Always possible with even
  number of rows and/or columns 12
• Robustness poor
• Path quality poor
• A Better Design 4 Hamiltonian Cycles

9
Robust Deployment Maximum 2 Interfaces per Node

• We use 4 undirected Hamiltonian Cycles
• Robustness
• 2-edge-connected
• Better than directed cycles
• Path Quality
• Better than directed cycles

10
Robust Deployment Maximum 3 Interfaces per Node

• Design Approach
• 1) Generate a 3-degree constrained shortest path
  spanning tree from the sink with minimum number
  of 3-d nodes (optimal pattern)
• 2) Add additional edges to make it
  2-edge-connected
• 3) Add additional edges to improve probabilistic
  robustness
• Introduce minimum number of 3-degree nodes in
  each step

11
Subproblem Quadrants
12
Lower Bound for Number of 3-d nodes in a Quadrant

• Theorem Consider a quadrant with sides of size m
  and n where mn. A sink is placed in a corner. A
  3-degree constrained shortest-path tree rooted at
  the sink and spanning all nodes inside and on the
  boundaries of the quadrant require at least (m-2)
  3-degree nodes.

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Optimal Pattern for a Quadrant
14
Do Optimal Patterns for Quadrants Give Optimal
Pattern for the Grid?

• Depends on whether or not 3-degree constraint is
  violated on the axes
• In any case, (l1l2l3l4) remains the lower
  bound
• We call LB (l1l2l3l4) ? li

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A Pattern for a Quadrant that Avoids Conflict on
the Axes

• A pattern that draws edges only from the vertical
  axis
• Has minimum number of 3-d nodes (li ) of y x
  but has minimum1 number of 3-d nodes (li1) if y
  gt x

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Pattern Applied on the Entire Grid

• Shortest path spanning tree from the sink with
  3-degree constraint
• Number of 3-degree nodes in the worst case is
  LB4 which can be shown to be actually LB3
• clockwise counterclockwise LB2 in worst case

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Summary of Proposed Deployments
TOP2
TOP3
TOP1
TOP4
TOP5
TOP6
18
Summary of Proposed Deployments 12x12 Grid
19
Static Evaluation of Deployment Topologies

• Two failure models
• Isolated Model 15
• Patterned Model 15
• Metrics Robustness Path Quality

20
Important Findings

• TOP6 offers almost 98 robustness even when each
  link is failed with 8 probability
• TOP6 offers almost 95 robustness even when three
  error blobs with dimension a60m and b4m are
  present in the grid
• TOP2 offers acceptable robustness if failures are
  always concentrated in a certain region

21
Dynamic Evaluation of Deployment Topologies

• Resilient Routing Protocols
• Memory-constrained Flooding (FLD)
• Dual Paths Protocol (DPP)
• Hop-by-Hop Acknowledgment with local update
  protocol (HHA)

22
Simulation Environment

• Single Packet generating source
• Ten packets generated per second, each with 1 Kb
  payload
• Three error blobs (20mx4m) moving at 15 cm/sec
  speed in the grid in a random-walk fashion

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Important Findings

• FLD supports highest resiliency (97 with TOP6)
  with shortest delay but incurs excessive
  transmissions
• DPP fails to utilize the inherent redundancies in
  the topology because of its static nature
• HHA supports resiliency almost as good as FLD
  with a small number of transmissions but with
  slightly increased delay
• TOP6 not only supports highest delivery ratio but
  also lowest delay (and transmissions for HHA)

24
Summary

• Robust deployment topologies for optical UWSN
  with 1, 2 and 3 interfaces per node constraints
• For 1 and 2 interfaces cases, topologies that
  utilize four directed and undirected Hamiltonian
  cycles in the grid, respectively.
• For 3 interfaces case, formulation pattern for a
  3-degree constrained shortest path spanning tree
  in the grid with arbitrary root and arbitrary
  dimension that results in (LB2) 3-degree nodes
  in the worst case.
• A series of deployment patterns built on the
  3-degree constrained shortest path tree that
  support higher degrees of robustness by
  introducing additional links in the network at
  strategic points.

25
Summary

• Static evaluation of the proposed topologies show
  that a very high degree of robustness (98) is
  maintained by TOP6 even at reasonably harsh
  conditions
• Dynamic evaluation of the proposed topologies
  with three simple routing protocols
• FLD achieves a very high degree of delivery ratio
  when applied on TOP6 but incurs excessive
  communication
• DPP fails to utilize the inherent redundancies of
  the proposed topologies
• HHA achieves delivery ratio as good as FLD with
  very small communication overhead but slightly
  higher average delay

26
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