Trajectory-Based Forwarding Mechanisms for Ad-Hoc Sensor Networks

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Trajectory-Based Forwarding Mechanisms for Ad-Hoc
Sensor Networks

• Murat Yuksel, Ritesh Pradhan, Shivkumar
  Kalyanaraman
• Electrical, Computer, and Systems Engineering
  Department
• Rensselaer Polytechnic Institute, Troy, NY
• yuksem_at_ecse.rpi.edu, rspradhan_at_alum.rpi.edu,
  shivkuma_at_ecse.rpi.edu

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Outline

• Motivation
• Overview of Trajectory-Based Routing (TBR)
• Bezier curves for TBR
• Forwarding algorithms for TBR
• Long trajectories
• Simulation results
• Future work

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Motivation

• There may be several cases where shortest-path
  routing is not suitable for the application
• To measure some parameters for a river
• To obtain terrain knowledge of a hostile area
• To use safer locations for important data
  transmissions
• Such application-specific requirements are
  particularly important for sensor networks

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Motivation (contd)

• Example Consider a battlefield with east-side of
  mountains being friendly area.
• Application can request to
• obtain view of west-side of the mountains
• transmit secure information to allied soldiers
  through east-side of the mountains

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Overview of TBR

• Source Routing (SR)
• Source inserts entire route into each packet,
  e.g. SBR, DSR.
• Very flexible for applications, but causes too
  large packet headers.
• Greedy Routing (GR)
• Assuming a positioning service, each packet is
  forwarded to the neighbor closest to the
  destination, e.g. GPSR, CR.
• Fixed-size, short packet headers, but not
  flexible for applications.
• Trajectory-Based Routing (TBR)
• Proposed by Nath and Niculescu from Rutgers
  University.
• Represents the whole path as a parametric curve
  and encodes it into each packet.
• Geographic routing protocol, and requires
  positioning service.

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Overview of TBR (contd)

• What happens when a packet travels in the
  network?
• Source encodes the trajectory into the packets
  header.
• All nodes forward the packet based on a
  predefined forwarding strategy.
• After packet arrival, the intermediate nodes
  decode the trajectory and forwards the packet
  along the trajectory.
• The packet gets forwarded until it reaches the
  destination or is dropped.
• TBR is a middle-ground between SR and GR.
• Since a parametric curve can form any path (e.g.
  circle, straight line, oscillatory lines), it
  gives more flexibility to define the path.
  similar to SR
• Since nodes decode the trajectory, i.e. stateless
  similar to GR
• One important issue is how should we encode the
  trajectory into packets headers?

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Bezier Curves for TBR

• We propose to encode paths by using Bezier
  curves.
• Cubic Bezier curves (2 control pts source
  destination) are easy to handle.
• A Cubic Bezier curve is represented in parametric
  form

• Q(0) is the source point, and Q(1) is the
  destination point.

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Bezier Curves for TBR (contd)

• If (x0,y0), (x1,y1), (x2,y2) and (x3,y3) are
  known, then the constant vectors A, B C can be
  calculated as
• Each packet header contains locations of source
  (x0,y0), destination (x3,y3) and control points
  (x1,y1), (x2,y2).
• So, when a packet arrives, each node
• Decodes the trajectory by performing the above
  calculations
• Figures out which neighbor to forward the packet,
  based on forwarding strategy.

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Forwarding Algorithms for TBR

• Terminology
• di closest distance of node Ni to the
  trajectory curve
• ti value of the time parameter at the point
  where node Ni is closest to the curve residual
  of node Ni

• The residual ti of node Ni can also be
  interpreted as projection of the node on the
  curve.
• neighbor of Ni set of nodes that are in
  transmission range of Ni and have a residual
  greater than ti.

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Forwarding Algorithms for TBR (contd)

• Random - node randomly forwards to one of its
  neighbor

• Closest-To-Curve (CTC) - node forwards to its
  neighbor closest to the curve.
• Least Advancement on Curve (LAC) node forwards
  to its neighbor with least advancement on the
  curve.

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Forwarding Algorithms for TBR (contd)

• CTC-LAC node forwards to its neighbor with LAC
  but is also close to the curve (within a
  predefined distance).
• Most Advancement on Curve (MAC) node forwards
  to its neighbor which is nearest to the
  destination.

Failure of CTC and MAC
Failure of LAC
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Forwarding Algorithms for TBR (contd)

• Lowest Deviation from Curve (LDC) node forwards
  to its neighbor with lowest deviation from curve.
• Calculation of areas is computationally
  intensive.
• Can be approximated by numerical techniques.

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Long Trajectories

• For a generalized long trajectory
• We brake the trajectory into multiple cubic
  Bezier curves.
• Before data traffic, source performs signaling
  and sends a probe packet that include all the
  control points (more than two) for the trajectory
  and starting locations of the smaller cubic
  Bezier curves (i.e. Intermediate Point (IP) ).
• Nodes close to an IP will contend for being a
  Special Intermediate Node (SIN).

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Long Trajectories (contd)

• SINs (i.e. I1, I2 below) do special forwarding.
• They remove info about last curves control
  points and replaces it with that of the next
  pieces control points from packets header and
  inserts the next ones control points.
• Rest of the nodes fwd packets to nodes that are
  closest to curve and you advance least on curve.

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Simulation Results

• Used NS-2
• Number of nodes 50, 100, 150, 200.
• Area 250mX500m
• Three different trajectories
• Circular
• Zigzag Single-piece
• Zigzag -- Multi-piece
• No mobility yet

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Simulation Results (contd)

• A long trajectory composed of two concatenated
  cubic Bezier curves

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Simulation Results (contd)

• Deviation of various forwarding strategies
  from the circular trajectory

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Simulation Results (contd)

• Normalized path length in various forwarding
  strategies applied on the circular trajectory

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Simulation Results (contd)

• Deviation of various forwarding strategies
  from the single-piece zigzag trajectory

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Simulation Results (contd)

• Normalized path length in various forwarding
  strategies applied on the single-piece zigzag
  trajectory

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Simulation Results (contd)

• Deviation from the trajectory and normalized
  path length for the multi-piece zigzag trajectory
  with CTC-LAC forwarding strategy

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Future Work

• Extensive simulation of multi-piece case
• Amount of state maintained at SINs
• Strategies for selecting SINs
• Simulation with various mobility patterns
• Analysis of success rate (i.e. reaching
  destination) for the forwarding strategies
• Resilience strategies to increase success rate

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Thank you !!