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An Implementation Framework for Trajectory-Based Routing in Ad Hoc Networks

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An Implementation Framework for Trajectory-Based Routing in Ad Hoc Networks Murat Yuksel, Ritesh Pradhan, Shivkumar Kalyanaraman Electrical, Computer, and Systems ... – PowerPoint PPT presentation

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Title: An Implementation Framework for Trajectory-Based Routing in Ad Hoc Networks


1
An Implementation Framework for
Trajectory-Based Routing in Ad Hoc Networks
  • Murat Yuksel, Ritesh Pradhan, Shivkumar
    Kalyanaraman
  • Electrical, Computer, and Systems Engineering
    Department
  • Rensselaer Polytechnic Institute, Troy, NY

2
Outline
  • Motivation
  • Overview of Trajectory-Based Routing (TBR)
  • Bezier Curves for TBR
  • Forwarding Algorithms for TBR
  • Long/Complex Trajectories
  • Contributions
  • Future Work

3
Motivation
TE is essential for ad hoc networks
Proactive routing does NOT work!
  • Wireless ad hoc networks
  • An emerging part of our technology, e.g. laptops,
    PDAs, watches, cars,
  • Very scarce resources e.g. capacity, power,
    memory
  • Traffic engineering requires flexibility in
    routing
  • Multi-path capability
  • Major issues
  • Ad hoc nature of nodes
  • Mobility
  • Dynamic topology causes continuous update to
    routing tables.

TE in ad hoc networks require new routing
building blocks
4
Motivation (contd)
  • Why TBR is a viable routing building block for
    TE?
  • Multi-path capability in a wireless, multi-hop,
    ad hoc environment
  • Possible application to p2p with virtual
    geographic locations

5
Motivation (contd)
  • Application-specific requirements
  • particularly important for sensor networks
  • Area of interest
  • Take pictures of the lake
  • Measure temperature around an experimental area
  • Area of disinterest
  • Route secure info around the unsafe area
  • Route more traffic around the congested area

6
Overview of TBR
  • Source Routing (SR)
  • Source inserts all the route into each packet,
    e.g. SBR, DSR.
  • Very flexible for applications, but causes too
    large packet headers.
  • Greedy Routing (GR)
  • Each packet is forwarded to the neighbor closest
    to the destination, e.g. FACE, Greedy Perimeter
    Stateless Routing (GPSR), Cartesian Routing (CR).
  • Fixed-size, short packet headers, but not
    flexible for applications.
  • Trajectory-Based Routing (TBR)
  • Proposed by a group from Rutgers University.
  • Represents the whole path as a parametric curve
    and encodes it into each packet.

7
Overview of TBR (contd)
  • TBR is a geographic routing protocol, and
    requires a positioning service
  • TBR is a middle-ground between SR and GR.
  • Since a parametric curve can form any path (e.g.
    circle, straight line, curly lines), it gives
    more flexibility for the source to define the
    path. similar to SR
  • Since the intermediate nodes decode the
    trajectory, they do not have to keep state.
    similar to GR

Source Routing i.e. flex, large header
Greedy Routing i.e. no header or state, but no
flex
Trajectory-Based Routing
8
Overview of TBR (contd)
  • So, how does it work?
  • What happens when a packet travels in the network?

D
S
  • How to encode the trajectory into packets
    headers?

9
Bezier Curves for TBR
  • Can we use Bezier curves?
  • Cubic Bezier curves
  • 2 control pts source destination
  • easy to handle.
  • Represented in parametric form

Q(1) is the destination point
Q(0) is the source point
  • t is the time parameter.

10
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
  • Given that
  • Each packet header contains locations of source
    (x0,y0), destination (x3,y3) and control points
    (x1,y1), (x2,y2).
  • Each node maintains neighbor table.
  • 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.
  • What is a viable forwarding strategy?

11
Forwarding Algorithms for TBR
  • Terminology
  • di closest distance of node Ni to the curve
  • ti time parameter at the point where node Ni is
    closest to the curve time of node Ni
  • The time ti of node Ni can also be interpreted as
    projection of the node on the curve.
  • neighbor of Ni nodes that are in transmission
    range of Ni and have a time greater than ti.

12
Forwarding Algorithms for TBR (contd)
  • Random - randomly forward to one the neighbors
  • Closest-To-Curve (CTC) - to the neighbor with
    smallest distance to the curve.
  • Least Advancement on Curve (LAC) to the
    neighbor with smallest time on the curve.

13
Forwarding Algorithms for TBR (contd)
  • Several other algorithms are possible..
  • CTC-LAC to the neighbor with smallest time but
    also stands within a predefined distance from the
    curve.
  • Most Advancement on Curve (MAC) to the neighbor
    with largest time.
  • CTC-MAC to the neighbor with highest time but
    also stands within a predefined distance from the
    curve.
  • Failure cases are possible..

14
Forwarding Algorithms for TBR (contd)
  • Failure of LAC

15
Forwarding Algorithms for TBR (contd)
  • Failure of CTC and MAC

16
Forwarding Algorithms for TBR (contd)
  • Lowest Deviation from Curve (LDC) node forwards
    to its neighbor with lowest deviation from curve.
  • Deviation deviated area from the curve per unit
    curve distance, i.e.

17
Forwarding Algorithms for TBR (contd)
  • Lowest Deviation from Curve (LDC)
  • Area calculations are computationally intensive.
  • Can be approximated by numerical techniques.
  • Slice the area by parallel lines similar to
    Riemann Sums in numerical integration

18
Simulation Results
  • NS-2
  • Area 250mX500m
  • Different trajectories
  • Circular
  • Zigzag
  • No mobility yet

19
Simulation Results (contd)
  • Deviation from the circular trajectory

20
Simulation Results (contd)
  • Normalized path length on the circular
    trajectory

21
Simulation Results (contd)
  • Deviation from the zigzag trajectory

22
Long/Complex Trajectories
  • How to encode long/complex curves?
  • longer curve ? larger packet header
  • Split the curve into simpler pieces
  • Each piece could be represented by a cubic Bezier
    curve
  • The complete trajectory is concatenation of the
    pieces.
  • Source performs signaling and sends a control
    packet that include
  • end locations of the cubic Bezier curves, i.e.
    Intermediate Point (IP)
  • all the control points
  • The nodes closest to the IPs will be the Special
    Intermediate Nodes (SINs).

23
Long/Complex Trajectories
  • How to encode long/complex curves?
  • longer curve ? larger packet header
  • SINs (i.e. I1, I2) do special forwarding.
  • Store the next Bezier curves control points
  • Update the packet headers with that of the next
    Bezier curves control points

24
Contributions
  • Our contributions
  • An architecture to deploy TBR for long/complex
    trajectories.
  • A locally optimal forwarding strategy Lowest
    Deviation from Curve (LDC)
  • A method of encoding/decoding trajectories by
    using Cubic Bezier curves.
  • A simulation-based evaluation of several
    forwarding strategies.

25
Future Work
  • Our ongoing work on TBR
  • A testbed deployment in RPI-CWN.
  • Calculation of optimal curve to avoid certain
    spots.
  • Finding optimal route for a given trajectory with
    global topology knowledge.
  • Future work on TBR
  • Optimal split of long/complex trajectories.
  • Analysis of the signaling overhead in mobile
    environments.
  • Hybrid trajectory encoding techniques frequency
    and space-time
  • Resilience techniques for different forwarding
    strategies.

26
THE END
Thank you!
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