Trajectory-Based Forwarding Mechanisms for Ad-Hoc Sensor Networks Murat Yuksel, Ritesh Pradhan, Shivkumar Kalyanaraman Electrical, Computer, and Systems

Trajectory-Based Forwarding Mechanisms for Ad-Hoc Sensor

Networks

Murat Yuksel, Ritesh Pradhan, Shivkumar KalyanaramanElectrical, Computer, and Systems Engineering Department

Rensselaer Polytechnic Institute, Troy, [email protected], [email protected], [email protected]

Rensselaer Polytechnic Institute, Troy, NY 2

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


MotivationThere may be several cases where shortest-path routing is not suitable for the application:To measure some parameters for a riverTo obtain terrain knowledge of a hostile areaTo use safer locations for important data transmissions

Such application-specific requirements are particularly important for sensor networks


Motivation (cont’d)

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”


Overview of TBRSource 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.


Overview of TBR (cont’d)What happens when a packet travels in the network? Source encodes the trajectory into the packet’s 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”?


source

destination

Control pt -2

Control pt -1

Bezier Curves for TBRWe 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.


Bezier Curves for TBR (cont’d)

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.


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.


Forwarding Algorithms for TBR (cont’d)

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.

Random - node randomly forwards to one of its neighbor



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



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.


Long Trajectories For a generalized long trajectoryWe 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).


Long Trajectories (cont’d)SINs (i.e. I1, I2 below) do special forwarding. They remove info about last curve’s control points and

replaces it with that of the next piece’s control points from packet’s header and inserts the next one’s control points.

Rest of the nodes fwd packets to nodes that are closest to curve and you advance least on curve.

Curve 3

DCurve 1

Curve 2

S

I1

I2


Simulation ResultsUsed NS-2Number of nodes – 50, 100, 150, 200.Area – 250mX500mThree different trajectories:

Circular Zigzag –

Single-piece Zigzag --

Multi-piece

No mobility yet


Simulation Results (cont’d)A long trajectory composed of two concatenated cubic Bezier curves


Simulation Results (cont’d)

Deviation of various forwarding strategies from the circular trajectory



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



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


Simulation Results (cont’d) Normalized path length in various forwarding

strategies applied on the single-piece zigzag trajectory



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


Future Work Extensive simulation of multi-piece caseAmount of state maintained at SINsStrategies 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


Thank you !!

Documents

Trajectory-Based Forwarding Mechanisms for Ad-Hoc Sensor Networks Murat Yuksel, Ritesh Pradhan, Shivkumar Kalyanaraman Electrical, Computer, and Systems