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Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network Atul Verma, Hemjit Sawant and Jindong Tan Department of Electrical and Computer Enginee ring Michigan Technological University Houghton, USA Speaker: stephan

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Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network. Atul Verma, Hemjit Sawant and Jindong Tan Department of Electrical and Computer Engineering Michigan Technological University Houghton, USA Speaker: stephan. Introduction. A hybrid sensor network. - PowerPoint PPT Presentation

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Page 1: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network

Selection and Navigation of Mobile Sensor Nodes Using a

Sensor NetworkAtul Verma, Hemjit Sawant and Jindong Tan

Department of Electrical and Computer EngineeringMichigan Technological University

Houghton, USA

Speaker: stephan

Page 2: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network

Introduction

• A hybrid sensor network.

• Mobile sensor nodes (MSNs) and static sensor nodes can enhance each other’s capability:– MSN can reallocate sensing, networking, and

computing resources to provide required coverage and sensing accuracy.

– static sensors can guide the MSN to solve some navigation problem.

Page 3: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network
Page 4: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network

Problem Formulation

Page 5: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network

Modeling of Sensor Network

• n: num of static sensor nodes• m: num of mobile sensor nodes • Mobile sensor nodes:

– M = { M1, M2, …, Mm}

• Configuration of MSN, Mi :

– qi (t) = [xi, yi, θi]T

• i = 1, 2, ..m

• xi, yi: the coordinates of MSN, Mi

• θi: the orientation of the MSN with respect to its local coordinate system.

Page 6: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network

• Dynamics of Mi:

– ui: the navigational control input• Provide MSN with the direction towards which it sh

ould navigate.

• Mobile sensor nodes:– S = { S1, S2, …, Sn}

• Configuration of static sensor nodes:

Page 7: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network

Credit Field Based Navigation

• A cluster forms

• cluster leader: determine whether and how many MSNs are required.– Select– Build up the Navigation Field– Navigation of MSN

Page 8: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network

• Select– find available MSNs using WREQ packet (bro

adcasted by leader) • MSN reply its weight back to the leader by reversin

g the route through which the WREQ propagated.• Lower is the weight of the MSN, greater is its prob

ability of navigation of the region of phenomenon.

Page 9: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network

• Build up the Navigation Field (using ADV packet)

Page 10: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network

• Navigation of MSN

Page 11: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network
Page 12: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network

• The navigational controller ui is calculated on the basis of virtual attractive force generated by each static sensor which have the maximum credit field value during each phase of broadcast of navigation packet.

Page 13: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network

• The total energy associated with a MSN is defined:

– pij is a vector from MSN, Mi to static sensor nodes Sn in the coordinate frame

– || pij || = – ki and kiv are parameters of virtual potential en

ergy and kinetic energy of the MSN.

Page 14: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network

• ui :

• Fi is the virtual navigation force generated by static sensor nodes which are at the maximum credit value during each phase of broadcast of navigation packet.

Page 15: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network

Weight of a Mobile Sensor Node

• three metrics to calculate the weight of a MSN:– coverage: leave a smaller coverage hole.– power: saving energy of MSN– distance

Page 16: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network

• coverage :– don’t know the topology of the whole network:

• using Voronoi cell approach to determine the coverage of MSN.

Page 17: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network
Page 18: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network

• Power:– greater the power of MSN, greater is the dista

nce it can traverse and less will be its weight.

Page 19: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network

• Distance:– don’t know the topology of the whole network:

• the total num of intermediate nodes through which the WREQ travels is used.

– more num of hops more is the weight of MSN.

Page 20: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network

• Weight = Voronoi_cell * distance / power– lower is the weight, more is the probability of

MSN reaching the goal.

Page 21: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network

Simulation

• 500 x 500 meters.

• Phenom node

• Three scenarios:– a uniformly distributed sensor network– a randomly distributed sensor network– a sensor network with a “coverage hole” in it

which could represent an “obstacle”.

Page 22: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network

uniformly distributed sensor network

Page 23: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network

randomly distributed sensor network

Page 24: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network

a sensor network with a “coverage hole”

Page 25: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network

Dynamic events

• Mobile phenom

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Page 27: Selection and Navigation of Mobile Sensor Nodes Using a Sensor Network

Conclusion

• The algorithm is robust to failures of static sensor.

• The algorithms have been verified in an ns-2 environment.