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ENERGY-EFFICIENT TARGET TRACKING IN SENSOR NETWORKS USING SLEEP

SCHEDULING

Presented byK.Sumathi

811311805002

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BASE PAPER DETAILS

TITLE :Probability-Based Prediction and Sleep Scheduling for Energy Efficient

Target Tracking in Sensor Networks

AUTHOR(S) :Bo Jiang, Binoy Ravindran, Hyeonjoong Cho

TRANSACTION DETAILS :IEEE Transaction on Mobile

Computing, Vol 12, No. 4PUBLISHED DURING :April 2013

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OBJECTIVE

• To improve energy efficiency using Probability-basedPrediction and Sleep Scheduling Protocol (PPSSP).

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INTRODUCTION

• Process - fixed position to dynamic position.

• To access services anyplace, anytime and anywhere.

• Capable of performing Operation (gathering information and communicating with other connected nodes in a network).

• Input – Signal (Light, heat, motion and pressure).

• Output – Human readable form.

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DIAGRAMMATIC REPRESENTATION OF SENSOR NODE

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APPLICATIONS OF WIRELESS SENSOR NETWORK

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ISSUES IN SENSOR NETWORKS

• Energy efficiency is to be enhanced.

• QoS did not provide to predict the target.

• Target is based on specific location.

• Low tracking coverage.

• Sleeping node missing the target.

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ENERGY SAVING MECHANISM

• Duty Cycling.

• Clustering.

• On-Demand wake-up scheme.

• Energy Efficient Scheduling.

• Smart Sleeping.

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LITERATURE SURVEY

• Binary Sensor Model

• Prediction - Based Energy Saving Scheme • Node Sleeping Scheduling

• Grid Based Co-ordinated Routing Algorithm

• Smart Sleeping Policies

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BINARY SENSOR MODEL ( Aslam et al., 2003 )

• Sensor send a single bit of information.

• Save Energy.

• Binary Sensor Network - Each sensor can supply one bit of information only

• Plus Sensor :Object is approaching• Minus Sensor :Object is moving away

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BINARY SENSOR MODEL Cont…

• Plus and Minus Sensors - form a convex hull.• Two convex hulls are disjoint.• Separated by the normal vector to the object.• Uses tracking algorithm.

BINARY SENSOR NETWORK

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Example - Sound Level• Sensor simply report whether the sound is getting

louder or quieter. [Using single bit information]

Disadvantages• Only give accurate prediction about the direction of

object.• Do not have enough information content to identify

the exact object location.

BINARY SENSOR NETWORK Cont…

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PREDICTION BASED ENERGY SAVING (PES)(Yingqi et al., 2004)

PES consists of three methods

Prediction Model ─ which predict the future movement of an object.

Wake up Mechanism ─ decide which nodes will be the target node.

Recovery Mechanism ─ is initiated when the network loses the track of an object.

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WAKE UP MECHANISM

Disadvantages• Only applicable for static area.• Example: Forest.

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NODE SLEEPING SCHEDULING (Qing et al., 2005)

• BOUNDED-DELAY– Sensing coverage mechanism. – Maximize the network lifetime.

• DETECTION DELAY– Ensure Coverage Rotation within some finite interval of time.

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NODE SLEEPING SCHEDULING Cont...

Detection Delay- Each node chooses a wakeup time.- Each node re-calculate its wakeup time exactly, corresponding to neighbor node.

- Minimum time interval can be calculated using Ton = Tw + Ts + Tp

where, Tw = Warm up TimeTs = Sampling EnvironmentTp = Processing Time

Disadvantages• Does not provide continuous tracking.• Chance to miss the target (Rotation).

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COVERAGE ROTATION

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Methods Used1. Co - ordinator Election2. Grid – Size Estimation3. Load Balancing

1. Co-ordinator Election– The node with the largest ID in a grid is elected as

the grid co-ordinator.– Coordinator runs out of energy, the node with the

2nd highest ID become the new co-ordinator's.

GRID BASED CO-ORDINATED ROUTING ALGORITHM( Robert et al., 2007 )

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Co - Ordination Election Simulation

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METHODS USED Cont…

2. Grid-Size Estimation- Sensor field is divided into square shape grid.- Grid size is defined by user.- Calculate the upper bound for the square grid

with width r is calculated as r2 = (2r)2 ≤ Rn

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where Rn => maximum transmit distance

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3. Load Balancing– Initially all the nodes are assigned the same rank.– Coordinators elect one node per grid.– If node energy>25% of battery life,

• its rank is raised by 1.– If node energy<25% of battery life,

• its rank is raised by 2.

Disadvantage– Network with the grid sizes around 150m.

METHODS USED Cont…

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SMART SLEEPING POLICIES( Jason et al., 2008 )

• Sensor node may put into sleep mode with a timer.• Timer determine the sleep duration.

Disadvantages– Sleeping node may miss the target.– Does not provide Quality of service.

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PROPOSED SYSTEM

• Target prediction schemes based on • Kinematics rules.• Theory of probability.

• PPSSP not only predicts a target’s next location, but also describes the probabilities with which it moves along all the directions.

• Components1) Target prediction2) Awakened node reduction3) Active time control

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SYSTEM ARCHITECTURE

S1

S2

S5

S3

S8

S6

S4

S7

S9

S0

S10

S11

S12

SINK

Broadcast Alarm Message Send Prediction Details Receive Prediction Details

Sensing Area

Awakened NodeDetect a

Target

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REFERENCES1. Aslam Javed, Zack Butler, Florin Constantin, Valentino Crespi, George

Cybenko, Daniela Rus, “Tracking a Moving Object with a Binary Sensor Network”, ACM, Nov 2003.

2. Jason A. Fuemmeler, and Venugopal V. Veeravalli, “Smart Sleeping Policies for Energy Efficient Tracking in Sensor Networks”, IEEE Trans. Signal Processing, vol.56, May 2008.

3. Q.Cao, T.Abdelzaher, T.He, and J. Stankovic, “Towards Optimal Sleep Scheduling in Sensor Networks for Rare Event Detection”, proc. Fourth International Conference, Information Processing in Sensor Networks, 2005.

4. Robert Akl, Uttara Sawant, “Grid-based Coordinated Routing in Wireless Sensor Networks”, IEEE 2007.

5. Yingqi Xu, Julian Winter, Wang-Chien Lee, “Prediction-based Strategies for Energy Saving in Object Tracking Sensor Networks” Proc. IEEE International Conference, Mobile Data Management, 2004.