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Grid-Based Access Scheduling for Mobile Data Intensive Sensor Networks

C.-K. Lin, V. Zadorozhny and P. Krishnamurthy

IEEE International Conference on Mobile Data Management, 2008

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Outline

Introduction GLASS protocol description GLASS analysis Simulation results Conclusion

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Introduction

MSN applications have stringent requirements on the response time

Minimizing sensor response time and minimizing energy consumption is crucial

Even high rate wireless networks (e.g., IEEE 802.11) use best-effort service that can lead to packet loss (from collisions)

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Grid based Latin Squares Scheduling Access (GLASS) protocol description System model GLASS protocol Time slot assignment

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System model

Sensors are evenly deployed in a field Every sensor transmits or receives on a

common carrier frequency Time synchronization is managed by a Base

Station (BS) using beacons

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GLASS protocol

Grid searching Transmission frame assignment Time slots assignment

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Grid searching

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Transmission frame assignment

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Transmission frame

We define a TF as a group of continuous time slots

The length of TF is configured differently for different sensor distributions

If the sensors are not evenly distributed, α will increase

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Time slots assignment

Each sensor performs neighborhood discovery to prepare for time slots scheduling

We use Latin Squares (LS) to assign time slots for sensors

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Example

1 4

2

53

14

2

5

3

1 4

2

5 3

1 4

253

1 4

2

5 3

1 4

25

3

14

2

53

14

2 5

3

1 4

2

5

3

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Collision avoidance near intersection of grids

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Example

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2

1

1

4

23

1

2

5

62

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GLASS analysis

Theorem 3.1: There is no conflicting time slot assignment between any two sensors within any grid cell when the protocol converges. (Proof omitted).

Theorem 3.2: There is no conflicting time slot assignment between any two sensors from any two different grid cells when the protocol converges. (Proof omitted).

Theorem 3.3: There is no conflicting time slot assignment between any two sensors when the protocol converges. (Proof omitted).

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Simulation results

Simulator: NS-2 Compare the GLASS protocol with the IEEE

802.15.4 CAP mode and DRAND Set the channel data rate to 250 Kbps Set the sensor transmission range to 15

meters The packet size is 70 bytes

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Distributed Randomized TDMA Scheduling (DRAND)

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Transmission efficiency(1/2)

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Transmission efficiency(2/2)

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Scalable network

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Overhead evaluation

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Impact of sensor mobility(1/2)

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Impact of sensor mobility(2/2)

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Conclusion

GLASS efficiently alleviates conflicting time slots schedules

This approach is especially suitable for the mobile data intensive sensor network with frequently changing topology